National Positioning Infrastructure

National Positioning Infrastructure:

Technical, Institutional and Economic Criteria for Coordinating Access to Australia’s GNSS CORS Infrastructure

Grant J. Hausler BGeomE (Hons). GCertCommResSt

Submitted in total fulfilment of the requirements of the degree of Doctor of Philosophy

March 2014

Department of Infrastructure Engineering The University of Melbourne

This work has been supported by the Cooperative Research Centre for Spatial Information, whose activities are funded by the Australian Commonwealth's Cooperative Research Centres Programme.

ABSTRACT

Satellite positioning technology is embedded in the global information economy. Society uses Global Navigation Satellite Systems (GNSS) to derive Position, Navigation and Timing (PNT) information for transport, engineering, construction, agriculture, surveying, meteorology, finance, Earth sciences, emergency response and research activities. Consumer demand for PNT information has stimulated market growth for value‐added GNSS services that enhance accuracy, coverage and service performance.

In Australia, governments do not currently invest in space assets for PNT, but deploy GNSS ground infrastructure and operate positioning services that build integrity in the national datum, and facilitate access to this datum using Continuously Operating Reference Stations (CORS). Industry providers have developed positioning services by licensing data from government‐owned CORS where demand is strong, and deploy additional CORS where commercial benefits outweigh fixed‐cost investment.

However, a lack of technical, institutional and economic coordination between governments and industry has led to duplication and over‐investment which, based on findings from this research, has limited high accuracy positioning coverage to less than 9% of the country’s land mass. No individual provider enables access to this existing coverage region, and limited research has addressed the barriers to entry that hamper coordination in supplying CORS infrastructure, which in turn limits access to high accuracy positioning services.

Technical, institutional and economic barriers are identified and examined through this research to contribute spatial and economic evidence supporting the development of a National Positioning Infrastructure (NPI) in Australia. Recommendations for coordinating access to existing and future CORS infrastructure are summarised within the NPI Planning Framework to outline criteria for minimising future investment costs, and to maximise the utility of existing investment. New evidence is presented in an economic context on the public good and commercial benefits of producing and distributing authoritative and standardised multi‐GNSS position information through a single point of access from the NPI. These findings are consolidated within the NPI Planning Framework to inform future policy and investment decisions, including recommendations that will support implementation of Australia’s Satellite Utilisation Policy and the Australian Government NPI Plan.

iii

DECLARATION

This is to certify that

i. the thesis comprises only my original work towards the PhD,

ii. due acknowledgement has been made in the text to all other material used,

iii. the thesis is less than 100,000 words in length, exclusive of tables, maps, bibliographies and appendices.

Grant J. Hausler

Date

ACKNOWLEDGEMENTS

First and foremost, thank you to my supervisor Dr Philip Collier for his unwavering support and commitment to this research. Your interest, guidance, expertise, communication, professionalism, patience and encouragement define the notion of ‘leading by example’.

To my co‐supervisor, A/Prof Allison Kealy, for encouraging me to begin this journey, and for contributing such a broad network of resources to this research, and to the department as whole.

To the University of Melbourne and the Department of Infrastructure Engineering (Geomatics), thank you for the opportunity to undertake this research. I am grateful for your ongoing administrative and financial support, including funding through a Melbourne University Overseas Research Experience Scholarship (to Nottingham University, UK) as well as departmental contributions for conference attendance. I extend this thank you to Melbourne Business School and the Melbourne School of Graduate Research for additional scholarship funding to complete a Graduate Certificate in Commercialisation for Research Students, which inspired the economic direction of this work. This research was also made possible through Australian Postgraduate Award funding from the Australian Government.

To the Cooperative Research Centre for Spatial Information (CRCSI), thank you for the network of industry, government and academic resources and expertise you not only brought to this research, but bring to the spatial sector as a whole. Thank you for allowing access to your amenities and for your financial support through top‐up scholarships and additional conference support.

There has been ongoing input from numerous government and industry participants nationally and internationally towards this research. Special thanks to James Millner and the team at GPSnet within Victoria’s Department of Environment and Primary Industries for introducing me to the intricacies of CORS network management, both technically and institutionally. To Gary Johnston, John Dawson and the team at Geoscience Australia, thank you for the opportunity to build on, and contribute value from this research at a national level.

To my colleagues at the CRCSI and Melbourne University, thank you for your interest in this research and for our ongoing discussions on a diverse array of interrelated research themes. Special thanks to Eldar Rubinov, Christos Stamatopoulos and Simon Fuller for supporting and discussing this research, and for reminding me to enjoy the social side of research life.

To Martin Hale, for our endless discussions on the objectives and relevance of this research in a national context, and for your mentorship on the research experience itself.

And finally, to my family, for your confidence and support in pursuing this challenge, and every challenge I embark on. Your support and encouragement is most important of all.

vii

To my family

viii

CONTENTS Abstract ...... ii Declaration ...... iv Acknowledgements ...... vi List of Figures ...... xiv List of Tables ...... xv Chapter 1 Introduction ...... 1 1.1 Problem Statement ...... 4 1.2 Research Hypothesis ...... 5 1.3 Research Rationale ...... 6 1.4 Significance of the Research ...... 7 1.4.1 National Positioning Infrastructure Plan ...... 7 1.4.2 Thesis Scope ...... 8 1.5 Research Aims & Tasks ...... 9 1.6 Thesis Outline ...... 10 1.6.1 NPI Planning Framework ...... 12 Chapter 2 Space Policy & Satellite Positioning Systems ...... 15 2.1 Introduction ...... 16 2.1.1 Research Rationale ...... 16 2.2 Space Policy ...... 17 2.2.1 US Space Policy ...... 18 2.2.2 Russian Space Policy ...... 20 2.2.3 European Space Policy ...... 20 2.2.4 Japanese Space Policy ...... 21 2.2.5 Chinese Space Policy ...... 21 2.2.6 Indian Space Policy ...... 22 2.2.7 Australian Space Policy ...... 22 2.3 Global Navigation Satellite Systems ...... 25 2.3.1 Early Radionavigation Systems ...... 25 2.3.2 Geodesy ...... 27 2.3.3 GPS (US) ...... 27 2.3.3.1 Space Segment ...... 28 2.3.3.2 Selective Availability ...... 29 2.3.3.3 Control Segment ...... 30 2.3.3.4 User Segment ...... 31 2.3.3.5 GPS Modernisation ...... 31 2.3.4 GLONASS (Russia) ...... 32 2.3.4.1 Space Segment ...... 33 2.3.5 GALILEO (Europe) ...... 33 2.3.6 BEIDOU (China) ...... 35 2.4 Regional Navigation Satellite Systems ...... 37 2.4.1 QZSS (Japan) ...... 37 2.4.2 IRNSS (India) ...... 38 2.4.3 Space Based Augmentation Systems ...... 38 2.4.3.1 WAAS (US) ...... 40 2.4.3.2 EGNOS (Europe) ...... 41 2.4.3.3 MSAS (Japan) ...... 43 2.4.3.4 SDCM (Russia) ...... 43 2.4.3.5 GAGAN (India) ...... 44 2.4.3.6 South Korea ...... 45 2.4.3.7 Australia ...... 46 2.4.3.8 Global SBAS Coverage ...... 47 2.5 A Multi‐GNSS Future...... 48 2.6 Conclusion ...... 51 Chapter 3 Positioning Infrastructure & GNSS Positioning Techniques ...... 53 3.1 Introduction ...... 54 3.1.1 Research Rationale ...... 54

3.2 Positioning Infrastructure ...... 55 3.2.1 Ground Infrastructure ...... 57 3.2.1.1 Continuously Operating Reference Stations ...... 57 3.2.1.2 Tiered Infrastructure ...... 58 3.2.2 Non‐GNSS Positioning Infrastructure ...... 60 3.3 GNSS Measurements and Error Sources ...... 61 3.3.1 Code and Carrier Phase Measurements ...... 62 3.3.2 Satellite Orbit Errors...... 64 3.3.3 Satellite and Receiver Clock Errors ...... 64 3.3.4 Ionospheric Error ...... 65 3.3.5 Tropospheric Error ...... 66 3.3.6 Multipath ...... 67 3.3.7 Other Biases ...... 68 3.3.8 User Equivalent Range Error ...... 69 3.4 GNSS Positioning Techniques ...... 70 3.4.1 Single Point Positioning ...... 70 3.4.2 Relative Positioning ...... 71 3.4.2.1 Differential GNSS ...... 71 3.4.2.2 Real‐Time Kinematic (RTK) ...... 72 3.4.2.3 Network Real‐Time Kinematic (NRTK) ...... 72 3.4.3 Precise Point Positioning ...... 74 3.4.3.1 Real‐Time PPP ...... 75 3.4.4 Data Formats ...... 76 3.5 The Geospatial Reference System (GRS) ...... 78 3.5.1 Position Accuracy ...... 79 3.5.2 Australia’s NGRS ...... 80 3.5.2.1 Coordinate Traceability ...... 81 3.5.2.2 Relative versus Absolute Accuracy ...... 82 3.5.2.3 Global and Regional Reference Frames ...... 82 3.5.2.4 A Modernised Datum for Australia ...... 85 3.5.2.5 Asia‐Pacific Reference Frame (APREF)...... 85 3.6 Conclusion ...... 86 Chapter 4 Evolution of Australia’s CORS Infrastructure & Positioning Services ...... 87 4.1 Introduction ...... 88 4.1.1 Research Rationale ...... 88 4.2 Government & Industry CORS Infrastructure ...... 89 4.2.1 Government Infrastructure & Service Providers ...... 89 4.2.1.1 Institutional Roles & Responsibilities ...... 90 4.2.1.2 Federal Infrastructure (ARGN & AuScope) ...... 92 4.2.1.3 State and Territory Infrastructure ...... 94 4.2.2 Positioning Services ...... 98 4.2.2.1 Service Providers ...... 98 4.2.2.2 Data Service Providers ...... 99 4.2.2.3 Value Added Resellers ...... 99 4.2.2.4 Data Custodians ...... 101 4.2.2.5 Service Level Management ...... 103 4.2.3 Competitive Neutrality ...... 104 4.2.4 Industry Infrastructure & Service Providers ...... 104 4.2.5 Wholesale and Retail Distribution ...... 108 4.2.5.1 National Broadband Network ...... 108 4.2.5.2 High Accuracy Positioning Services ...... 109 4.3 Mapping CORS Infrastructure & High Accuracy Service Coverage ...... 111 4.3.1 National GNSS CORS Infrastructure (NGCI) Web Map ...... 111 4.3.1.1 NGCI Database ...... 112 4.3.2 High Accuracy GNSS Service Coverage ...... 113 4.3.2.1 Data Licensing Arrangements ...... 116 4.3.2.2 Data Licensing ‐ Royalties ...... 117 4.3.2.3 Pseudo‐National Positioning Services ...... 117 4.3.2.4 Government versus Industry Coverage ...... 118 4.3.3 Case Study 1 – Network Expansion ...... 120 4.4 International Comparisons ...... 123

4.4.1 Great Britain ...... 123 4.4.2 Germany...... 124 4.4.3 United States ...... 126 4.4.3.1 Scientific Drivers ...... 127 4.4.3.2 State Networks ...... 129 4.4.4 Canada ...... 131 4.4.5 Data Licensing – An International Trend ...... 132 4.4.6 Global Services Providers ...... 133 4.4.6.1 Industry Service Providers ...... 133 4.4.6.2 IGS Real‐Time Service ...... 135 4.4.6.3 Global versus National Positioning Infrastructures ...... 136 4.4.7 Global Collaboration ...... 136 4.5 Conclusion ...... 137 Chapter 5 The NPI Concept ...... 139 5.1 Introduction ...... 140 5.1.1 Research Rationale ...... 140 5.2 Building Consensus ...... 141 5.2.1 ANZLIC NPI Policy ...... 141 5.2.2 Australian Strategic Plan for GNSS ...... 141 5.2.3 Australia’s NPI Plan ...... 142 5.3 NPI: A Single Point of Access ...... 143 5.3.1 Past Research ...... 143 5.3.1.1 GNSS CORS Network Management Model ...... 144 5.3.1.2 The Higgins Model ...... 146 5.3.2 NPI: A New Approach to Coordinating Access ...... 147 5.3.2.1 NPI: A Natural Evolution ...... 149 5.4 Conclusion ...... 150 Chapter 6 Accessing GNSS Positioning Services: Understanding the Economics ...... 153 6.1 Introduction ...... 154 6.1.1 Research Rationale ...... 154 6.1.2 Economic theory ...... 155 6.1.2.1 Background ...... 155 6.1.2.2 Spatial Data & Position Information ...... 156 6.2 Market Structure & Competition ...... 157 6.2.1 Information Goods ...... 157 6.2.1.1 Opportunity Cost ...... 158 6.2.1.2 Utility ...... 159 6.2.1.3 Cost Structure ...... 159 6.2.2 Market Structure ...... 161 6.2.2.1 Natural Monopolies & Economies of Scale ...... 162 6.2.2.2 Pricing Information Goods ...... 163 6.2.3 Producing High Accuracy Positioning Services ...... 165 6.2.3.1 Data Licensing & Market Competition ...... 165 6.2.3.2 Performance Standards ...... 167 6.2.3.3 Case Study 2 – Pricing Government & Industry Positioning Services ...... 168 6.2.3.4 Oligopolistic Competition ...... 171 6.2.4 Network Effects ...... 173 6.2.4.1 Data Standards: Open versus Controlled Access ...... 175 6.2.4.2 IGS Data Standards: Implications for Australia’s NPI ...... 178 6.3 Supply and Demand for Positioning Services in Australia ...... 179 6.3.1 Demand ...... 179 6.3.1.1 Background Theory ...... 179 6.3.1.2 Quantifying Demand ...... 181 6.3.1.3 Horizontal & Vertical Differentiation...... 182 6.3.1.4 Price versus Accuracy ...... 184 6.3.1.5 Estimating Demand for High accuracy Subscriptions in Australia ...... 186 6.3.1.6 Identifying Current & Future Demand in the GNSS Market ...... 189 6.3.2 Supply...... 191 6.3.2.1 Externalities & the Cost‐Benefit Relationship ...... 192 6.3.2.2 Duplication, Over‐Investment & Market Failure ...... 195 6.3.2.3 Locating Costs and Benefits in Australia ...... 196

xii

6.3.2.4 Marginal Utility ...... 201 6.3.3 NPI: Maximising Benefits at Minimum Cost ...... 203 6.3.3.1 The Value of RT‐PPP to Australia ...... 207 6.4 Public Policy ...... 210 6.4.1 Rules and Regulations ...... 210 6.4.1.1 Telecommunications ...... 210 6.4.1.2 Electricity ...... 211 6.4.1.3 Positioning Services ...... 211 6.4.2 The Role of Government ...... 212 6.4.2.1 Addressing Market Failure ...... 212 6.4.2.2 Commercial Drivers ...... 214 6.4.3 Public Goods ...... 215 6.4.3.1 Background ...... 215 6.4.3.2 Positioning Infrastructure & Services: A Public Resource? ...... 216 6.5 Conclusion ...... 217 Chapter 7 NPI Planning Framework: Technical, Institutional & Economic Criteria for Coordinating Access to Australia’s GNSS CORS Infrastructure ...... 221 7.1 Introduction ...... 222 7.1.1 Research Rationale ...... 222 7.2 NPI: A Conceptual Framework ...... 223 7.2.1 Introduction ...... 223 7.3 NPI Planning Framework ...... 226 7.3.1 Policy ...... 228 7.3.1.1 Institutional Criteria ...... 228 7.3.1.2 Technical Criteria ...... 230 7.3.1.3 Economic Criteria ...... 231 7.3.2 Investment ...... 232 7.3.2.1 Institutional Criteria ...... 233 7.3.2.2 Technical Criteria ...... 234 7.3.2.3 Economic Criteria ...... 235 7.3.3 Infrastructure & Services ...... 236 7.3.3.1 Institutional Criteria ...... 236 7.3.3.2 Technical Criteria ...... 237 7.3.3.3 Economic Criteria ...... 238 7.3.4 Access ...... 239 7.3.4.1 Institutional Criteria ...... 239 7.3.4.2 Technical Criteria ...... 241 7.3.4.3 Economic Criteria ...... 242 7.4 Conclusion ...... 243 Chapter 8 Thesis Conclusion ...... 245 Legislation ...... 249 References ...... 249 Appendix A – Geodetic Datums & Coordinate Systems ...... 263 Appendix B – Measurement Criteria for NRTK Coverage in Australia ...... 267 Appendix C – Global & Regional CORS Networks ...... 269

xiii

LIST OF FIGURES

Figure 1: Research Hypothesis...... 6 Figure 2: Chapter 1 Rationale ...... 6 Figure 3: Thesis Rationale ...... 12 Figure 4: Chapter 2 Rationale ...... 16 Figure 5: International Public Spending on Space Activities ...... 18 Figure 6: National Executive Committee for Space‐Based PNT ...... 19 Figure 7: Australian Governance for Space Activities ...... 24 Figure 8: Doppler Effect ...... 26 Figure 9: GPS Signal‐In‐Space Performance ...... 29 Figure 10: QZSS Satellite Footprint ...... 37 Figure 11: WAAS Ground Infrastructure ...... 41 Figure 12: EGNOS Sytem Architecture ...... 42 Figure 13: EDAS System Architecture ...... 42 Figure 14: MSAS System Architecture ...... 43 Figure 15: SDCM Reference Stations ...... 44 Figure 16: GAGAN Reference Stations ...... 45 Figure 17: Current Global SBAS Coverage ...... 47 Figure 18: Projected Global SBAS Coverage ...... 48 Figure 19: Projected Multi‐GNSS Satellite Coverage ...... 49 Figure 20: Chapter 3 Rationale ...... 54 Figure 21: Positioning Infrastructure Components ...... 56 Figure 22: GNSS Error Sources ...... 62 Figure 23: NRTK Concept ...... 73 Figure 24: AFN & ANN Stations ...... 81 Figure 25: Service‐Side & User‐Side Reference Frame Transformations ...... 84 Figure 26: Chapter 4 Rationale ...... 89 Figure 27: Australian States & Territories ...... 90 Figure 28: AMSA CORS Network ...... 93 Figure 29: GPSnet Victoria ...... 94 Figure 30: CORSnet NSW ...... 95 Figure 31: SunPOZ QLD and Proposed Ergon Energy Network ...... 96 Figure 32: State & Territory CORS ...... 98 Figure 33: CORS Licensing & Distribution Arrangements ...... 101 Figure 34: Data Custodian Arrangements ...... 103 Figure 35: Industry CORS ...... 107 Figure 36: Government & Industry CORS ...... 107 Figure 37: Wholesale & Retail Distribution ...... 110 Figure 38: National GNSS CORS Infrastructure (NGCI) Web Map ...... 112 Figure 39A and 39B: NGCI Metadata ...... 113 Figure 40: Australian NRTK Coverage ...... 114 Figure 41: Pseudo‐National Positioning Services ...... 118 Figure 42: CORS – Great Britain ...... 124 Figure 43: CORS ‐ Germany ...... 125 Figure 44: Fee Structure – SAPOS Germany ...... 125 Figure 45: US National CORS Network ...... 126 Figure 46: US PBO CORS Network ...... 128 Figures 47A and 47B: Japanese & European CORS ...... 128 Figure 48: CORS ‐ Washington ...... 129 Figure 49: SmartNet North America ...... 130 Figure 50: SmartNet North America Affiliate Networks ...... 130 Figure 51: US Trimble VRS Now Service ...... 131 Figures 52A and 52B: CORS ‐ Canada ...... 132

xiv

Figure 53: Chapter 5 Rationale ...... 140 Figure 54: GNSS CORS Network Management Model ...... 145 Figure 55: Higgins Model ...... 146 Figure 56: Conceptual NPI Model ...... 148 Figure 57: Chapter 6 Rationale ...... 155 Figure 58: Average Total Cost Curve ...... 162 Figure 59A and 59B: Government & Industry ATC Curves ...... 169 Figure 60: S‐Curve Adoption Paths ...... 174 Figure 61: Open & Controlled Access ...... 177 Figures 62A and 62B: Demand Curves ...... 180 Figure 63A and 63B: Selective Availability & Market Demand for GPS ...... 184 Figure 64: Australian Population Density & NRTK Coverage ...... 197 Figure 65: Australian Wheat Growing Regions & NRTK Coverage ...... 198 Figure 66: Australian Remoteness Index & NRTK Coverage ...... 199 Figure 67: Australian Transport Networks & NRTK Coverage ...... 200 Figure 68: Conceptual NPI ATC Curve ...... 203 Figure 69A and 69B: ATC & Demand for a NPI ...... 204 Figure 70: Chapter 7 Rationale ...... 222 Figure 71: Conceptual NPI Planning Framework ...... 223 Figure 72: NPI Planning Framework & Higgins model ...... 225 Figure 73: Ellipsoid ...... 263 Figure 74: Reference Ellipsoid & Geoid ...... 266

LIST OF TABLES

Table 1: NPI Planning Framework Recommendations ...... 13 Table 2: GPS Applications ...... 31 Table 3: GNSS Constellation Parameters ...... 36 Table 4: International GPS Agreements & Collaborations ...... 50 Table 5: CORS Infrastructure Components ...... 58 Table 6: GNSS & Non‐GNSS Specific Biases ...... 68 Table 7: UERE Components ...... 69 Table 8: State & Territory CORS ...... 97 Table 9: Government & Industry NRTK Coverage ...... 115 Table 10: State & Territory NRTK Coverage ...... 119 Table 11: NPI Planning Framework Recommendations...... 227 Table 12: Policy – Institutional Findings & Recommendations ...... 228 Table 13: Policy – Technical Findings & Recommendations ...... 230 Table 14: Policy – Economic Findings & Recommendations ...... 231 Table 15: Investment – Institutional Findings & Recommendations ...... 233 Table 16: Investment – Technical Findings & Recommendations ...... 234 Table 17: Investment – Economic Findings & Recommendations ...... 235 Table 18: Infrastructure & Services – Instituional Findings & Recommendations ...... 236 Table 19: Infrastructure & Services – Technical Findings & Recommendations ...... 237 Table 20: Infrastructure & Services – Economic Findings & Recommendations ...... 238 Table 21: Access – Instituional Findings & Recommendations ...... 239 Table 22: Access – Technical Findings & Recommendations ...... 241 Table 23: Access – Economic Findings & Recommendations ...... 242 Table 24: Albers equal area conic map projection parameters ...... 267 Table 25: Published and computed area comparison ...... 267 Table 26: Global & Regional CORS ...... 269

LIST OF ACRONYMS

2SOPS 2nd Space Operations Squadron CRCSI Cooperative Research Centre for Spatial Information 3D Three‐Dimensional CS Commercial Service AAI Airports Authority of India DALA Distribution Access Licence AATS Australian Academy of Agreement Technological Sciences DC Data Centre AC Analysis Centre DDRO Defense Research and Development ACT Australian Capital Territory Organisation ADSL Asymmetric Digital Subscriber Line DEPI Department of Environment and AFN Australian Fiducial Network Primary Industries AGD Australian Geodetic Datum DGNSS Differential GNSS AGOS Australian Geophysical Observing DOI Department of Industry System DLP Department of Lands and Planning AMSA Australian Maritime Safety DNRM Department of Natural Resources Authority and Mines ANN Australian National Network DNSS Defense Navigation Satellite System ANZLIC The Spatial Information Council DoD Department of Defence APV Approach with Vertical guidance DOP Dilution of Precision ARGN Australian Regional GNSS Network DORIS Doppler Orbitography and Radio ARNS Aeronautical Radio Navigation Positioning Integrated by Satellite Service DPIPWE Department of Primary Industries, ASBC Advanced Space Business Parks, Water & Environment Corporation DPTI Department of Planning, Transport ASC Australian Spatial Consortium and Infrastructure ASCII American Standard Code for DSP Data Service Provider Information Interchange EDAS EGNOS Data Service ASRP Australian Space Science Program EGNOS European Geostationary Navigation BoM Bureau of Meteorology Overlay Service C/A Course Acquisition eLORAN Enhanced LORAN CASA Civil Aviation Safety Authority EOS Earth Observations from Space CBA Cost‐Benefit Analysis ESA European Space Agency CDMA Code Division Multiple Access EU European Union CNSA China National Space Administration EULA End User Licence Agreement CONUS Contiguous US FAA Federal Aviation Authority CORS Continuously Operating Reference FDMA Frequency Division Multiple Access Station FKP Flächenkorrekturparameter

xvi

FOC Full Operational Capability INRES Indian Reference Station GA Geoscience Australia IOC Initial Operation Capability GAGAN GPS Aided Geo Augmentation IOV In‐Orbit Validation Navigation IP Internet Protocol GBAS Ground Based Augmentation IPS Ionospheric Predication Service System IPW Integrated Precipitable Water GCC Ground Control Centre Vapour GDA Geocentric Datum of Australia IRNSS Indian Regional Navigation Satellite GDOP Geometric Dilution of Precision System GES Ground Earth Station ISM Industrial, Scientific and Medical GGOS Global Geodetic Observing System ISP Internet Service Provider GGTO Galileo to GPS Offset ISRO Indian Space Research Organisation GJU Galileo Joint Undertaking ITRF International Terrestrial Reference Frame GLONASS Global’naya Navigatsionnaya Sputnikovaya Sistema IWG Interoperability Working Group GNSS Global Navigation Satellite System KPI Key Performance Indicator GPS Global Positioning System LBS Location Based Service GRF Global Reference Frame LEO Low Earth Orbit GRS Geospatial Reference System LEX L‐Band Experimental GSA European GNSS Agency LINZ Land and Information New Zealand GSS Galileo Sensor Station LLR Lunar Laser Ranging GST Galileo System Time LORAN Long Range Navigation HAL Horizontal Alert Limit LPI Land and Property Information HDOP Horizontal Dilution of Precision LPV Localiser Performance with Vertical guidance HEO Highly Elliptical Orbit MAC Master Auxiliary Concept HR Human Resources MCS Master Control Station ICG International Committee on GNSS MEO Medium Earth Orbit ICSM Intergovernmental Committee on Surveying and Mapping MEOSAR Medium Earth Orbit Search and Rescue ICT Information and Communication Technology MFF Multi‐annual Financial Framework IDC Interdepartmental Committee MGEX Multi‐GNSS Experiment IGS International GNSS Service MIT Massachusetts Institute of Technology IGSO Inclined Geosynchronous Orbit NNRMS National Natural Resources IGS‐RTS IGS Real‐Time Service Management System ILS Instrument Landing System MRS Monitor and Ranging Stations INMCC Indian Master Control Station MSAS MTSAT Satellite Augmentation System

xvii

MSM Multiple Signal Message RIMS Receiver Integrity Monitoring Stations NAVSEG Navigation Satellite Executive Group RINEX Receiver Independent Exchange NBN National Broadband Network RMS Root Mean Square NCRIS National Collaborative Research Infrastructure Strategy RNSS Radionavigation Satellite Service NGCI National GNSS CORS Infrastructure RRF Regional Reference Frame NGRS National Geospatial Reference RTCA Radio Technical Commission for System Aeronautics NGS National Geodetic Survey RTCM Radio Technical Commission for Maritime Services NLES Navigation Land Earth Stations RTK Real‐Time Kinematic NMS Network Management System RT‐PPP Real‐Time PPP NPI National Positioning Infrastructure SA South Australia NRTK Network Real‐Time Kinematic SAIF Submeter‐class Augmentation with NSW New South Wales Integrity Function NT Northern Territory SAR Search and Rescue NTRIP Network Transfer of RTCM via SARPS Standards and Recommended Internet Protocol Practices NTSC National Time Service Center SBAS Space‐Based Augmentation System (China) SCO Space Coordination Office NWP Numerical Weather Prediction SDCM System for Differential Correction OCS Operational Control Segment and Monitoring OCX Operational Control System SECOR Sequential Correlation of Range OS Open Service SESAR Single European Sky Air Traffic OSR Observation Space Representation Management Research PCG Permanent Committee on Geodesy SIS Signal‐In‐Space PDU Power Distribution Unit SLA Service Level Agreement PLA Planning and Land Authority SLM Service Level Management PNT Position, Navigation and Timing SoL Safety‐of‐Life PPP Precise Point Positioning SoP Signals of Opportunity PPP‐RTK PPP Real‐Time Kinematic SP Service Provider PPS Precise Positioning Service SPP Single Point Positioning PRN Pseudorandom Noise SPS Standard Positioning Service PRS Public Regulated Service SPU Space Policy Unit QLD Queensland SSR State Space Representation QZSS Quasi‐Zenith Satellite System SV Satellite Vehicle RA Responsible Authority TAI International Atomic Time

xviii

TAS Tasmania VLBI Very Long Baseline Interferometery UERE User Equivalent Range Error VNAV Vertical Navigation UHF Ultra‐High Frequency VRS Virtual Reference Station UK United Kingdom VSAT Very Small Aperture Terminal UN United Nations VSC Victorian Spatial Council UNOOSA United Nations Office for Outer WA Western Australia Space Affairs WAAS Wide Area Augmentation System UPS Universal Power Supply WAD Wide‐Area Differential URE User Range Error WAM Wide‐Area Master UTC Coordinated Universal Time WRS Wide‐Area Reference Station VAL Vertical Alert Limit WVR Water Vapour Radiometer VAR Value Added Reseller ZTD Zenith Tropospheric Delay VIC Victoria

xix

CHAPTER 1 INTRODUCTION

INTRODUCTION

Every natural and man‐made feature has a definable three‐dimensional position on or near the Earth. Accurate and reliable position information supports a plethora of activities, including evidence‐based decision‐making. Economic and social value is created by producing, distributing and maintaining consistent and standardised position information.

Over the past two decades, Global Navigation Satellite Systems (GNSS) have become a dependable and frequently used source of Position, Navigation and Timing (PNT) information. GNSS have been augmented with ground and space‐based infrastructures to enhance the accuracy, availability, reliability and overall integrity of PNT information. Increased user demand for reliable and cost‐effective PNT solutions has stimulated development of innovative technologies and value‐added services.

Continuously Operating Reference Station (CORS) networks are a common form of ground‐based augmentation that governments and industry use to distribute centimetre (cm) accurate PNT information in real‐time across a region. Networks of CORS have been deployed locally, nationally, regionally and globally in response to scientific and commercial demand from multiple industries including mining, construction, agriculture, engineering, surveying, transport, meteorology, emergency management, Location Based Services (LBS) and defence (GSA, 2013, Hausler and Collier, 2013a). Collaboration between governments and industry in the United Kingdom (UK), Ireland, Germany, Sweden, Japan, Turkey and New Zealand has enabled national positioning services that support civil, scientific and commercial functions. Industry service providers often license access to data from government‐owned CORS to offer competitive value‐added positioning services that are linked to a uniform national positioning infrastructure. Industry providers deploy additional CORS in high demand regions and sell access to their services directly or through Value‐Added Reseller (VAR) arrangements.

In Australia however, there is no uniform national positioning service that offers access to high accuracy position information anytime and anywhere across the country. Investment has been prioritised where demand from construction, agriculture and mining industries is higher, which has resulted in the ad‐hoc deployment of independently owned and operated positioning services (The Allen Consulting Group, 2008). It follows that the costs and benefits to government and industry of deploying CORS networks are not evenly distributed across Australia. In regions of higher demand, recent studies (Hale, 2007, Higgins, 2008, ANZLIC, 2010, ASC, 2012, Australian Government, 2013a, Hausler and Collier, 2013a) indicate that ad‐hoc deployment has led to duplication, over‐investment, constraints on user access, non‐uniform service standards and limited quality control.

This thesis presents technical, institutional and economic evidence that further explores these findings and demonstrates that in regions where coverage is available, no government or industry service provider delivers a single point of access to the full service coverage region.

The technical benefits to society of creating a single point of access to positioning infrastructure through a National Positioning Infrastructure (NPI) are subsequently examined by reviewing user demand for

2 consistent and standardised (e.g., data formats, accuracy, availability) position information in Australia. Institutional and economic benefits resulting from greater coordination between governments and industry are also examined in the context of funding, operating, managing and regulating a NPI; with a goal to minimise investment costs and guarantee a minimum level of service that is legally traceable.

To achieve these benefits, emphasis is placed on evaluating the influence that average station spacing between CORS has on cost‐benefit decisions for deploying additional CORS infrastructure. Station spacing affects the type of GNSS processing methodology that is adopted, which in‐turn influences the level of accuracy, latency and availability of position solutions, and thus the overall investment required. To broaden service coverage, demand from governments and industry must outweigh the capital and operational costs of deploying, extending or densifying a CORS network. Compounding these investment decisions is Australia’s variable population density which has, in large part, influenced the location of previous investment given high accuracy positioning coverage tends to be correlated with higher population densities along jurisdictional coastlines. Identifying the quantity, location and type of CORS infrastructure that has been deployed (i.e., supplied) across Australia provides insight on where market demand for high accuracy positioning information is strongest.

Current approaches to managing CORS infrastructure and positioning services independently have created technical, institutional and economic challenges that are addressed within this thesis. These challenges are briefly described below.

Technical challenges relate to the level of interoperability and compatibility between independent positioning services, which reflects the types of network processing methodologies, user equipment, data latency, data standards and station densities that are used. Interoperability is a key consideration as society enters a world with multiple‐GNSS (multi‐GNSS). The widely used Global Positioning System (GPS) has been or will soon be joined by comparable systems from Russia (GLONASS1), Europe (Galileo) and China (Beidou), along with Regional Navigation Satellite Systems (RNSS) from Japan (QZSS2) and India (IRNSS3). Australia stands to benefit greatly from its geographic location where visibility to all satellites will be higher than most other places in the developed world (see Figure 19 in Chapter 2). Australia’s CORS infrastructure should therefore be interoperable and compatible with all existing and emerging systems to ensure the nation remains competitive as an early adopter and pioneer of multi‐ GNSS enabled products and services (ASC, 2012).

Institutional challenges arise from a lack of national policy for developing, coordinating and enforcing roles and responsibilities for funding and standardising positioning services (e.g., data formats, service performance and access). Unregulated and independent management of CORS infrastructure has limited data sharing (e.g., in the absence of a single point of access), which leads to duplication of

1 Global’naya Navigatsionnaya Sputnikovaya Sistema. 2 Quasi‐Zenith Satellite System. 3 Indian Regional Navigation Satellite System.

3 infrastructure and limits access to new user markets (e.g., for users that demand national positioning coverage) within and outside of existing coverage regions. International engagement through a single point of contact within the Australian Government is therefore critical for maintaining access to new satellite systems (Australian Government, 2013a) and the positioning services that depend on these systems.

Economic inefficiencies result from over‐investment in some regions, and a lack of productivity where little or no investment in positioning infrastructure has been made in other regions. Geographic regions that could benefit from high accuracy positioning coverage are identified in this thesis. Coverage regions that are dominated by an individual Service Provider (SP) are also found to limit competition and can ‘lock’ users to vendor‐specific equipment. Whilst individual providers can build economies of scale that broaden coverage and improve price competition, the full benefits may not be passed onto users if access is contingent upon proprietary data standards and equipment, thus limiting the potential value that can be generated from a broader network of users. Open standards can enable greater compatibility and interoperability, which facilitates innovation and competition by broadening the network of technology and services that users connect to through their positioning devices.

It follows that the market structure for producing and distributing high accuracy position information has not been clearly defined in an economic context for Australia. The roles of government and industry are continuing to evolve, and public policy, supported by rigorous Cost‐Benefit Analysis (CBA), must accommodate these changes to encourage and optimise future investment in CORS infrastructure by the public and private sectors.

Collectively, these challenges limit access to high accuracy PNT information nationally, which in turn limits the utility, and therefore the value that CORS infrastructure and associated positioning services contribute to the Australian economy. To address these limitations, the NPI Planning Framework has been developed as a unique output of this research. The Framework identifies a complex matrix of inter‐ linked criteria that must be satisfied to achieve greater technical, institutional and economic coordination of Australia’s CORS infrastructure.

1.1 PROBLEM STATEMENT

GNSS CORS infrastructure is currently deployed and operated independently by public and private SPs within Australia. Independent and ad‐hoc management has led to duplicated infrastructure and overinvestment, inconsistent data and service standards, limited measures of quality control, sub‐ optimal service coverage, geographic and commercial constraints on user access, limited competition, and limited oversight on the institutional roles and responsibilities of governments and industry towards infrastructure ownership, maintenance, expansion, service management and delivery.

Limited research has been undertaken to articulate and demonstrate how these technical, institutional and economic challenges collectively limit the utility of real‐time, high accuracy positioning services across Australia.

To address these challenges, this thesis builds on early policy work by State and Territory institutions within the spatial community, and more recently by the Australian Government, which has opened communication with industry and the research community to build political, commercial and technical support for developing a NPI.

A unique economic context has been developed to describe the relationship between key GNSS positioning technologies, institutional roles and responsibilities, and methods for evaluating costs and benefits to guide planning and development of a NPI. These findings are summarised within the NPI Planning Framework to inform policy, and future modelling of the economic investment and technical criteria needed to coordinate and maximise social and economic benefits that are enabled by high accuracy CORS network positioning services in Australia.

1.2 RESEARCH HYPOTHESIS

The hypothesis examined within this research states that:

A National Positioning Infrastructure will enable greater access to GNSS CORS infrastructure across Australia.

Access in this context refers to enhanced utility to users, and a positive impact on productivity, innovation and the Australian economy. Figure 1 therefore illustrates the key research themes used to address this hypothesis by first identifying that criteria for accessing CORS infrastructure, and the position information derived from this infrastructure, are influenced by a combination of technical, institutional and economic factors. The NPI is introduced as a mechanism for addressing the relationship between these factors, to coordinate the development and utility of existing and future CORS infrastructure by establishing a single point of access.

A unique economic context is developed to communicate why greater coordination of CORS through the NPI will continually increase the value generated by these CORS compared with independent management approaches. Criteria and recommendations for achieving greater coordination are summarised within the NPI Planning Framework.

FIGURE 1: RESEARCH HYPOTHESIS

Increased Value

A National Positioning Infrastructure will enable greater access to GNSS CORS infrastructure across Australia

Technical Institutional Economic

Coordination

A NPI will address technical, intuitional and economic factors for coordinating access to CORS infrastructure to increase value to the Australian economy.

1.3 RESEARCH RATIONALE

Figure 2 maps the relationship between technical, institutional and economic themes explored within this thesis. Figure 2 illustrates why a unique economic interpretation and analysis of the supply chain and value chain for high accuracy positioning services in Australia is needed to describe the relationship between institutional (e.g., policy and funding) and technical (e.g., ground and space‐based infrastructure) criteria for establishing a NPI. This economic context will demonstrate that greater coordination at each stage of the supply chain and value chain will improve access to positioning services, thereby increasing the economic and social value generated by these services.

FIGURE 2: CHAPTER 1 RATIONALE

The need to identify, relate and communicate the relationship between technical, institutional and economic criteria for establishing a NPI provides the rationale for undertaking this research (Gov: Government).

Two principles (identified in Figure 2) guide this rationale and are examined throughout this thesis in an economic context:

1. Governments have a role in funding public infrastructure (i.e., as a public good4).

2. Space and ground‐based positioning infrastructure facilitates commercial enterprise for developing GNSS products and services that improve productivity and open new markets for government and business services.

Both principles recognise that GNSS positioning services deliver broader and less direct benefits beyond the direct benefits secured by everyday users (e.g., surveyors and engineers). These indirect benefits are termed ‘externalities’ in the economic literature (see Chapter 6). At the institutional level, governments typically seek to maximise direct and indirect benefits through strategic policy and investment in space and ground infrastructure.

For example, the geodetic framework, commonly known as the Geospatial Reference System (GRS), is a public good that enables direct (e.g., financial) and indirect (e.g., public safety) benefits in Australia. GNSS positioning infrastructure is a key input for managing the GRS to deliver government and business services. Public policy and funding supports the establishment and maintenance of the GRS as a public good, meaning anyone can freely access (i.e., non‐excludability) and use the GRS without reducing its availability (i.e., non‐rivalry).

The research is guided by these two principles in order to identify, relate and spatially analyse technical and institutional criteria for developing a NPI. Hence, these principles provide a common benchmark for evaluating the extent to which the NPI will improve access to GNSS ground infrastructure in Australia, as per the research hypothesis.

1.4 SIGNIFICANCE OF THE RESEARCH

The Australian Government National Positioning Infrastructure Plan (NPI Plan) is introduced below to outline the significance and scope of this research.

1.4.1 NATIONAL POSITIONING INFRASTRUCTURE PLAN

In 2010, the Australian Government assigned the Space Policy Unit (SPU) within the Department of Industry (DoI5) a mandate to bring forward a space policy for Australia (Space Policy Unit, 2012).

4 In economics, public goods are non‐rivalrous meaning one individual can consume the good without reducing its availability for another individual, and are non‐excludable meaning no individual can be excluded from using the good. 5 Formerly the Department of Industry, Innovation, Climate Change, Science, Research and Tertiary Education (DIICCSRTE).

Australia’s Satellite Utilisation Policy was subsequently released on 9th April 2013 by Senator Kate Lundy, Minister Assisting for Industry and Innovation.

Principle one of the Policy identifies the need for Australia to focus on space applications of national significance, including the development of a National Positioning Infrastructure Plan to examine investment in the domestic ground infrastructure needed to deliver accurate and reliable positioning information to users (Australian Government, 2013). Geoscience Australia (GA) within the DoI6 is leading the development of the NPI Plan to identify Australia’s future PNT capabilities and requirements.

The author of this thesis was the lead author of the draft NPI Plan and was seconded to GA for five months in 2012 to assist consultations with Federal, State and Territory governments, industry service providers, and academic stakeholders. The Intellectual Property presented within this thesis and acquired during this period of secondment has been certified by GA for public release.

1.4.2 THESIS SCOPE

The scope of this thesis is limited to the GNSS CORS component of a NPI, although non‐GNSS positioning systems are briefly introduced in Chapter 3 to demonstrate the scalability of the NPI concept. Focussing primarily on GNSS resources in the short‐term supports the objectives set out in Australia’s Satellite Utilisation Policy and more specifically the emphasis given in two key publications identified below. Both publications recognise GNSS services and CORS infrastructure as enabling technologies for the NPI, and have therefore influenced the research direction:

1. The ‘NPI Policy’ (2010) developed by ANZLIC – the spatial information council, the purpose of which was:

“... to outline a set of principles for the provision of a national positioning infrastructure (NPI) that will ensure sustainable, nationally compatible deployment of GNSS Continuously Operating Reference Stations (CORS) infrastructure capable of accommodating a variety of providers and ensuring an efficient and effective Australia wide coverage and service for the positioning needs of a diverse user community.” (ANZLIC, 2010)

2. The NPI Plan (2012) being developed by GA for consideration by the DoI:

“... to review Australia’s positioning infrastructure, considering the benefits that could be derived from a national rollout of a standardised network, and the assumption that this

6 GA formally reported to the Department of Resources, Energy and Tourism (DRET) whose functions were transferred to the DoI due to machinery of government changes in 2013.

would enhance innovation and speed up adoption rates; and allow for uniformed standards, quality levels and pricing of and access to the network.” (Geoscience Australia, 2012)

Both documents identify technical, institutional and economic considerations that must be addressed to improve access to GNSS infrastructure and information, which provides the justification for undertaking this research. The content and implications of both documents are explored throughout this thesis.

1.5 RESEARCH AIMS & TASKS

The theoretical concepts applied within this research span multiple disciplines including geodesy; spatial information analysis; Information and Communications Technologies (ICT); public policy; microeconomics and macroeconomics. These concepts are defined, tested and linked by developing the NPI Planning Framework, and two case studies are used to demonstrate key spatial and economic concepts.

In light of this multi‐disciplinary approach, the aims of this research are threefold:

1. Compile spatial evidence on the location of existing CORS infrastructure owned by governments and industry in Australia to determine where duplication and over‐investment has occurred, and where future investment should be prioritised.

2. Using this spatial evidence, develop a unique economic context examining the technical, institutional and economic challenges and benefits of establishing a NPI that enables greater access to existing and future CORS infrastructure.

3. Develop a NPI Planning Framework that identifies, relates and communicates technical, institutional and economic criteria, and provides recommendations for coordinating a single point of access to CORS infrastructure in Australia.

Key tasks for achieving these aims are:

To review:

• GNSS theory, including developments in satellite systems and ground infrastructure as well as current and future methods of real‐time satellite‐based positioning.

• The physical locations and metadata for GNSS CORS infrastructure owned by governments and industry across Australia.

• Microeconomic theories and principles of public policy that influence the market structure for producing, distributing and standardising high accuracy position information.

• Australian and international models for managing CORS infrastructure and services.

To develop:

• An interactive online web map to visualise and communicate infrastructure locations and positional coverage.

• A unique economic and spatial context for determining the technical, institutional and economic costs and benefits that a single network positioning solution would deliver to the Australian economy through a NPI, and a way of prioritising its roll‐out.

• A NPI Planning Framework for identifying and relating key technologies, governance mechanisms and economic drivers for implementing a NPI.

To provide recommendations on:

• Technical, institutional and economic criteria for coordinating the deployment and management of CORS infrastructure within Australia to maximise the utility of high accuracy positioning services through a NPI.

1.6 THESIS OUTLINE

Key content addressed within each Chapter is outlined below:

• Chapter 2 reviews the current and future role of foreign space policies for developing space and ground‐based PNT systems. GNSS/RNSS technologies and their development programs are subsequently discussed as a basis for evaluating how Australia can leverage maximum benefit from multi‐GNSS systems.

• Chapter 3 reviews satellite positioning theory and processing techniques, and associated ground‐based infrastructures that support the acquisition and delivery of high accuracy PNT information. For completeness, the Chapter concludes with a discussion on non‐GNSS technologies as a complement and alternative to GNSS.

• Chapter 4 contributes new spatial evidence that is used to describe the evolution of CORS networks in Australia by reviewing hardware, software and technical standards underpinning the production and distribution of high resolution (accuracy) positioning services. Scientific and commercial business drivers for deploying CORS infrastructure are identified and analysed in light of multi‐GNSS developments. Past and present approaches by Australian governments and

industry towards managing CORS infrastructure and associated positioning services are reviewed and critically evaluated. Comparisons are made with international positioning networks in Great Britain, Germany, Canada and the US.

• Chapter 5 introduces the NPI concept as a technical, institutional and economic mechanism for coordinating a single point of access to existing and future CORS infrastructure in Australia. Chapter 5 reviews early planning and policy work by governments, industry and the research community which demonstrates the infancy of the NPI concept, and therefore identifies why this research contributes original evidence and analysis that will guide future implementation of a NPI.

• Chapter 6 is an original contribution that describes the economic market structure underpinning the supply of, and demand for high accuracy GNSS positioning services in Australia. Economic principles and terminology for communicating technical, institutional and commercial concepts outside of the spatial sector are established. The focus of Chapter 6 is to understand the value of Australia’s high accuracy positioning market as opposed to quantifying it. The natural monopoly characteristics of CORS infrastructure are described and evaluated with regard to Australia’s geographic constraints on user access, and associated barriers to entry for producers and users of high accuracy positioning services. The Chapter concludes with a discussion on production and distribution factors that build economies of scale for supplying GNSS data, and network externalities that will influence current and future demand.

• Chapter 7 consolidates the technical, institutional and economic criteria identified throughout this thesis by developing the NPI Planning Framework, which will influence decision‐making on the policy, infrastructure and services, and investment needed to create a single point of access through the NPI. The contribution of Chapter 7 is to provide recommendations that inform the business case for designing, funding and implementing a NPI, thereby enhancing the direct and external benefits of accessing multi‐GNSS technology in Australia. The Framework links each recommendation to the theories and evidence presented throughout Chapters 1 to 6, and Table 1 summarises these recommendations to outline the scope of this thesis.

• Chapter 8 provides a conclusion to this study.

Figure 3 maps the themes of each Chapter according to the research rationale defined in Figure 2. Note the inclusion of a ‘NPI’ element in Figure 3 compared with Figure 2, which is introduced in Chapter 5 to evaluate the need for a single point of access to ground infrastructure in Australia.

FIGURE 3: THESIS RATIONALE

The research rationale defines the relationship between each Chapter.

1.6.1 NPI PLANNING FRAMEWORK

The NPI is proposed as a new approach to coordinating, securing and improving access to Australia's PNT resources to maximise value from existing and future space and ground infrastructure. Technical, institutional and economic criteria for establishing a NPI are examined in this thesis. Table 3 summarises recommendations from the NPI Planning Framework that will strengthen the business case for investment in positioning infrastructure both nationally and internationally. The remainder of this thesis provides the theory and evidence supporting these recommendations.

TABLE 1: NPI PLANNING FRAMEWORK RECOMMENDATIONS

Policy Investment Infrastructure & Services Access

• Establish a national governance • Identify existing and new sources of • Develop procedures for certifying • Develop and enforce uniform structure with representation from public funding from Federal, State CORS infrastructure and associated licensing agreements for distributing Australian governments, industry and and Territory governments positioning services in accordance data through a single point of access research stakeholders, to set with national policy, legislation and • Investigate public‐private • Develop and enforce Service Level Institutional directions and seek government regulations partnerships Agreements (SLAs) endorsement on positioning related matters • Investigate policy, legislative and regulatory conditions for privatisation

• Endorse national infrastructure • Quantify the direct and external costs • Develop and formally document • Adopt/develop open data standards standards and benefits of establishing a NPI positioning infrastructure • Distribute data from a secure and with a single point of access specifications in accordance with • Endorse national service level highly redundant single point of national policy, standards and standards access via multiple communications legislation systems • Endorse open data standards for Technical • Define Key Performance Indicators recording and distributing GNSS data • Deliver a minimum level of service (KPIs) for measuring service level within a NPI performance accessible to all users standards • Endorse measures and • Monitor service performance and • Network and process data within a responsibilities for certifying access access requirements against KPIs secure and highly redundant ICT to NPI services platform

• Undertake rigorous Cost‐Benefit • Develop sustainable cost‐recovery • Identify and map the geographic • Implement data pricing policies that Analysis to evaluate the direct and models to ensure ongoing funding location of existing and future maximise access for public good and external value of creating a single positioning infrastructure & services commercial purposes point of access to a NPI Economic • Prioritise future investment in • Minimise the wholesale and retail • Develop a whole‐of‐government data geographic regions where public cost of accessing positioning data pricing policy good benefits and commercial demand are higher

CHAPTER 2 SPACE POLICY & SATELLITE POSITIONING

SYSTEMS

SPACE POLICY & SATELLITE POSITIONING SYSTEMS

2.1 INTRODUCTION

Space infrastructure and systems are integral to the functioning of modern society. A range of satellites have been deployed to support, amongst other things, telecommunications, image collection and other forms of remote sensing, environmental monitoring, meteorology, gravity studies and, important in the context of this thesis, a variety of civil and military PNT applications. This Chapter reviews the policies and space technologies used to establish satellite navigation systems such as GPS, which provide PNT information to users across the Earth.

2.1.1 RESEARCH RATIONALE

Institutional space policy frameworks that support funding and technical development of global and regional satellite‐based positioning systems in response to public and commercial drivers are introduced and reviewed in this Chapter. PNT services offered by all operational and planned GNSS, RNSS and SBAS are described, and the proposed benefits of a future multi‐GNSS7 environment are identified. Australia’s growing dependence on international space‐based PNT systems is emphasised by reviewing the Australian Government’s recently released Satellite Utilisation Policy. The research rationale in Figure 4 illustrates that institutional and technical themes relating space‐based infrastructure are used to justify the research focus on identifying and analysing associated ground infrastructure requirements in Australia.

FIGURE 4: CHAPTER 2 RATIONALE

Research logic for Chapter 2 which explores the relationship between foreign space policy and investment in technical GNSS/RNSS infrastructure in response to public and commercial drivers.

7 The term multi‐GNSS encompasses all GNSS and RNSS. SBAS are addressed separately.

Subsequent Chapters explore the need for greater coordination between existing Federal and State policies for managing ground networks, in cooperation with industry, to maximise public and commercial benefits for Australia’s positioning market. Improving access to the multi‐GNSS services described in this Chapter, through a coordinated single point of access to ground infrastructure, is a central theme of this thesis.

2.2 SPACE POLICY

“The utilization of space has created new markets; helped save lives by warning us of natural disasters, expediting search and rescue operations, and making recovery efforts faster and more effective; made agriculture and natural resource management more efficient and sustainable; expanded our frontiers; and provided global access to advanced medicine, weather forecasting, geospatial information, financial operations, broadband and other communications, and scores of other activities worldwide. Space systems allow people and governments around the world to see with clarity, communicate with certainty, navigate with accuracy, and operate with assurance.” (US Government, 2010)

Space policies identify diverse objectives, institutions and systems for managing and funding space infrastructure and resources. Principles and guidelines for establishing and managing satellite‐based PNT systems are addressed within space policy.

PNT users rely on a stable and consistent policy environment to secure funding and continued access to satellite‐based positioning systems (RAND Corporation, 1995). Space policies implemented by nations that own and operate GNSS and RNSS influence the policy decisions made by foreign users. For example, the Australian Government does not currently own or operate space assets in the PNT domain. However, the recent release of Australia’s first ever space policy, Australia’s Satellite Utilisation Policy (2013a) outlines the nation’s goal of ensuring on‐going, cost‐effective access to international space capabilities (driven by foreign space policy), and assigns responsibility to the Australian Government for securing access to foreign satellite positioning systems. This reliance on foreign PNT systems is not unique to Australia given GNSS programs currently led by the US, Russia, Europe and China enable benefits to global user communities. Policy and investment in RNSS (particularly across the Asia‐Pacific) and SBAS systems also influences policy at national, regional and international levels of government.

The space policies and plans discussed below have been developed primarily by nations that are currently deploying and modernising space infrastructure. A comprehensive overview of space policies, issues and trends, including annual budget figures, is available from the European Space Policy Institute (ESPI, 2012), including policies and strategies for countries listed in Figure 5, as well as those for Singapore and Iran. A comparison of the 2011 public space budgets for leading spenders has been

17 adapted from ESPI (2012) in Figure 5 and includes data collected from Euroconsult (2012) and the Space Foundation (2012).

FIGURE 5: INTERNATIONAL PUBLIC SPENDING ON SPACE ACTIVITIES

50000

45000

40000

35000

30000 $USD

25000

Millions 20000

15000

10000

5000

Public spending on space activities (in millions $US) for 2011 estimated by ESPI (2012) using data collected by Euroconsult (2012) and Space Foundation (2012).

Note in Figure 5 that total US spending comprises over US$26 billion for defence and almost US$21 billion for civil expenditure, including revenue for telecommunications, Earth observation and PNT space infrastructure, manufacturing, launch services and ground equipment. However, estimates for Russia’s military spending on space launches and scientific programmes are not included. In April 2013, Russian President Vladimir Putin announced an additional US$50 billion funding between 2013 and 2020 for the Russian space program described below.

Also absent from Figure 5 is the European Space Agency (ESA), which received a budget of US$5.8 billion in 2011 through joint investment from its 20 member States, some of which are listed above. Note that membership of the European Union (EU) and ESA is not the same given they are separate organisations, although there is significant overlap.

2.2.1 US SPACE POLICY

In recognition of the public safety, scientific, commercial and economic benefits that GPS enables, the US National Space Policy8 (2010) continues to grant free access to the global user community. The shift

8 Policy leadership in the US extends back to the National Aeronautics and Space Act of 1958.

18 from a military‐only system, to a ‘dual‐use’ arrangement, dates back to 1983, when President Reagan announced free access to civilian aircraft following the Soviet Union’s decision to shoot down Korean Air Flight 007, after the aircraft accidently intruded into Soviet airspace.

The US National Space Policy covers all activities in the space sector and draws on a separate US Space‐ Based Position, Navigation and Timing Policy enacted in 2004, which establishes guidance and implementation actions for PNT programs, augmentations and activities. It is noteworthy that PNT related matters are reported directly to the White House through the National Executive Committee for Space‐Based PNT, in recognition of the national benefit that PNT information delivers (see Figure 6). The PNT Policy centres on developing, acquiring, operating, sustaining and modernising GPS to protect access for US and global users. The open access policy serves to improve public awareness of government activities by promoting openness and transparency in space operations in accordance with international space law9. These objectives are strengthened through bilateral agreements, such as those established with Australia, which promote skills and knowledge development to encourage global trade and support monitoring and management of the space environment (GPS.gov, 2010).

FIGURE 6: NATIONAL EXECUTIVE COMMITTEE FOR SPACE‐BASED PNT

Organisational structure for the joint civil/military US National Executive Committee for Space‐Based Positioning, Navigation, and Timing (GPS.gov, 2012).

Related studies on policy cooperation between the US and Japan by the Washington‐based Center for Strategic and International Studies (CSIS, 2003) have identified three drivers for space policy: science, commerce and security. Each driver can be linked to the principles and objectives defined in the foreign space policies described within this Chapter, meaning they are also important considerations for Australia. It follows that space policy in the US and other nations influences policy development and

9 Five international legal principles and treaties are upheld by the United Nations Committee on the Peaceful Use of Outer Space (UNOOSA).

19 associated investment decisions for accessing space infrastructure and information in Australia. This thesis will identify the technical, institutional and economic influence of US and other space policies and systems on deploying and operating a NPI in Australia.

2.2.2 RUSSIAN SPACE POLICY

Russian space policy dates back to the former Union of Soviet Socialist Republics (USSR) with the launch of Sputnik, the world’s first artificial satellite in 1957, and initial development of Russia’s GPS equivalent GLONASS10 in the 1970s. Similar to GPS, GLONASS was originally designed and operated as a military system, with civilian use officially granted in 1995 (United Nations, 2004). Whilst the Russian Federal Space Agency, also known as Roskosmos, coordinates implementation of the GLONASS program, there are six State Customers that manage the program: the Federal Space Agency, the Ministry of Defence, the Ministry of Industry, the Ministry of Transport, the Ministry of Science and Education and the Federal Geodesy and Mapping Service.

Today, State Policy for the Federal GLONASS Program is governed by Presidential Decree No. 638 dated 17 May 2007, “On using GLONASS Global Navigation Satellite System for the Benefit of Social and Economic development of the Russian Federation” (GLONASS Union, 2013), which establishes the basic principles of free and unlimited access for worldwide commercial use. The Federal Program for GLONASS Sustainment, Development and Use for 2012‐2020 was recently approved on 3 March 2012 (UNOOSA, 2013).

Russia remains a leader in commercial launch services for a range of communications, navigation and remote sensing activities, and its space program plays an active role in managing the International Space Station (ISS). Key policies include the 10‐year Federal Space Program announced in 2005, which outlines scientific and commercial goals for modernising Russia’s space resources, and a 2008 policy paper by the Russian Security Council which outlines space priorities (ESPI, 2012). The Federal Space Agency (2013) recently published its National Space Programme for 2013 to 2020.

2.2.3 EUROPEAN SPACE POLICY

The European Union (EU) provides policy leadership through its Resolution on the European Space Policy that was adopted in 2007 by the EU Council of ESA and the European Commission. The Resolution emphasises social, scientific, commercial and national security requirements for establishing the EU’s flagship space programmes, Galileo and Copernicus (formerly known as the GMES11 programme). Subsequent Resolutions to the European Space Policy have been adopted since 2007 to ensure the

10 Global’naya Navigatsionnaya Sputnikovaya Sistema (GLONASS). 11 Global Monitoring for Environment and Security.

20 policy remains relevant and focussed on improving global innovation and competition in space activities (European Commission, 2013).

Galileo is the European owned and operated GNSS described in Section 2.3.5, and its development is guided by the policies described in this Section. In 2013, the EU Council adopted the EU Space Industrial Policy which focuses on realising economic growth in the space sector. Funding for the period 2014 – 2020 to bring the Galileo system to Full Operational Capability (FOC) is estimated at approximately €6.3 billion through the EU’s Multi‐annual Financial Framework (MFF) (Gutierrez, 2013). Full public funding was required after previous attempts to establish Public‐Private Partnerships broke down in 2007 (Gibbons, 2007). The European Commission delegates design and procurement responsibilities to ESA, and regulatory oversight is assigned to the European GNSS Agency (GSA), which superseded the Galileo Joint Undertaking (GJU) in 2006 (Gutierrez, 2013).

2.2.4 JAPANESE SPACE POLICY

Prior to 2009, Japanese space policy was carried out by different ministries with no government office to exercise leadership and oversight. Following the Basic Space Law enacted in 2008, the Office of National Space Policy was established, and a Basic Plan for Space Policy was released by the Strategic Headquarters for Space Policy (Government of Japan, 2009). The Plan is a five‐year program from 2009 to 2013 that identifies a range of environmental and communications satellites and research missions to be launched by Japan. The Quasi Zenith Satellite System (QZSS), a regional satellite positioning system that is interoperable with GPS, establishes the navigation component of the program to augment positioning services in Japan and the Asia‐Pacific, particularly in mountainous regions and cities where coverage is limited using GPS alone. A decision was made by Japan’s Cabinet Office in 2011 to accelerate development of QZSS for full service by 2020 (Government of Japan, 2011). The Basic Plan for Space Policy covering the years 2013 to 2017 was released by the Strategic Headquarters for Space Policy of Japan in January 2013 (Government of Japan, 2013).

2.2.5 CHINESE SPACE POLICY

The national space agency responsible for China’s space program is the China National Space Administration (CNSA) within the State Administration for Science, Technology and Industry for National Defense. In 2011, China’s Information Office of the State Council released a white paper titled China’s Activities in 2011, which outlined key policies and tasks between 2011 and 2016 (People's Republic of China, 2011). The paper sets out China’s short term goals for space transportation, satellite development, space applications and space science, and promotes scientific and economic growth and national security. The paper also includes the three‐step development plan for the country’s satellite navigation system Beidou, from an experimental system, to a regional system, then a global system by 2020.

2.2.6 INDIAN SPACE POLICY

The military origins of India’s space activity dates back to 1962 when the Indian National Committee for Space Research was established to advise government on civil and military policy and launch options (Harding, 2012). This was superseded by the Indian Space Research Organisation (ISRO) in 1969 within the Department of Space, which is a branch of the National Natural Resources Management System (NNRMS). Military programs are developed under a separate agency, the Defense Research and Development Organisation (DRDO).

The Satellite Navigation Program administered by ISRO includes the GPS Aided Geo Augmentation Navigation (GAGAN) system agreed in 2001, and the autonomous Indian Regional Navigation Satellite System (IRNSS) announced in 2006. Both systems are currently under development, with the first IRNSS satellite (IRNSS‐1A) launched on 1st July 2013 (Inside GNSS, 2013b), joining two GAGAN geosynchronous satellites already in orbit. The recent 2013‐14 Indian budget increased spending for ISRO’s space program to US$1.3 billion, reflecting an increase in activity for implementing these systems (Hughes, 2013).

2.2.7 AUSTRALIAN SPACE POLICY

Australia is notably absent from the public spending data in Figure 5 since the Australian Government does not own, manufacture, launch, or operate space‐based assets. Space‐related funding across the Australian Government is traditionally administered through Departmental appropriations, such as those of Geoscience Australia (GA) and the Bureau of Meteorology (BoM). The funds are used to purchase and license data such as satellite imagery, and to build and operate ground‐based infrastructure such as GNSS receivers and celestial tracking and monitoring systems, including Very Long Baseline Interferometry (VLBI) sites (refer to Section 3.5).

A recent exception was the AUD $48.6 million Australian Space Science Program (ASRP) announced in the 2009‐10 Budget (Australian Government, 2009b), $8.6 million of which established the Space Policy Unit (SPU) to coordinate Australia's national and international civil space activities. The remaining $40 million was administered by SPU to support space‐related research, education, and innovation activities through 14 competitive merit‐based grants (Australian Government, 2009a).

In 2011, SPU released the Australian Government’s Principles for a National Space Policy, which set the foundation and direction for Australia’s Satellite Utilisation Policy released in April 2013. This is Australia’s first official space policy. However, early policy work can be traced back to 1985 with a report prepared by the Australian Academy of Technological Sciences (AATS) for the Minister of Science (AATS, 1985).

The Satellite Utilisation Policy recognises that Australia relies heavily on international space systems to support civilian and national security functions, and that coordination and engagement both nationally and internationally is needed as this dependence grows. The policy specifies seven principles (SPU, 2013) to reaffirm the Australian Government’s focus on:

1. Space applications that have a significant security, economic and social impact, specifically Earth Observation, Satellite Communications and PNT applications;

2. Ensuring resilient access to those space systems on which we rely now and to those important to our future national security, economic, environmental and social well‐being;

3. Strengthening those relationships and cooperative activities on which Australia relies, and will continue to rely to a substantial degree, for space system capabilities;

4. Continuing to support rules‐based international access to the space environment; promoting peaceful, safe and responsible activities in space;

5. Enhancing the coordination, understanding and strategic direction of Australia’s uses and approach to space;

6. Promoting collaboration between Australian public and private research and development organisations with industry in space‐related activity, including space science, research and innovation in niche areas of excellence or national significance;

7. Ensuring Australia’s space capabilities will be used to enhance, and guard against threats to our national security and economic well‐being.

The policy established a new Space Coordination Office (SCO) and Space Coordination Committee (SCC) (Figure 7) within the DoI from 1st July 2013. As the central point of contact and coordination for all Australia’s national and international civil space activities, the SCO coordinates the implementation of the policy, and administers the Space Activities Act 1998. Critically, the SCC has two initial working groups that will lead the planning and future implementation of a National Earth Observations from Space Infrastructure Plan (EOS Plan) and a National Positioning Infrastructure Plan (NPI Plan), the latter of which addresses Australia’s long‐term PNT requirements. The technical, institutional and economic criteria identified, related and analysed within this thesis will inform development and implementation of the NPI Plan.

FIGURE 7: AUSTRALIAN GOVERNANCE FOR SPACE ACTIVITIES

New governance structure established through Australia’s Satellite Utilisation policy. The Australian Government SCC will report to the Coordination Committee on Innovation. The SCC will work closely with a National Security Space Inter‐Departmental Committee (NSS IDC) to manage national security dimensions of civilian space activities. The SCC will also receive advice from a committee representing stakeholders in industry and research sectors and in State and Territory governments (Australian Government, 2013a).

2.3 GLOBAL NAVIGATION SATELLITE SYSTEMS

Satellite‐based positioning systems allow users to determine three‐dimensional (3D) global location by simultaneously measuring distances from a receiver to a number (at least four) satellites orbiting the Earth. In simplistic terms, each distance is determined by measuring the time taken for a radio signal to be sent from a satellite to the receiver, and multiplying this time difference by the speed or ‘velocity’ (the speed of light12) at which the signal travels. The introduction of time‐based radionavigation technology as a modern and indispensable positioning technique is explored below by reviewing early navigation and satellite systems that led to the development of GPS and other GNSS. Principles of geodesy are introduced to describe why any location can be determined relative to the Earth using satellite radionavigation systems.

2.3.1 EARLY RADIONAVIGATION SYSTEMS

The origins of radionavigation date back to the early 1940s when the British Royal Air Force13 developed the first ground‐based system codenamed Gee during World War 2 (WWII) (NIMA, 2002). This was closely followed by the more accurate Long Range Navigation (LORAN) ground system developed by the Radiation Laboratory within the Massachusetts Institute of Technology (MIT) (RAND Corporation, 1995). Both systems applied the principles of hyperbolic navigation14 to measure the time taken to receive radio signals that were sent between aircraft and dedicated ground communications towers. This time difference revealed the approximate distance to each tower. The short and long range accuracies of Gee ranged from 200 m to over 6 miles (9.5 km) respectively, and the absolute accuracy of LORAN ranged from 0.1 nautical miles (nm) (185m) to 0.25 nm (460 m) (NIMA, 2002). The OMEGA navigation system was the first truly global long‐range radio navigation system built on a global network of terrestrial radio beacons (Pierce et al., 1966).

Following the launch of the first artificial satellite Sputnik 1 by the Soviet Union in 1957, radio pulses from the satellite were tracked in a way that determined when it reached its closest distance to an observing site. As the satellite approached a ground receiver, the frequency of each pulse would increase (i.e., shorter wavelength) until it reached its closest point above the receiver. After passing this point, the frequency would decrease (i.e., longer wavelength) as the satellite moved away.

This relative change in frequency of the Sputnik radio signal is an example of the Doppler effect, which was first discovered in 1824 by Christian Johann Doppler (Doppler, 1842). Figure 8 provides a basic example of the Doppler Effect by illustrating the changing frequency of a sound wave moving towards and away from an observing site.

12 299,792,458 metres per second (m/s). 13 The British Royal Navy also deployed the Decca Navigator System in WWII to support ship and aircraft navigation. 14 Hyperbolic Navigation describes the form of radionavigation that is based on differences in time when receiving two radio signals along a baseline.

FIGURE 8: DOPPLER EFFECT

The Doppler Effect means the frequency of the sound wave from the ambulance increases (i.e., shorter wavelengths) as the ambulance approaches the stationary observer. The frequency becomes lower (i.e., longer wavelengths) as the ambulance recedes. Observing a higher frequency from the ambulance corresponds to a higher pitched sound. The same theory applies to measuring the velocity between a GNSS satellite and receiver that are moving relative to one another.

In the 1960s, the US Navy sponsored two programs which became predecessors to GPS: TRANSIT15 and Timation. TRANSIT was originally developed to locate ballistic missile submarines and other ships at the ocean’s surface, but was made available for civilian use in 1967 to service demand from maritime navigators. Timation advanced the use of high‐stability clocks, methods of time‐transfer, and two‐ dimensional navigation after the first satellite was launched in 1967. A third design concept known as System 621B was also explored by the US Air Force to provide three‐dimensional navigation and this system verified the use of pseudorandom noise (PRN) measurements as a new form of satellite ranging in 1972. GPS uses PRN codes to measure signal transit time between a satellite and receiver. The US Army had also proposed its own Sequential Correlation of Range (SECOR) system during this period and RAND Corporation (1995) provides a comprehensive overview of the motivation and technology for developing each of these systems.

In 1968, the US Department of Defense (DoD) established the Navigation Satellite Executive Group (NAVSEG) as a tri‐service steering committee that would coordinate and leverage current efforts by the US Navy, Air Force and Army towards establishing a global, all weather, continuously available, highly accurate positioning and navigation service. The proposed Defense Navigation Satellite System (DNSS) managed by the US Air Force was intended to support a broad spectrum of users, whilst saving the DoD money by limiting the proliferation of specialised equipment for particular missions (RAND Corporation, 1995).

15 TRANSIT was developed by the John Hopkins Applied Physics Laboratory (APL) under Dr. Richard Kirschner.

By December 1973, a new concept known as the NAVSTAR GPS was approved as a compromise between each of the programs described above, which led to the development of the GPS service that society relies on today. FOC of the 24‐satellite constellation was declared by the US Air Force in 1995.

The Soviet Union also developed a satellite positioning system known as Tsikada, or ‘Cicada’ in the 1970s that transmitted the same two radio frequencies as TRANSIT using similar Low Earth Orbit (LEO) satellites. The 10‐satellite constellation consisted of six military satellites, with the remaining four designed for civilian use (Hofmann‐Wellenhof et al., 2008).

2.3.2 GEODESY

Prior to describing the current status of GPS and other GNSS, it’s important to recognise the role that the field of geodesy plays in establishing a common coordinate reference frame for computing and recording location, or ‘position’. By defining the size, shape, origin and orientation of a terrestrial (geodetic) coordinate system, the position of any object can be determined relative to that system using geodetic measurements and computational techniques.

Put simply, the science of geodesy is used to measure the size and shape of the Earth through time and to understand its gravity field. Geodesy is therefore used to establish coordinate systems to record location. Space geodesy includes measurements to natural and artificial satellites using equipment such as Very Long Baseline Interferometry (VLBI), Satellite Laser Ranging (SLR) and GNSS. Satellite positioning systems require a consistent global frame of reference in order to compute new positions using a combination of absolute and relative satellite‐based positioning techniques.

The remainder of this Chapter reviews the system architectures and status of international GNSS, RNSS and SBAS programs. Detailed technical descriptions are available from Hofmann‐Wellenhof et al. (2008) and the United Nations (2010), and from the regular program updates provided by the International Committee on GNSS (ICG) within the United Nations Office for Outer Space Affairs (UNOOSA, 2014). A comprehensive description of all GNSS, RNSS and SBAS infrastructure and services is available online from ESA and is updated regularly (ESA, 2013).

2.3.3 GPS (US)

The NAVSTAR GPS is the most familiar and widely used satellite‐based positioning system worldwide. It is a global information infrastructure that establishes a free and open utility for accessing PNT information (GPS.gov, 2013). GPS products and services support a wide range of military, civilian, scientific and commercial functions that affect many aspects of modern life.

GPS and other GNSS consist of three main segments: the space segment, the control segment and the user segment. A technical overview of each segment and regular system updates are available at

GPS.gov (2013), including key milestones for the GPS modernisation program that was first announced by US Vice President Al Gore in January 1999. An overview of each segment and associated upgrades administered through the GPS modernisation program to improve service integrity, signal availability and the overall accuracy of the system are provided below.

2.3.3.1 SPACE SEGMENT

The first NAVSTAR GPS satellite was launched in 1974 for concept validation purposes. This was followed by the first operational Block I satellite launched in 1978. At the time of writing, the GPS is at FOC with a space segment consisting of 27 operational satellites that occupy Medium Earth Orbit (MEO) at a height of approximately 20,200 km above the Earth. There are six orbital planes that are inclined at 55° to the equator and separated by 60° in right ascension. Each satellite completes a full orbit every half sidereal day which equates to 11 hours and 58 minutes. Each plane contains four satellites, although a recent constellation expansion known as ‘Expandable 24’ means the GPS is effectively a 27‐satellite constellation (US Air Force, 2011).

GPS satellites transmit two radio signals known as L1 (1575.42 MHz16) and L2 (1227.60 MHz) within the L‐Band17 frequency range used for radionavigation. Both signals deliver navigation and system information using two types of pseudorandom noise (PRN) codes that are unique to each satellite. The Course Acquisition PRN code (C/A‐code) is modulated or ‘carried’ on the L1 frequency and the Precise code (P‐code) is carried on both L1 and L2. C/A‐code can be accessed without authorisation, whilst the P‐code is encrypted through a process known as anti‐spoofing to prevent unauthorised access. The Code Division Multiple Access (CDMA) technique is used to assign each satellite a unique segment of C/A and P‐code. Each code delivers part of the satellite message that contains system information such as approximate satellite locations, satellite health updates and atmospheric modelling parameters. Technical details of the signal structure and satellite navigation messages for each carrier frequency and PRN code are provided by the Global Positioning Systems Directorate (2011) and Hofmann‐Wellenhof et al.(2008).

From an operational standpoint, the C/A‐code can be accessed free of charge by civilian users as part of the Standard Positioning Service (SPS). P‐code is encrypted to produce the P(Y)‐code that can be accessed through the Precise Positioning Service (PPS) by authorised users only. C/A‐code has a long wavelength (about 300 m) and repeats every millisecond but is less accurate than P‐code given its short wavelength of about 30 m. The encrypted P‐code is more difficult to spoof (copy) than C/A‐code and its wide bandwidth is more difficult to jam.

16 Megahertz. 17 L‐Band refers to the 1‐2 Gigahertz (GHz) frequency spectrum.

The DoD (2008) specifies a global Signal‐in‐Space (SIS) User Range Error (URE18) of ≤7.8 m for the SPS19, which is statistically equivalent to ≤4.0 m Root Mean Square (RMS20), as identified in Figure 9. The characteristics of SIS errors are defined in Chapter 3 but can be described here as the total range error between a user’s receiver and a satellite arising from differences between predicated navigation information and ‘true’ navigation data (e.g., position and time information). Subject to satellite geometry and availability, this URE translates to a global average21 position accuracy of ≤9.0 m (95% confidence) horizontal (hz), ≤15.0 m vertical (95% confidence), and timing accuracy ≤40 nanoseconds22 (ns) (DoD, 2008). These averages are for a measurement observation period of 24‐hours as opposed to instantaneous position accuracy. Figure 9 demonstrates that the current GPS SPS is well exceeding its URE target having achieved an average of 0.9 m RMS since 2009.

FIGURE 9: GPS SIGNAL‐IN‐SPACE PERFORMANCE

GPS Performance Standards for Signal‐in‐Space (SIS) User Range Errors (URE) compared with observed performance between 2001 to 2010 (GPS.gov, 2013). Observed performance continues to exceed specifications.

2.3.3.2 SELECTIVE AVAILABILITY

Until May 2000, the US DoD actively degraded the position and timing accuracies of the SPS through a strategy known as Selective Availability. Selective Availability was implemented to prevent the spread of GPS technologies and capabilities to foreign military forces. By deliberately introducing errors into each satellite clock through a process known as dithering, and misrepresenting the orbits of each satellite, Selective Availability degraded the URE. Horizontal accuracies degraded from around 20‐30 metres to

18 A measure of the user’s position accuracy. 19 Single‐frequency C/A code. 20 RMS corresponds to one standard deviation (σ). 21 At worst, ≤17.0 m (hz) and ≤35.0 m (DoD, 2008). 22 1 ns = 1 x 10‐9 (one billionth of a second).

100 metres (at a 95% confidence interval) with Selective Availability turned on, and timing accuracies were degraded from 200 nanoseconds to around 340 nanoseconds (at a 95% confidence interval) (RAND Corporation, 1995).

Whilst Selective Availability degraded the SPS, various Differential GPS (DGPS) positioning techniques were developed within the civil user community to circumvent its effects. GPS receivers were positioned over a ground mark that had known geodetic coordinates, which allowed corrections to be computed for each pseudo‐range measured at the receiver. The pseudo‐range correction is the difference between the measured range (affected by Selective Availability and other errors) and computed range (derived from the known receiver coordinate). The ‘corrections’ were broadcast to nearby GPS receivers using dedicated radio devices, which allowed a more accurate position to be computed.

DGPS positioning techniques underpin the high accuracy positioning products and services examined within this thesis.

Selective Availability was discontinued from the year 2000 after the US Government and former Interagency GPS Executive Board (IGEB), predecessor to today's National Executive Committee for Space‐Based PNT (Figure 6), recognised the key role that GPS plays as a global information infrastructure to support civil and commercial PNT needs worldwide (IGEB, 2003). The opportunity costs of the decision to remove Selective Availability are reviewed in an economic context in Section 6.3.1.4 with regards to the public good benefits to society and industry that free and open access to GPS has created.

2.3.3.3 CONTROL SEGMENT

The GPS control segment is a global network of ground infrastructure used to track, monitor, analyse and update the GPS satellite constellation. The 2nd Space Operations Squadron (2SOPS) at Schriever Air Force Base in Colorado Springs is responsible for the daily command and control of the GPS constellation. Key tasks include satellite maintenance and manoeuvres, periodic updates of satellite orbits (ephemerides) and clock information, time synchronisation of the satellites, and uploading the satellite message that is communicated to users.

GPS.gov (2013) provides an overview of the current Operational Control Segment (OCS), which includes a Master Control Station (MCS) and alternate MCS, 12 command and control antennas and 16 monitoring sites. Monitor stations track carrier signals from the GPS satellites and transfer this navigation information to the MCS. The MCS monitors the health and accuracy of the GPS constellation and computes precise locations (ephemerides) and clock parameters for each satellite. Ground antennas controlled by the MCS upload these navigation messages to satellites, along with other system commands using S‐band communication links.

2.3.3.4 USER SEGMENT

The GPS user segment comprises the products and services that are used to observe, integrate and apply GPS information. In its simplest form, the user segment refers to GPS receivers that detect, record and process GPS signals to compute PNT information. In today’s modern information economy, GPS technology is integrated into everything from cell phones and banking systems to high accuracy engineering, agriculture, surveying and construction equipment. The price and quality of each product and service varies with each application, meaning the user segment underpins the market analyses presented within Chapter 6, to review the quantity and type of GPS products and services demanded by consumers.

Examples of applications in different sectors of the economy that are becoming increasingly reliant on GPS information are shown in Table 2.

TABLE 2: GPS APPLICATIONS

Sector Applications Transport Road, rail, aviation and maritime transport systems and logistics management Engineering Construction, mining, surveying, structural monitoring Environmental Agriculture, weather prediction, hazards monitoring and management National Security Defence, emergency management, safety of life applications Banking and Finance Financial transactions and telecommunication synchronisation Spatial Geo‐imagery, land surveys and spatial data management Earth Sciences Climate change (sea level monitoring) and crustal monitoring Social Location based services including smart phones and other hand‐held devices

GPS applications across different industry sectors.

2.3.3.5 GPS MODERNISATION

The GPS modernisation program is an ongoing, multibillion dollar effort to upgrade and enhance the space and control segments to improve GPS performance. Following the launch of eight Block IIR(M) GPS satellites between 2005 and 2009, a second civilian known as L2C has been made available on the L2 carrier to meet the increased accuracy and performance needs of commercial users. L2C is broadcast at a higher power than C/A‐code making it easier to receive in challenging environments (e.g., under tree foliage), thus increasing its reliability and operating range. Position accuracy can be improved in the user segment using dual‐frequency receivers that simultaneously track the C/A and L2C signals to improve ionospheric modelling. Ten satellites currently transmit L2C although the full benefits to users will not be available until the next generation Operational Control System (OCX) is completed and the GPS constellation is fully modernised by 2025.

In 2010, a third civil carrier signal known as L5 also became available on the newer Block IIF satellites, three of which are currently operational with the remaining nine due to be deployed by 2025. L5 is transmitted in a radio band (ARNS23) reserved exclusively for aviation safety services, and is designed to meet safety‐of‐life transportation requirements using a higher powered signal than C/A and L2C and greater bandwidth to improve jamming resistance. L5 contains two PRN ranging codes (I5‐code and Q5‐ code) with navigation data modulated on the I5‐code (GPSD, 2012). Whilst L5 will ultimately lead to increased productivity and cost savings through increased capacity and efficiency, particularly for transport services given signals are transmitted in the ARNS radio band, these benefits are also contingent upon the completion of OCX and the future launch schedule for Block IIF satellites.

The newest fleet of GPS satellites known as GPS III are scheduled for launch in 2015 and will contain the fourth civil signal known as L1C on the L1 carrier. Designed to enable interoperability between GPS and other GNSS and RNSS, including Europe’s Galileo, Japan’s QZSS, India’s IRNSS and China’s Beidou, L1C is designed to improve mobile reception and therefore access to modernised GPS services in cities and challenging environments.

A new military M‐code also became available on Block IIR(M) satellites and is transmitted on L1 and L2 in addition to the existing P‐code. M‐code enables higher resistance against jamming, increased navigation performance, higher security encryption and is transmitted at higher power (Hofmann‐ Wellenhof et al., 2008).

Further details on each generation (i.e., ‘Block’) of satellite and their launch schedules is available at GPS.gov (2013).

2.3.4 GLONASS (RUSSIA)

Global’naya Navigatsionnaya Sputnikovaya Sistema (GLONASS) is the Russian equivalent of GPS. It was developed as a military system by the USSR in the 1970s based on earlier experiences with the Tsikada Doppler system. The first GLONASS satellite was launched in 1982 and civilian access officially granted in 1995. A fully operational 24‐satellite constellation was first achieved in 1996 before a number of in‐orbit failures and a lack of funding for new satellites significantly reduced the number of active satellites to seven in 2002 (Urlichich et al., 2011). FOC was however restored in 2011 following increased funding approved through the GLONASS Mission Oriented Program, which focussed on system maintenance and modernisation, and GNSS equipment and technology development for transport, military and geodetic applications. The GLONASS Coordination Board established in 2002 provides program oversight and coordinates the activities of the six State Customers identified in Section 2.2.2.

23 Aeronautical Radio Navigation Service.

2.3.4.1 SPACE SEGMENT

The nominal baseline constellation comprises 24 GLONASS‐M satellites deployed in three (circular) orbital planes with an altitude of 19,100 km and a period of 11 hours, 15 minutes and 25 seconds (United Nations, 2010). Orbital planes are separated by 120° in right ascension with an inclination of 64.8° to the equator which, according to Habrich (1999 cited in Hofmann‐Wellenhof et al., 2008, p.349), provides simultaneous visibility to at least five satellites across 99% of the Earth. Four additional GLONASS‐M satellites are currently held as spares or ‘reserves’, and a newer GLONASS‐K1 satellite launched in 2011 is undergoing system testing.

GLONASS satellites currently implement the Frequency Division Multiple Access (FDMA) technique, meaning each satellite broadcasts its own carrier frequency. Hence, each satellite is differentiated by the frequency it transmits, which differs from GPS where each satellite transmits a unique PRN code on the same carrier frequencies. Satellite frequencies for GLONASS are centred at 1602.00 MHz in the L1 sub‐band and 1246.00 MHz in the L2 sub‐band (United Nations, 2004).

GLONASS navigation information is transmitted through the Standard‐accuracy C/A code on the L1 sub‐ band frequencies, and the high‐accuracy P‐Code on the L1 and L2 sub‐band frequencies. A new L3 (1202.025 MHz) signal is also available on the experimental GLONASS‐K1 satellite, which underpins a new generation of lighter GLONASS‐K (K1 and K2) satellites with improved clock stability and a longer design life (Urlichich et al., 2011). The first GLONASS‐K satellites are scheduled for launch in 2015. Importantly, L3 is a CDMA signal which enables greater interoperability with other GNSS (Hein, 2006). GLONASS‐K1 satellites will transmit a second civilian PRN code and a second military PRN code on the L3 carrier frequency, and GLONASS‐K2 satellites will also feature CDMA signals on the L1 and L2 frequencies. GLONASS‐K and GLONASS‐M satellites will contain the L3 signal and will continue transmitting FDMA signals (Lyskov, 2013). A new L5 signal is also being investigated. User positioning accuracy (i.e., URE) in 2012 is quoted at 2.8m RMS, with a future objective of 0.6m from new M, K1 and K2 satellites (GPS World, 2013c).

Having outlined the basic characteristics and functions of each segment for GPS in Section 2.3.3, the remaining technical descriptions for each GNSS only highlight major differences in system design and operations, including unique broadcast frequencies and positioning services, to avoid repeating the general purpose of each space, ground and control segment. Time standards and datum considerations for selected GNSS are reviewed in Chapter 3.

2.3.5 GALILEO (EUROPE)

Galileo is the European GNSS that is jointly funded and managed by the EU and ESA. Galileo will operate independently of GPS and GLONASS, but will provide full interoperability with both. The EU’s first venture into satellite navigation was the European Geostationary Navigation Overlay Service (EGNOS),

33 an SBAS similar to the US Wide Area Augmentation System (WAAS), both of which are detailed in Section 2.4.

Galileo is unique in that the program was justified on economic, social and technological grounds as a civilian system in contrast to the military origins of its US and Russian counterparts. Transport, agriculture, telecommunications, energy and finance applications continue to drive trans‐European investment in Galileo throughout the EU. As of January 2014, four Galileo satellites have been launched to complete the In‐Orbit Validation (IOV) phase, which is jointly funded by ESA and the EU. Fourteen additional satellites are planned for launch by 2015 to establish an 18‐satellite constellation as the program moves towards Initial Operating Capability (IOC) (Gutierrez, 2013).

A fully deployed constellation is expected by 2020, with 27 operational satellites plus three active spares that will orbit at an altitude of 23,222 km in three circular MEO planes at an inclination of 56° to the equator. Two Galileo Ground Control Centres (GCCs) have been deployed in Europe to perform satellite and navigation mission management using a global ground network of Galileo Sensor Stations (GSSs).

Galileo will provide four primary satellite services to the global user community (ESA, 2010):

1. Open Service (OS) – A free of charge PNT service comparable to that of other GNSS that will be delivered without a service guarantee.

2. Commercial Service (CS) – A paid service that provides access to two additional encrypted signals that improve PNT accuracy and provide a higher data transfer rate. The CS is likely to be backed by a service guarantee.

3. Safety‐of‐Life Service (SoL) ‐ Improves the OS by providing integrity information through a service guarantee to alert users when they fail to meet a certain threshold of accuracy. Safety‐ critical transport applications such as aviation and maritime services will be key beneficiaries.

4. Public Regulated Service (PRS) – PRS will focus on delivering continuous service through controlled access to encrypted signals. Public safety, national security and critical infrastructure are key drivers for the PRS.

A fifth Search and Rescue (SAR) service will also form part of the Medium Earth Orbit SAR (MEOSAR) component of the international satellite‐based program known as COSPAS‐SARSAT (NOAA, 2014). The program aims to provide accurate, timely and reliable distress alert and location data to help SAR authorities assist persons in distress on land or at sea.

The signal structure (European Union, 2010) for Galileo contains five CDMA carrier frequencies summarised in Table 3. Two of these signals E5a and E5b are sub‐bands within the wideband E5 range and, along with E1 and GPS L5, exist within the ARNS spectrum to support SoL services. Frequencies E1 and E5a are directly interoperable with the GPS L1 and L5 signals respectively. Galileo satellites will

34 transmit a total of 10 ranging codes spread across the three primary signal bands E1, E6 and E5, as identified in Table 324. A key feature of the E6 signal is its E6b ranging code that provides a high data transfer rate of 500 bits per second (bps) for the Galileo CS.

Target performance specifications for the OS are quoted by the UN (2010) as 15m hz and 35m vertical (95% confidence) for single‐frequency (E1) users, and 4m hz and 8m vertical for dual‐frequency (E1 and E5b) users. Hofmann‐Wellenhof et al. (2008) quote the same dual‐frequency requirements for the CS and SoL services, and 6.5m hz and 12m vertical for dual‐frequency PRS users. Timing is quoted at 99.5% availability and 30 nanosecond accuracy (95% confidence) (Hofmann‐Wellenhof et al., 2008, United Nations, 2010). Localisation accuracies using SAR are expected to be better than 100 m (95% confidence) for COSPAS‐SARSAT beacons fitted with Galileo receivers (United Nations, 2010).

2.3.6 BEIDOU (CHINA)

The BeiDou Navigation Satellite System is being developed by the China Satellite Navigation Office (CSNO) within the People’s Republic of China. Phase one was known as the BeiDou Demonstration project and consisted of three geosynchronous25 satellites launched between 2000 and 2003, to deliver wide‐area differential corrections across China (National Academy of Sciences, 2012). The project recently completed its second of three phases with a constellation of 14 operational satellites, five of which are in geostationary26 orbits at an altitude of 35,786 km; another five positioned in Inclined Geosynchronous Orbit (IGSO) at the same altitude, and the remaining four in MEO at an altitude of 21,528 km (CSNO, 2012). The second phase establishes a RNSS for coverage over China and surrounding areas (including Australia), and a full constellation with global coverage is planned for the third phase. The full constellation, to be completed by 2020, will consist of 35 satellites, 30 of which are non‐ geostationary and will be a combination of MEO and IGSO satellites in three orbital planes at an inclination of 55° to the equator (GPS World, 2013c).

BeiDou will offer two global services: an Open Service (free of charge) and an Authorised Service. A wide‐area differential service (accuracy better than 1m) and short message communication service will also be available in the China region (National Academy of Sciences, 2012). Beidou transmits CDMA signals using three carrier frequencies known as B1, B2 and B3 (Montenbruck et al., 2012) as summarised in Table 3, with B1 and B2 accessible through the Open Service, and all three frequencies transmitted through the Authorised Service. Plans are in place to shift the B1 signal to the L1 frequency centred at 1575.42 MHz from 2016 onwards to provide interoperability with GPS, GLONASS and Galileo

24 Hofmann‐Wellenhof (2008) provide a detailed description of each signal including the central frequency bands (E5, E6, E1), modulation types (e.g., BOC, AltBOC, BPSK, MBOC), PRN codes (E5a‐I, E5a‐Q, E5b‐I, E5b‐Q, E6a, E6b, E6c, E1a, E1b, E1c) and the services that each PRN code will deliver. 25 An orbital period with the same rotation period of the Earth, meaning the satellite returns to the same position in the sky after each sidereal day. 26 A circular geosynchronous orbit directly above the Earth’s equator, meaning an object in geostationary orbit appears fixed to ground observers.

35 services located in the same L1‐band (Gibbons, 2013). Note also the alignment between B3 and Galileo’s E5b in Table 3. All BeiDou services aim to provide position accuracy of ≤10 m (95% confidence) and timing accuracy of ≤20ns with respect to Coordinated Universal Time (UTC).

TABLE 3: GNSS CONSTELLATION PARAMETERS

GPS GLONASS Galileo Beidou Funding Public Public Public Public FOC 1995 1995 & 2011 2020* 2020* Nominal 24 24 27 35 Constellation 3 (MEO and Orbital Planes 6 3 3 IGSO) Orbital 55° 64.8° 56° 55° Inclination Signal CDMA FDMA & CDMA CDMA CDMA Separation Carrier 3 sub‐bands (L1, 3: (E2‐L1‐E1)**, E6, 3: L1, L2, L5 3: B1, B2, B3 Frequency Bands L2, L3) E5: E5a, E5b*** Central Carrier L1: 1575.420 L1: 1602.000 (E2‐L1‐E1): 1575.420 B1: 1561.098 Frequencies L2: 1227.600 L2: 1242.000 E6: 1278.750 B2: 1268.520 (MHz) L5: 1176.450 L3: 1202.025 E5: 1191.750 B3: 1207.140 (Civilian) (Dual Use) (Dual Use) OS: E1,E5 (Dual Use) Global Services SPS & PPS: Civilian & Military: SoL: E1,E5 Open: B1,B2 (Frequencies) L1,L2,L5 L1,L2,L3 CS: E1,E6,E5 Authorised: (investigating L5) PRS: E1,E6 B1,B2,B3 SAR: L6 downlink Geodetic Datum WGS‐84 PZ‐90 GTRF CGCS2000 BeiDou time GPS time GLONASS time Time System Galileo System Time (GST) (BDT) UTC (UNSO) UTC (SU) UTC (NTSC)

E129 (single frequency): L1 (C/A) URE:27 URE28 ‘Open Service’ ≤15.0 m (hz); ≤35.0 m vertical Position30: ≤10 m ≤4.0 m RMS ≤2.8 m RMS Position and E1‐E5 (dual; frequency): (95% confidence) UTC offset: UTC offset: Time Accuracy ≤4.0 m (hz); ≤8.0 m vertical UTC offset: ≤20 ns RMS ≤20 ns RMS Specifications UTC offset: ≤20 ns RMS

≤30 ns RMS

* Planned. ** E2‐L1‐E1 uses the same central frequency as L1 and includes the adjoining bands E1 and E2. *** E5a (1176.450 MHz) and E5b (1207.140 MHz) are sub‐bands within the E5 bandwidth, effectively producing three carrier frequencies within the E5 band.

Summary of constellation parameters, signals structures, signal frequencies, datums, time systems, and service performance specifications for GPS, GLONASS, Galileo and Beidou.

27 (DoD, 2008). 28 (GPS World, 2013). 29 95% confidence (UN, 2010). 30 (National Academies of Sciences, 2012).

2.4 REGIONAL NAVIGATION SATELLITE SYSTEMS

The term Regional Navigation Satellite System (RNSS) refers to regional satellite positioning systems that are not global but provide coverage over a specific portion of the Earth. This Chapter also reviews Space Based Augmentation Systems (SBAS) that complement GNSS and other RNSS infrastructure with additional measurement and communication signals for safety‐of‐life applications.

2.4.1 QZSS (JAPAN)

First authorised by the Japanese Government in 2002, the Quasi Zenith Satellite System (QZSS) is of considerable interest to the Australian user community given its coverage footprint across the Asia‐ Pacific region (Figure 10) and the type of services it will offer. QZSS is not a standalone navigation system but will consist of four satellites31 placed in Highly Elliptical Orbit (HEO) to ensure one satellite is always centred over Japan, in addition to GPS and other GNSS satellites. HEO is particularly beneficial for improving access to signals in mountainous regions and urban canyons where other GNSS coverage can be limited.

FIGURE 10: QZSS SATELLITE FOOTPRINT

QZSS coverage footprint across the Asia‐Pacific region.

Whilst QZSS was originally established as a joint public and private venture, the collapse of the Advanced Space Business Corporation (ASBC) in 2007 resulted in the Japanese Aerospace Exploration Agency (JAXA) taking full responsibility for the system. Its first satellite Michibiki was subsequently launched in September 2010, and in 2013 Japan’s Cabinet office announced funding for an additional three satellites, one more than originally planned.

31 Japan's Cabinet Office announced the expansion of the QZSS in early 2013 approving a $526 million contract with Mitsubishi Electric for the construction of three satellites for launch before the end of 2017.

A unique feature of QZSS is its signal structure that is directly interoperable with GPS through the L1 C/A, L1C, L2C and L5 ranging signals. QZSS is intended to improve signal availability from 90% with GPS alone to 99.8% with regional augmentation. In addition to the navigation signals, QZSS will also transmit augmentation signals known as the L1 Submeter‐class Augmentation with Integrity Function (L1‐SAIF) and the L‐Band Experimental Signal (LEX). L1‐SAIF is effectively an SBAS signal that complements Japan’s existing wide‐area differential correction service MSAS (MTSAT Satellite Augmentation System) described in Section 2.4.3.3. The LEX (1278.75 MHz) signal will provide a dedicated communication channel for broadcasting more complex correction information than standard differential SBAS to improve high accuracy positioning capabilities in the coverage zone. This presents significant opportunities for Australia and is an important consideration for identifying and evaluating data delivery mechanisms beyond terrestrial broadband networks, which are currently limited in their national coverage. Initial results from testing data transmissions with the LEX signal in Australia were presented at the 2013 Precise Point Positioning (PPP) Workshop in Ottawa Canada (Hausler, 2013).

2.4.2 IRNSS (INDIA)

The Indian Regional Navigation Satellite System (IRNSS) differs from QZSS in that it is a standalone system that provides an independent PNT capability for the India region as opposed to only augmenting existing GPS and GNSS infrastructure. To achieve this, the full constellation will contain seven satellites, three in geostationary orbit and the remaining four positioned in geosynchronous orbit. This allows visibility to all satellites across India on a 24‐hour basis. The first satellite was launched in July 2013 and FOC is expected in 2015.

IRNSS will offer a free Standard Positioning Service to civilian users and a restricted Precision Service for authorised users. Both services will offer the L5 signal (1176.45 MHz) for interoperability with GPS and Galileo (E5a), and a second signal S1 will be centred in the S‐band (2492.08 MHz) frequency. Whilst the higher frequency of S‐band can help to reduce ionospheric errors, the large separation from L5 can introduce additional processing challenges described by Rao et al. (2011).

2.4.3 SPACE BASED AUGMENTATION SYSTEMS

SBAS improve the accuracy, availability, reliability and integrity of GNSS and RNSS services. SBAS are primarily designed and implemented to support safety‐of‐life aviation services including aviation, maritime, road and rail transport, however there is no limit to application areas for SBAS (e.g., agriculture, emergency services and many others). Government funding and policy is used to develop, maintain and ensure open access to SBAS in various countries and to ensure safety‐of‐life standards are met for critical transport applications.

SBAS are also comprised of space, ground and user segments. Terrestrial networks of ground control stations are deployed to observe and monitor GNSS, RNSS and SBAS signals. Data corrections are then uploaded to dedicated SBAS satellites that transmit data to users via L‐Band PRN ranging codes. SBAS coverage is however fixed over a country or region using one or multiple (for redundancy) geostationary satellites rather than an entire constellation of MEO satellites. The space segment is essentially a combination of the geostationary satellites and the GNSS constellation(s) they augment.

SBAS ground control sites are distributed with a higher density than standalone GNSS control sites to improve atmospheric modelling capabilities across the service region. With reference to Section 2.3.3.2, SBAS are a form of differential positioning given the geodetic locations of ground stations are known, which allows the relative error corrections for observed signals to be computed and sent to users. Additionally, SBAS provide a space‐based (and ground‐based in the case of Galileo) capability for communicating integrity information that can alert users of faults or inconsistencies for safety‐of‐life applications. SBAS satellites are effectively communication satellites that send correction parameters at a higher data rate, and may (but not necessarily) transmit ranging codes identical to those of GNSS to increase the number of signals available.

A key property of SBAS services, particularly those owned by governments, is the stringent design and performance standards enforced by the International Civil Aviation Organisation (ICAO) to certify their use for aviation purposes. These standards include ICAO’s (2008) Standards and Recommended Practices (SARPS) for the type and content of data that is transmitted, and the Radio Technical Commission for Aeronautics’ (RTCA) Minimum Operational Performance Standard (MOPS32) for SBAS receiver and antenna equipment. For example, the US Government identifies these and other government and non‐government standards in its Performance Standard (FAA and DOT, 2008) for its Wide Area Augmentation System (WAAS).

It follows that SBAS are one of two systems recognised by ICAO for completing approaches with vertical guidance (APV) (Australian Government, 2011). APV is a major safety initiative designed to mitigate Controlled Flight into Terrain (CFIT) incidents by improving safety, efficiency and capacity through cost‐ effective navigation services for departure and landing. Barometric Vertical Navigation (Baro‐VNAV) is the second and more widespread method recognised by ICAO, and both methods are evaluated in an Australian context in Section 2.4.3.7. SBAS is an enabler for the US Federal Aviation Administration’s (FAA) Next Generation Transportation System (NextGEN) and the European Commission’s Single European Sky Air Traffic Management Research (SESAR) (IWG, 2012).

To benefit from the augmented signals, users must be located within the coverage region using a GNSS receiver that is compatible with SBAS signals. Most commercial receivers are now sold with an in‐built SBAS capability to receive open signals from government‐owned and operated SBAS, such as those in

32 See (RTCA, 2013) for document DO‐229 pertaining to GPS SBAS standards.

39 the US and Europe. These foreign owned systems provide no augmentation services in countries where SBAS coverage is unavailable, such as Australia. Global SBAS services are however offered by commercial providers and require users to own a vendor‐specific (proprietary) GPS and/or SBAS receiver to access the signals. OmniStar, owned by Trimble Navigation Ltd33, and StarFire, operated by Deere and Company, are leading commercial providers of SBAS services in Australia, with a strong focus on maritime and agriculture applications. Note however that commercial SBAS are not certified by the international aviation standards that govern public SBAS services such as WAAS for civil aviation. This distinction between public and private service standards provides an important comparison for identifying the minimum performance requirements that will maximise the utility of CORS infrastructure within a NPI (Chapters 6 and 7).

2.4.3.1 WAAS (US)

The Wide Area Augmentation System (WAAS) developed by the US FAA dates back to 1992 and reached IOC in 2003. It was the first implementation of an ICAO compliant SBAS and is defined by the FAA as a system:

“…designed to meet high accuracy, integrity, continuity, availability standards of aviation users, but is an open service that has the capability to support other applications as well” (FAA and DOT, 2008)

The WAAS ground network is comprised of 38 Wide‐area Reference Stations (WRS) located across the US, Canada, Mexico and Puerto Rico (see Figure 11). Three Wide‐Area Master (WAM) stations are used to compute the Wide‐Area Differential (WAD) corrections, which are uploaded to three commercially owned geostationary satellites via six Ground Earth Stations (GES) (Hofmann‐Wellenhof et al., 2008). GPS satellites and WAAS geostationary satellites comprise the space segment.

The US Government’s WAAS Performance Standard (FAA and DOT, 2008) specifies a three‐dimensional signal‐in‐space minimum accuracy limit of 4m (95% confidence). Associated Performance Analysis Reports demonstrate actual performance is around 1.6m (95% confidence). Performance metrics are often differentiated between en‐route operations and vertical guidance operations termed Localiser Performance with Vertical guidance (LPV). For instance, WAAS coverage is divided into five geographic zones, where zone one covers the 48 Contiguous US (CONUS) states and requires 99.999% availability for en‐route operations, and 99% availability for LPV approaches (but higher accuracy requirements, as described below).

33 Limited.

FIGURE 11: WAAS GROUND INFRASTRUCTURE

Location of WAAS ground infrastructure (FAA and DOT, 2008).

LPV‐200 is the most demanding guidance procedure that the WAAS is certified to support, which allows aircraft to descend as low as 200 feet above touchdown height. For comparison, en‐route applications require 0.40 nautical miles (nm34) hz accuracy (95% confidence) and have no vertical accuracy requirement, whilst LPV‐200 requires 16m hz and 4m vertical accuracy (95% confidence). A Horizontal Alert Limit (HAL) is communicated via WAAS if horizontal accuracy exceeds 40 m for LPV‐200, with a corresponding Vertical Alert Limit (VAL) of 35m. The number of LPV approaches being flown in the US now exceeds the number of more traditional landing approaches using Instrument Landing Systems (ILS).

2.4.3.2 EGNOS (EUROPE)

Like all SBAS, the architecture of the European Geostationary Navigation Overlay Service (EGNOS) is standardised for aviation purposes and each segment has a similar design to that described for WAAS. EGNOS became a fully operational free and open service in 2009, and a safety‐of‐life aviation service in March 2011. The EGNOS ground network contains 34 Receiver Integrity Monitoring Stations (RIMS) that transfer data to four master control stations (one active; three backup), which is uploaded to three geostationary satellites from six Navigation Land Earth Stations (NLES) (see Figure 12).

34 0.40 nm equates to 0.74 km.

FIGURE 12: EGNOS SYTEM ARCHITECTURE

EGNOS system architecture (De Smet, 2011).

Corrections parameters can be communicated to users via the space‐based Open Service and the terrestrial EGNOS Data Service (EDAS) as demonstrated in Figure 13. EDAS eliminates the need for direct access to geostationary satellites which provides an additional layer of redundancy if satellite transmissions are blocked or subject to interference. EDAS uses the Signal‐in‐Space over internet (SISNeT) concept developed by ESA and operates on a commercial business model with service providers offering service guarantees to customers.

FIGURE 13: EDAS SYSTEM ARCHITECTURE

EGNOS Data Service (EDAS) system architecture (IP: Internet Protocol, RDS: Radio Data System, DAB: Digital Audio Broadcasting) (GSA, 2011).

The European Commission took full ownership of EGNOS from ESA on 1st April 2009, meaning EGNOS and Galileo are both funded and managed by the Commission. Operational management, service provision and maintenance responsibilities are assigned to the European Satellite Services Provider (ESSP), a company comprised of seven European air navigation providers from Spain, Germany, France, Italy, UK, Portugal and Switzerland.

2.4.3.3 MSAS (JAPAN)

Japan’s SBAS uses two geostationary Multifunctional Transport Satellites (MTSAT) owned by the Japanese Meteorological Agency and Japanese Ministry of Land, Infrastructure and Transport. The MTSAT Satellite Augmentation System (MSAS) has been operational for aviation purposes since September 2007. MSAS contains four Ground Monitor Stations (GMS) that send GPS and MTSAT data to two MCS for upload to the geostationary satellites (see Figure 14). An additional two Monitor and Ranging Stations (MRS) are located in Hawaii and Australia which also function as GMS sites (Japan Civil Aviation Bureau, 2009).

FIGURE 14: MSAS SYSTEM ARCHITECTURE

System architecture for the MTSAT Satellite Augmentation System (MSAS) (Fujiwara, 2011).

2.4.3.4 SDCM (RUSSIA)

The Russian Federation is currently developing its System for Differential Correction and Monitoring (SDCM) to compute SBAS correction parameters and communicate integrity information for both GPS and GLONASS. Two geostationary satellites were launched in 2011 and 2012 and are currently

43 undergoing testing, with a third satellite planned for early 2014. The ground network (Figure 15) currently contains 19 reference stations across Russian territory, and five stations located abroad (three of which are on Antarctica). A further 21 reference stations are planned for Russia with an additional 18 to be distributed globally based on current projections (Stupak, 2012).

Full SBAS coverage for the L1 signal is expected in 2016, with L5 capabilities for central Russia expected by 2018. SDCM certification for LPV‐200 approaches is expected by 2019 (Lyskov, 2013). SiSNeT will also be used to broadcast corrections via a terrestrial network, similar to that of EDAS described previously.

FIGURE 15: SDCM REFERENCE STATIONS

Current and planned reference stations in Russia for the SDCM SBAS (Stupak, 2012).

2.4.3.5 GAGAN (INDIA)

The Airports Authority of India (AAI) and ISRO reached agreement in 2001 to establish the GPS Aided Geo Augmented Navigation (GAGAN) system. GAGAN has been implemented in two phases; a proof of concept phase completed in 2007 known as the Technology Demonstration System (TDS), and the Final Operations Phase (FOP) that commenced in 2009 and was completed in 2013.

GAGAN comprises 15 Indian Reference Stations (INRES), two Indian Master Control Stations (INMCC) and three Indian Land Uplink Station (INLUS) (Figure 16). Data is communicated via two operational35 geostationary satellites launched in 2011 (GSAT‐8) and 2012 (GSAT‐10) as part of the FOP phase (Cruising Heights, 2011, Ganeshan, 2012, Rao and Lachapelle, 2013). A third satellite GSAT‐15 is planned

35 The first GAGAN satellite launch in 2010 was unsuccessful.

44 for launch in 2015 to function as an in‐orbit spare (Sayeenathan, 2013). IRNSS will contribute three additional geostationary satellites.

GAGAN is expected to be fully operational in 2014 having received provisional certification (GPS World, 2013b) from the Directorate General of Civil Aviation (India) in December 2013.

FIGURE 16: GAGAN REFERENCE STATIONS

Location of GAGAN references stations (INRES), master control stations (INMCC) and uplink stations (INLUS) (Sudhir, 2013).

2.4.3.6 SOUTH KOREA

South Korea has also reported plans to develop an SBAS capability citing limited LPV36 availability from Japan’s MSAS as a primary driver (GPS World, 2013c). The system would include two geostationary satellites, two master stations, two ground uplink sites and five reference stations, although no formal documentation has been identified for system design, funding arrangements and time schedules by the Ministry of Land, Transport and Maritime affairs. Yun et al. (2013) report details of Wide‐Area DGNSS testing by Seoul National University between 2002 and 2004, and describe preliminary results from the Pseudolite‐Based Augmentation System project undertaken between 2010 and 2014 to demonstrate

36 Refer to Section 2.4.3.1.

45 the feasibility of an SBAS. GPS World (2013c) reports that demonstration projects are expected to be completed in 2014, and FOC for an SBAS is predicted for 2021 subject to funding approvals. The service would provide GPS L1 and L5 augmentation.

2.4.3.7 AUSTRALIA

None of the SBAS described previously provide coverage for Australia, and the Australian Government has not, to date, invested in an SBAS capability for the country. In response to a 2009 Aviation Policy White Paper (Australian Government, 2009), the Department of Infrastructure and Transport (Australian Government, 2011) completed an SBAS review to evaluate cost and timing issues for establishing an SBAS. The report highlighted that a number of new (GNSS) satellites and augmentation systems (RNSS and SBAS) will increase future satellite coverage across the country, meaning near‐term investment in an SBAS is difficult to justify. For example, the new GPS L5 safety‐of‐life signal in the aviation radio band is one example of the global aviation benefits that modernised GPS will offer. The report supported the increased adoption of APV at Australian aerodromes in line with previous ICAO resolutions, and noted the benefits of expanding Baro‐VNAV capabilities across all aerodromes as a near‐term solution.

Airservices Australia and the country’s Civil Aviation Safety Authority (CASA) are however active in their testing and development of Ground Based Augmentation Systems (GBAS) in Australia (Airservices Australia, 2012). The basic GBAS concept is to deploy a small network of GNSS receivers near an airport to simultaneously observe and transmit GNSS/RNSS data that improves signal accuracy when communicated to an aircraft on approach to land. GBAS services are a local implementation of the CORS network positioning services described in Chapters 3 and 4. GBAS are recognised by ICAO as a replacement for traditional ILS, and the technology is being adopted as part of next generation Performance Based Navigation (PBN) plans to improve safety, reduce fuel usage, reduce carbon dioxide emissions and increase capacity (FAA, 2013). The Honeywell Smartpath™ SLS‐4000 is the first and only GBAS certified for use by the US FAA and is being implemented at Sydney International Airport by Airservices Australia (2012), and at a number of international airports.

Noting the ground infrastructure theme that is explored throughout this thesis, it’s not surprising that aviation authorities are also focused on leveraging maximum benefit from multi‐GNSS enabled ground infrastructure before considering any major investment in space infrastructure. Fittingly, the recent launch of Australia’s Satellite Utilisation Policy has initiated whole‐of‐government engagement to begin identifying these cross‐sector benefits, by establishing Australia’s SCC that was introduced in Section 2.2.7. This is an important first step in recognising the social and economic value that can be created through coordinated access to existing ground infrastructure, with aviation providing a standout example.

2.4.3.8 GLOBAL SBAS COVERAGE

The emergence of standardised SBAS services in the US, Europe, Asia and Russia raises the prospect of one day achieving global SBAS coverage once each system is fully operational. The SBAS Interoperability Working Group (IWG) is the lead forum for addressing these questions and implementing the Standards and Recommended Practices (SARP) introduced previously. In particular, ICAO SARP Annex 10 defines standards that support interoperability amongst SBAS providers to facilitate a seamless transition from one service area to another. Indeed, the IWG has modelled potential coverage using a range of scenarios that incorporate expanded reference networks, single and dual frequency signal capabilities, and combinations of GNSS and SBAS services.

Figures 17 and 18 have been extracted from the 2012 global SBAS update provided at IWG 22 in Munich, Germany (IWG, 2012). Figure 17 shows that current operational WAAS, EGNOS and MSAS services cover less than 8% of the globe if a minimum requirement of 99% satellite availability is imposed. In light of future multi‐GNSS and SBAS developments, Figure 18 models potential global coverage by combining Galileo with dual frequency capabilities from WAAS, EGNOS, MSAS, GAGAN, SDCM, including their fully deployed reference station networks. This long‐term scenario demonstrates a dramatic increase in global coverage of up to almost 93% (with greater than 99% availability). The IWG (2012) considers this achievable between 2020 and 2025 to enable LPV‐200 approaches worldwide (GPS World, 2013a).

FIGURE 17: CURRENT GLOBAL SBAS COVERAGE

Global SBAS coverage (WAAS, EGNOS and MSAS) in 2012. Horizontal Alert Limits (HAL) and Vertical Alert Limits (VAL) are given in metres (IWG, 2012).

FIGURE 18: PROJECTED GLOBAL SBAS COVERAGE

Projected global SBAS coverage using dual frequency capabilities from WAAS, EGNOS, MSAS, GAGAN, SDCM and Galileo and, a fully deployed network of reference stations (IWG, 2012).

2.5 A MULTI‐GNSS FUTURE

Multiple GNSS, RNSS, SBAS and GBAS services will become operational over the coming decade. Multi‐ GNSS refers to the ‘system‐of‐systems’ environment that will result from having integrated access to all GNSS and RNSS. Multi‐GNSS services will be augmented by SBAS and GBAS infrastructure.

The benefits of a multi‐GNSS future frequently cited in the literature are improvements in the availability, accuracy, efficiency, continuity, reliability, and integrity of positioning services (Rizos, 2008, Dempster and Rizos, 2009, ASC, 2012). Australia finds itself with unique geographic, economic and political opportunities to leverage maximum benefit from global and regional constellations given the strength of its research and development capabilities, its stable political environment and ongoing investment in primary industries (e.g., agriculture, mining). Figure 19 illustrates the increased number of satellites that will be visible across Australia over the coming decade, and three primary benefits can be identified from accessing this multi‐GNSS infrastructure (Dempster and Rizos, 2009, ASC, 2012):

• Increased accuracy through more observations and better satellite geometry;

• Increased availability through more satellites transmitting more signals and services;

• Increased integrity through greater redundancy (i.e., more measurements) and reduced vulnerability from relying on one system alone.

FIGURE 19: PROJECTED MULTI‐GNSS SATELLITE COVERAGE

Anticipated average number of Satellite Vehicles (SVs) available by 2020 (based on 15° elevation cut‐off angle) from the GPS, GLONASS, Galileo, Beidou, WAAS, EGNOS, QZSS, MSAS, IRNSS and GAGAN constellations on a worldwide basis over a 24‐hour period (Dempster and Rizos, 2009).

Coupled with its geographically large and stable land mass, Australia offers an ideal location for deploying fundamental ground‐based tracking and monitoring facilities for these new satellite constellations (ASC, 2012). A globally distributed network of ground stations helps to observe, model and monitor key information such as satellite orbit locations, clock corrections and atmospheric parameters, which allow satellite‐based positioning services to function with greater accuracy and reliability. From an institutional perspective, Australia’s new SCC is currently the central point of contact within government for engaging and coordinating with these foreign providers.

In order to benefit from multi‐GNSS, users will need a receiver that is capable of observing and combining signals and information from each system. This in turn depends on each system being interoperable and compatible. The challenge of building interoperability and compatibility into each new system is both a technical and policy (institutional) issue, as demonstrated by the range of policy and system criteria described in this Chapter, including those in Table 3. To highlight this point, the US Space‐Based PNT Policy (2004) introduced at the beginning of this Chapter is revisited for its definitions of interoperability and compatibility:

• Interoperable refers to the ability of civil U.S. and foreign space‐based positioning, navigation, and timing services to be used together to provide better capabilities at the user level than would be achieved by relying solely on one service or signal;

• Compatible refers to the ability of U.S. and foreign space‐based positioning, navigation, and timing services to be used separately or together without interfering with each individual service or signal, and without adversely affecting navigation warfare.

A clear example of interoperability at the technical level is the alignment of signal frequencies, such as those of GPS and QZSS to facilitate observation and integration at the receiver level. Hein (2006) describes this as ‘signal interoperability’, and provides a separate definition for ‘system interoperability:’

“...where different GNSS systems provide the same answer, within the specified accuracy of each individual system.” Hein (2006)

Put simply, the information obtained from any system should be consistent, within tolerance, to ensure each system provides value to the user. At an institutional level, foreign policy agreements and partnerships are critical to ensuring the technical design of each system is interoperable and compatible with those of other providers. A summary of Joint Statements and Agreements between the US and other providers that facilitate this alignment is available from GPS.gov (2013), and key documents are identified in Table 4.

TABLE 4: INTERNATIONAL GPS AGREEMENTS & COLLABORATIONS

Year Country Statement/Agreement ‘Joint Statement by the Government of the US of America and the Government of Japan 1998 Japan on Cooperation in the Use of the GPS’

2004 Russia ‘Joint Statement on the U.S. GPS and The Russian GNSS’

‘Agreement on the Promotion, Provision and Use of Galileo and GPS Satellite‐Based 2004 EU Navigation Systems and Related Applications’ ‘United States‐Australia Joint Delegation Statement on Cooperation in the Civil Use of 2007 Australia GPS and Space‐Based Positioning, Navigation and timing (PNT) Systems and Applications’ ‘United States‐India Joint Statement ‐ Cooperation in the Use of GPS and Space‐Based 2007 India Positioning, Navigation and Timing Systems and Applications’ No formal Agreement – technical discussions completed at an operator‐to‐operator 2010 China level under auspices of International Telecommunications Union

2013 UK ‘Joint United Kingdom‐US Statement Regarding GPS Intellectual Property’

Joint Statements/Agreements between the US and other nations encouraging interoperability and compatibility for civil PNT service provision (GPS.gov, 2013).

2.6 CONCLUSION

A technical overview of all operational and planned GNSS, RNSS, SBAS and GBAS services has been provided. The overarching policy frameworks that drive public investment in these systems in response to public and commercial drivers have been identified. Foreign policy and subsequent investment in multi‐GNSS infrastructure has been shown to influence public investment decisions in Australia, most notably through the country’s ongoing deployment of ground infrastructure as opposed to owning space assets. Funding and management of this ground infrastructure is a central focus of this research to explore ways in which the utility of existing ground resources can be maximised through a NPI in light of public and commercial benefits that multi‐GNSS will bring. Australia’s Satellite Utilisation Policy has been introduced as a first step towards coordinating existing activities in Australia and providing a single point of contact (detailed in Chapter 5) for engaging with foreign service providers.

CHAPTER 3 POSITIONING INFRASTRUCTURE & GNSS POSITIONING TECHNIQUES

POSITIONING INFRASTRUCTURE & GNSS POSITIONING TECHNIQUES

3.1 INTRODUCTION

This Chapter describes why and how GNSS ground infrastructure is used to observe, record, and distribute high accuracy PNT information within a positioning infrastructure. Different positioning techniques that reduce common error sources affecting GNSS signals are reviewed. These techniques demonstrate the need to carefully plan where CORS infrastructure is located. Non‐GNSS positioning systems are briefly reviewed.

This Chapter concludes with an introduction to Australia’s Geospatial Reference Systems (GRS) to describe why coordinate systems are needed to reference GNSS position information, and why GNSS infrastructure contributes to managing national and international GRS.

3.1.1 RESEARCH RATIONALE

Chapter 2 identified that the Australian Government does not own space assets. In the PNT market, Australian users rely on free access to foreign owned GNSS/RNSS infrastructure made available through open data policies worldwide. Figure 20 illustrates that Australia’s positioning market can be evaluated in terms of the government and industry owned ground infrastructure that is used to augment GNSS/RNSS services. Australian governments and industry deploy GNSS ground infrastructure, predominantly in the form of CORS networks, to enhance the utility of satellite‐based positioning information across specific regions.

FIGURE 20: CHAPTER 3 RATIONALE

Rationale for Chapter 3 which identifies and explores the technical GNSS ground infrastructure (CORS) that enables high accuracy positioning services across Australia.

Prior to describing the evolution of CORS networks in Australia (Chapter 4) however, it’s critical to describe the technical functions of GNSS ground infrastructure (CORS), which ultimately influence the type, quantity, quality and configuration of CORS that are needed within a broader positioning infrastructure. These technical requirements influence public policies and commercial business models for accessing CORS infrastructure and associated positioning services in Australia, both of which are key themes explored in this thesis.

3.2 POSITIONING INFRASTRUCTURE

In Australia, the term ‘positioning infrastructure’ encompasses a broad array of infrastructure elements including ground‐based survey marks, ground reference stations (e.g., CORS, VLBI antennas), and a range of GNSS and non‐GNSS location devices (ANZLIC, 2010). Positioning infrastructure, like any other form of infrastructure, is developed to enable public and commercial benefits (refer to Figure 20). GNSS positioning systems, and the information they produce, support the functions of other infrastructures deemed critical to society (i.e., critical infrastructure37) including those for energy, food, water, transport, communications, banking and finance.

All infrastructure are developed according to specific technical, institutional and economic criteria for the application(s) they support. For example, cars, buses, trucks, bicycles and pedestrians all require access to road infrastructure to enable mobility. Road infrastructure is constructed and maintained to meet quality standards and regulations in accordance with local, State and Federal legislation (Austroads, 2013). Road infrastructure can therefore be described in terms of its technical requirements (e.g., construction materials, design specifications, quality control measures) and institutional requirements (e.g., standards and guidelines, legislation, ownership/funding arrangements, certification procedures). The costs of establishing this infrastructure are justified using an economic business case to articulate the value (benefits) proposition of public and/or private investment.

It follows that positioning policies and information standards (i.e., institutional requirements), and space and ground systems (i.e., technical requirements) are needed to produce PNT information that is valuable to governments, businesses and society at large. PNT information is therefore made available by establishing positioning infrastructure.

Chapter 2 introduced space policies and space infrastructure, and Chapters 4 and 5 explore economic assumptions that underpin the business case for deploying high accuracy PNT infrastructure in Australia. This Chapter discusses why GNSS is a key component of any positioning infrastructure. In this context, it is important to first describe the scalability of the term ‘infrastructure’, beginning with a definition:

37 Further detail on Australia’s critical infrastructure is available from the Australian Government (2010).

“The basic physical and organisational structures and facilities (e.g., buildings, roads, power ...) needed for the operation of a society or enterprise (e.g., the social and economic infrastructure of a country)” (Oxford Dictionaries, 2013)

From a societal standpoint, this definition represents the combined functions (e.g., transport and energy) enabled by the six critical infrastructure assets identified previously. At the enterprise level however, an individual ‘piece’ of infrastructure (e.g., a highway or bridge) can be viewed as one component of a much larger infrastructure (e.g., an entire road network). Hence, the definition of infrastructure is scalable given that different types of infrastructure contain different infrastructure components, which vary in their physical form and the organisational standards that guide their development. For example, in the same way that road infrastructure contains highways and bridges, a positioning infrastructure contains space and ground segments, as demonstrated in Figure 21.

FIGURE 21: POSITIONING INFRASTRUCTURE COMPONENTS

Space and ground infrastructure are integrated to establish positioning infrastructure in the same way that highway and bridge infrastructure are components of road infrastructure.

Non‐GNSS positioning infrastructures also exist that do not require space infrastructure. In the context of this thesis, a positioning infrastructure contains both GNSS and non‐GNSS components, which build redundancy, integrity and continuity into the positioning services it enables. Indeed, any augmentation

56 that improves the ability of the positioning infrastructure to observe, network, process, validate and deliver more information, improves its scalability.

3.2.1 GROUND INFRASTRUCTURE

As a general rule, GNSS ground infrastructure (e.g., receivers and antennas) can be deployed to augment the utility of standalone satellite positioning systems (e.g., GPS). In this context, GPS is not only a positioning infrastructure within itself, but an input to other positioning infrastructures that augment service performance (e.g., accuracy, availability, reliability) by combining multi‐GNSS and non‐GNSS technologies. The NPI described throughout this thesis is one such infrastructure that requires a national network of CORS to produce and distribute augmented positioning services.

3.2.1.1 CONTINUOUSLY OPERATING REFERENCE STATIONS

CORS infrastructure comprises the antenna, receiver and ancillary infrastructure used to continuously observe, record, distribute and archive signal data from one, or more GNSS, RNSS or SBAS. Ancillary infrastructure includes the physical monument on which the GNSS antenna38 is mounted (e.g., a portable tripod or stable ground pillar), primary and secondary communications and power infrastructure, additional sensors such as weather stations and cameras, and the physical housing in which the equipment is stored and protected. At the policy level, legal frameworks for leasing or purchasing land parcels, obtaining heritage clearance, and enforcing relevant planning laws to deploy a temporary or permanent CORS site are also key requirements for deploying and operating CORS infrastructure. Hence, the term CORS infrastructure accounts for the physical and institutional structures and facilities needed to establish, integrate, operate and maintain each component of a CORS.

Table 5 provides an example of the technical components that can be integrated to establish CORS infrastructure. Criteria identified in Table 5 vary for different applications depending on the level of infrastructure quality and stability that is required. These differences in the technical and physical characteristics of CORS infrastructure can be classified according to different ‘Tiers’ defined in Section 3.2.1.2 below.

38 The term ‘GNSS antenna’ implies that a GNSS receiver is used to record these observations.

TABLE 5: CORS INFRASTRUCTURE COMPONENTS

Component CORS Criteria (Depending on Tier) • Single, dual or multiple‐frequency receiver Single or Multi‐GNSS • Antenna (e.g., Dorne‐Margolin) Receiver/Antenna • Cabling • Mains (grid) power • Solar panels • Universal Power Supply (UPS) Power • Batteries • Power Distribution Unit (PDU) • Network Management System (NMS) • Cabling • Modem • Asymmetric Digital Subscriber Line (ADSL) • Very Small Aperture Terminal (VSAT) Information and • Radio (typically UHF) Communication Technologies • Broadband (e.g., National Broadband Network, mobile) (ICT) • Satellite (e.g., L‐Band, S‐Band, broadband) • Network Router • Firewall • Cabling • Automatic weather station (temperature, pressure, humidity sensors) Ancillary Sensors • Lightening detector • Antenna mount: o Deep or shallow drilled, concrete pillar, thermopile, polar mast, stainless Monument steel pin, survey tripod • Antenna tribrach • Ground reference mark (e.g., survey control point) • Building enclosure: o Shelving Housing o Insulation o Air conditioning • Security Fencing

Examples of common components that are integrated to form CORS infrastructure (UNAVCO, 2011).

3.2.1.2 TIERED INFRASTRUCTURE

In the absence of a real‐time communication mechanism to distribute data that is observed at a CORS site, GNSS observations are typically post‐processed once enough measurements are recorded and collected at each site. Traditionally, these ‘geodetic CORS’ have functioned as passive measurement devices to support the establishment and maintenance of the National GRS (NGRS) (see Section 3.5).

The stability of the physical monument and signal tracking capabilities of the GNSS antenna and receiver, including their internal quality control features, remain primary design considerations for deploying and operating passive geodetic CORS infrastructure. Over time however, the majority of these passive CORS have been upgraded with additional power and communications infrastructure to

58 establish real‐time data links and provide operational redundancy. Commercial grade equipment and software has also been developed to establish CORS networks that employ the positioning techniques reviewed in Section 3.3 to deliver real‐time, centimetre accurate positioning capabilities. The evolution of CORS networks in Australia is reviewed in Chapter 4.

Rizos (2008) subsequently defined a three Tier hierarchy for differentiating CORS in terms of their stability and quality. These Tiers form part of the standards and recommended practices being developed by Australia’s Permanent Committee on Geodesy (PCG) within the Intergovernmental Committee on Surveying and Mapping (ICSM), to guide the establishment and operation of CORS infrastructure. These guidelines have not been published at the time of writing but are summarised by Burns and Sarib (2010) as follows:

Tier 1 – High stability monuments to support geoscientific research and global reference frame (i.e., GRS) definition. Tier 1 sites support the International GNSS Service (IGS) and other equivalent ultra‐high accuracy networks in accordance with the IGS Site Guidelines39 (IGS, 2013b).

Tier 2 – High stability monuments, usually established by national geodetic agencies for the purpose of defining and maintaining the NGRS. Tier 1 CORS are generally a subset of Tier 2 stations that link national and international geodetic frameworks. Data from Tier 2 CORS are normally made available to relevant Federal, State and Territory jurisdictions for the purpose of national geodetic reference frame realisation and improvement (see Chapter 4).

Tier 3 – Stable monuments established by Federal, State and Territory governments and/or commercial organisations for the purpose of densification of the national CORS network, often supporting real‐time positioning applications. These stations generally operate in, and provide access to the national datum rather than define it.

Similar guidelines that align with work by the PCG have been developed and published by the NSW Government’s Land and Property Information (LPI) Division (LPI, 2011), partly driven by the fact that PCG guidelines have not yet been published. Guidelines have also been developed internationally including those of National Geodetic Survey (NGS) in the US (NGS, 2013b).

To summarise, existing and planned CORS infrastructure is a key component of positioning infrastructure that provides access to, and enhances the utility of GNSS position information linked to national and international GRS. Different Tiers are used to categorise the stability, quality and functionality of CORS.

39 Formerly the IGS Site Guidelines 2007.

3.2.2 NON‐GNSS POSITIONING INFRASTRUCTURE

Positioning systems that function independent of GNSS can complement and/or replace GNSS services. Non‐GNSS infrastructure can mitigate vulnerabilities associated with signal interference and decrease a nation’s reliance on foreign owned satellite systems. Non‐GNSS systems provide alternatives where GNSS coverage is limited or unavailable, the most obvious application of which is indoor positioning. Location Based Services (LBS) such as integrated navigation applications on a mobile phone are often designed to incorporate GNSS and non‐GNSS technologies. A common example is cell tower triangulation methods that are now routinely implemented on most standard mobile phones (Yang et al., 2010). The accuracy of the triangulated position may only be accurate to the nearest 100 m, but this still enables general navigation and can speed up the computation of a GNSS position. Many phones improve this accuracy by also observing free Wi‐Fi signals that abound in urban environments.

Locata Technology (LocataTech), a product developed by the Australian‐owned company Locata Corporation, can function as a standalone terrestrial positioning infrastructure, whilst also transmitting CDMA codes that complement existing GNSS signals (Locata Corporation, 2013). Rather than deploying satellite infrastructure, Locata uses a network of ground‐based transmitters (LocataLites) that broadcast strong radio‐frequency signals in the 2.4 Gigahertz (GHz) ISM40 radio band. This Wi‐Fi radio spectrum is currently free to license up to a certain power limit (currently one Watt) and higher power signals mean that a Locata receiver (Locata) can work indoors and outdoors (Locata Corporation, 2013) using special antennas (particularly to manage high multipath environments indoors). The resulting position accuracy can reach centimetres where sufficient LocataLites are available. However LocataLites are typically spaced41 closer to one another (e.g., within a few kilometres or less) compared with relative GNSS positioning techniques that deliver centimetre accuracy with networks of CORS spaced tens of kilometres apart. Hence, Locata is often described as a local extension to GPS that ‘fills the gaps’, thereby improving service coverage and reliability.

LOng‐RAnge Navigation (LORAN), briefly introduced in Section 2.3.1, was another independent positioning infrastructure previously used for radionavigation in US and other coastal waters. The most recent version LORAN‐C was terminated by the US Coast Guard in 2010. However, current research focuses on the development of Enhanced LORAN (eLORAN) technology, including the South Korean Government’s recent decision to implement an eLORAN system by 2016 (Inside GNSS, 2013d), and the formation of the non‐profit Resilient Navigation and Timing Foundation (RNT Foundation) in the US to advocate support for a privately funded eLORAN alternative to GPS (Inside GNSS, 2013c).

Other types of land or space based radio‐frequency signals that are transmitted for purposes other than PNT, but can also be used for PNT, are termed Signals of Opportunity (SoP) (Fisher, 2005). WiFi, digital television, radio and mobile phone signals are all examples of SoP. A key challenge to exploiting each of

40 Industrial, Scientific and Medical radio bands. 41 1 Watt transmission power delivers a line‐of‐sight range of 10 km or so (Rizos et al., 2010).

60 these signals is a lack of time synchronisation at the user end which is needed to determine signal travel times, and therefore distances to the transmitter for the purpose of triangulation (Fisher, 2005). BAE Systems plc42 has developed a research platform known as Navigation SoP (NAVSOP) that combines signals from GPS, air traffic control communications, television communication towers, WiFi, GPS jamming devices, cellular transmitters and radio communications towers, to compute a user’s position within a few metres (BAE, 2013).

There are other forms of positioning that are not based on radio frequency signals, including inertial and optical methods, which add another layer of augmentation and backup to positioning infrastructure and devices, but these methods are outside the scope of this thesis. It follows that although detailed technical descriptions of non‐GNSS infrastructure and positioning techniques are not provided within this thesis, they are technologies that need to be considered to address GNSS vulnerabilities in future work towards a NPI (ASC, 2012). These vulnerabilities include signal loss due to intentional or unintentional interference, signal jamming and malicious spoofing (The Royal Academy of Engineering, 2011). GNSS signals and their error sources are subsequently described in the following Sections.

3.3 GNSS MEASUREMENTS AND ERROR SOURCES

This Section introduces measurement and error characteristics (Figure 22) of the signal information transmitted by the multi‐GNSS systems described in Chapter 2. Positioning techniques that optimise the way in which this information can be applied by high accuracy positioning users are subsequently identified. Technical details on the functional and stochastic models used to compute the final position are beyond the scope of this thesis. An introduction to systematic and random errors that affect GNSS measurements is however needed to identify the extent to which ground infrastructure can improve accuracy and service performance. These concepts inform the technical component of the NPI Planning Framework (see Chapter 7), and underpin discussions in Chapters 5 and 6 on how a NPI can improve access to CORS infrastructure to increase positioning utility (accuracy, availability, reliability and integrity) on a national scale. GPS is used to demonstrate many of these concepts.

42 Public Listed Company.

FIGURE 22: GNSS ERROR SOURCES

GNSS signal propagation errors (ionosphere, troposphere, multipath), satellite errors (orbit and clock) and receiver errors (adapted from Brown, 2006).

3.3.1 CODE AND CARRIER PHASE MEASUREMENTS

A number of satellite signals were identified in Chapter 2 that are used to transmit satellite navigation information such as satellite orbit parameters, satellite health and satellite clock corrections. This navigation information is contained within ranging codes (e.g., C/A, L2C) that are transmitted to ground receivers using radio signals (e.g., carrier waves L1 and L2). In simple terms, the satellite‐receiver range is computed by measuring the time taken for a ranging code to arrive at the receiver and multiplying this time by the velocity at which the signal travelled (the speed of light). Due to a lack of synchronisation between the satellite and receiver clocks43, and the presence of atmospheric44 and other system biases45, the computed range does not reflect the ‘true’ range, and is thus termed a code pseudorange (Fraser, 2007). Satellite messages contained within the ranging codes help to model satellite specific biases to improve the code pseudorange accuracies. Whilst efficient, the resulting position solution is only accurate to around 5‐10 m if no augmentation is used to mitigate the error sources described in this Chapter.

To service the high accuracy positioning market, GNSS antennas and receivers are designed to observe and process the carrier wave itself. Whilst code measurements enable an approximate position to be solved instantaneously, GNSS receivers with single‐, dual‐ and triple‐frequency tracking capabilities can

43 Section 3.3.3. 44 Sections 3.3.4 and 3.3.5. 45 Sections 3.3.6 and 3.3.7.

62 measure the carrier phase of the radio signals used to deliver each ranging code. The carrier phase can be measured far more precisely (millimetres) than a pseudorange on account of its shorter wavelength. For example, the L1 carrier (0.19 m wavelength) is less than 0.10% of the wavelength of the C/A ranging code (≈300 m wavelength). Measuring the L1 carrier to within 1% (rule of thumb accuracy) will result in a raw measurement error of approximately ±2 mm (excluding the influence of external errors).

Carrier phase measurement techniques are beyond the scope of this thesis. Readers are referred to Hofmann‐Wellenhof et al. (2008) for technical details. Readers with a non‐technical background should note that the carrier signal wavelength (λ) represents one complete phase, or ‘cycle’ of the signal. A GNSS receiver measures only the fractional part of this full cycle as the signal arrives at the receiver. Given GPS satellites orbit at an altitude of approximately 20,200 km, and the L1 wavelength is only 0.19m, millions of cycles are repeated during signal transmission before the L1 carrier first reaches the GPS receiver.

Imagine a tape measure extending between the satellite and receiver with a numbering system that returns to zero after every 0.19 m. Regardless of the total distance, when the initial measurement is made the observer can only record a measurement that is less than or equal to 0.19 m within the section of tape that happens to intersect the receiver. As the satellite and/or receiver changes position, the receiver measures the change in range from this initial measurement (i.e., fractional part plus change in range). However, the total distance to the satellite at the time the initial measurement was made remains unknown. Hence, the carrier phase measurement is biased by an unknown number of full cycles that must be added to the portion (change in range) measured by the receiver in order to compute the full satellite‐receiver range. This unknown quantity is termed the integer ambiguity (N). Various techniques have been developed over the past three decades to solve this parameter in the most efficient, reliable and accurate way. These techniques are described in Section 3.4. Put simply, ambiguity resolution is essential to robust and reliable centimetre‐level positioning via GNSS.

Carrier phase measurements are subject to the same biases that affect code pseudoranges (both measurements come from the same radio signal after all), although some biases (e.g., ionospheric delays) affect the code and carrier signals in different ways. As demonstrated in Section 3.4, the spatially correlated nature of these biases over short distances on the Earth’s surface means that precise carrier phase measurements present unique opportunities for mitigating or eliminating certain biases altogether using relative positioning techniques. Furthermore, the fast initialisation properties of code pseudoranges are commonly used to narrow the search space for determining the full number of cycles (integer ambiguity) for the precise carrier phase measurement.

3.3.2 SATELLITE ORBIT ERRORS

Section 2.3.2 identified why satellite locations must be accurately measured in order to determine the location of an observing site on Earth via satellite ranging codes. Orbital parameters contained within the broadcast ephemeris are predicted using observations from ground stations within the control segment. These parameters are transmitted via the satellite navigation message attached to each ranging code (Hofmann‐Wellenhof et al., 2008).

Orbit errors represent the difference between a satellite’s predicted location (contained in the broadcast ephemeris) and its actual location. Communicating the broadcast ephemeris in real‐time via the satellite signal enables satellite positioning systems such as GPS to provide instantaneous positioning anytime and anywhere that satellites can be tracked. ‘True’ or final orbits typically take between 12 and 18 days to compute and the real‐time broadcast ephemeris is of lower accuracy46 than these post‐processed products. These real‐time errors affect the accuracy of the positioning solution computed by the receiver.

Orbit errors are further discussed in Section 3.4 when reviewing high accuracy positioning techniques and discussing the role of the International GNSS Service (IGS) in computing and monitoring global orbit information. It is important to note however that over the past three decades significant research and global collaboration (see Section 4.4.7) has been dedicated to improving orbit accuracies and decreasing the latency with which this information is made available to users (Kouba, 2009).

3.3.3 SATELLITE AND RECEIVER CLOCK ERRORS

Satellite positioning systems require highly accurate time information. Range measurements are computed by measuring the time taken for a signal to travel from a satellite to a receiver. Any timing errors will affect the accuracy of the computed position. Given that most GNSS satellites are positioned in MEO (≈20,000 km), and radio signals travel at the speed of light (≈3x108 metres per second), a clock error of one microsecond47 will produce a range error of around 300 m. GNSS timing measurements must therefore be accurate at the nanosecond (one billionth of a second) level to enable positioning accuracies at the metre‐level. Fortunately, GNSS satellites are fitted with caesium and rubidium atomic clocks that are ‘stable’ (variation over time) to better than a few parts in 10‐13 per day (Hofmann‐ Wellenhof et al., 2008). Galileo48 satellites contain newer hydrogen maser atomic clocks that improve this precision (stability) to better than 10‐15.

Time systems were introduced in Table 3. Each GNSS has its own time system (e.g., GPS Time; GLONASS Time) which each satellite clock is aligned to using information computed by the control segment. Each

46 Containing errors of around 1.0 m (IGS, 2013a). 47 1 microsecond = 1 millionth of a second (1x10‐6 seconds). 48 The Giove‐B test satellite launched in 2008 is the first satellite to fly a hydrogen maser in space.

GNSS provider dedicates considerable effort to managing their atomic time system and the amount by which it is offset from global standards, including Coordinated Universal Time (UTC) and International Atomic Time (TAI). To avoid continuous re‐adjustment, satellite clocks are allowed to drift within a specified tolerance of the standard, with deviations being tracked and mathematically modelled on a per satellite basis. These clock models are typically quite accurate given the high stability (and therefore predictability) of atomic clocks.

Clock correction coefficients are transmitted via the satellite navigation message to ensure all clocks can be synchronised (Fraser, 2007). Random clock drifts will remain which introduce residual errors that in turn manifest as inaccuracies in the computed position. According to the IGS (2013a), clock corrections broadcast via the satellite message are accurate to around 5 nanoseconds (ns), which translates to approximately 2m of range error for a single point positioning solution (i.e., without augmentation from surrounding CORS sites or SBAS). For higher precision applications, the IGS computes clock products using longer observation periods to model clock corrections with 0.75 picoseconds (ps) accuracy; less than 1mm of range error.

GNSS receiver clocks are much less accurate than atomic clocks, meaning they also drift relative to atomic time scales. Receiver clock error is determined and eliminated as part of the solution process for code range positioning using two main approaches. Firstly, the receiver can continuously ‘steer’ the low accuracy oscillator towards the relevant GNSS time system to minimise drift. Second, and more commonly (and economically), the receiver introduces periodic ‘jumps’ in the receiver’s estimate of time once the clock offset reaches a certain threshold (usually 1 millisecond) (Fraser, 2007, Inside GNSS, 2011). Relative positioning techniques described in Section 3.4.2 allow the receiver clock error to be almost entirely eliminated through the process of measurement differencing.

In a multi‐GNSS environment, timing offsets between the internal timing systems of each GNSS must also be broadcast in order to correlate ranging measurements to different satellite systems. For example, GLONASS broadcasts clock offsets to GPS, and Galileo IOV satellites transmit the Galileo to GPS Time Offset (GGTO) (Inside GNSS, 2013a). Put simply, GNSS system clocks are synchronised to their own internal time systems, and the offsets between each internal time system and UTC are computed with nanosecond accuracy, allowing measurements from each system to be time‐synchronised in one receiver.

3.3.4 IONOSPHERIC ERROR

The ionosphere extends from approximately 50 km to 1000 km above the Earth’s surface and contains ionised particles (free electrons) that interact with satellite signals. Ionisation is caused by solar radiation and is highly variable both spatially and temporally (Fraser and Donnelly, 2010). For example,

65 the dispersive49 effects of ionisation are higher in the afternoon when solar radiation is higher. There are more free electrons (higher ionisation levels) near the equator leading to more pronounced impacts on the GNSS signals in equatorial regions such as northern Australia.

Given GNSS signals are a form of electromagnetic radiation, the speed at which they travel is affected when exposed to ionised particles. Transmission times for the code and carrier phase signals described in Section 3.3.1 are affected in different ways. Carrier phase signals speed up (phase advance) resulting in ‘shorter’ carrier phase range measurements, and the codes are delayed (group delay) by the same amount, resulting in ‘longer’ range measurements. The resulting range errors vary from a few metres to tens of metres depending on solar radiation, satellite geometry, electron content, magnetic storms and the angle at which the signal arrives (Klobuchar, 1996 cited in, Fraser, 2007).

Transmission times are less affected for higher frequency signals. Thus a dual‐frequency receiver can be used to compare L1 and L2 measurements (in the case of GPS) and largely mitigate ionospheric effects. The PPS introduced in Section 2.3.3.1 allows authorised users to access the P‐code on L2, meaning relative ionospheric techniques can be applied using code pseudoranges for such users. Dual‐frequency code pseudoranges will become increasing available to civilian users in a multi‐GNSS environment with, for example, the introduction of L2C from GPS satellites. Single‐frequency receivers (e.g., L1 only) require empirical models to estimate Total Electron Content (TEC) and thus reduce ionospheric effects. The Klobuchar (1987) model broadcast via the GPS satellite message can reduce ionospheric error by about 50%.

Ionospheric modelling is also important for monitoring and protecting other technology and applications affected by space weather, including radio communications systems, power systems and geophysical exploration. The Ionospheric Predication Service (IPS) within the Radio and Weather Services branch of Australia’s Bureau of Meteorology (BoM, 2014) is responsible for monitoring and forecasting space weather across the Australian region. The IPS assimilates real‐time data feeds from selected Australian CORS sites, predominantly those managed by GA, to continuously update these weather models. GA also contributes a selection of dual‐frequency geodetic CORS to the Ionospheric Working Group within the IGS to improve global ionosphere models, particularly for GNSS purposes.

3.3.5 TROPOSPHERIC ERROR

The troposphere extends to an approximate height of 20 km from the Earth’s surface and is a neutral (non‐dispersive50) environment, meaning atmospheric refraction (delays) is the same for the code and carrier signals. Refraction occurs due to local variations in temperature, pressure and humidity (water vapour) along the satellite‐receiver path which delay signal transmission times. These delays cannot be eliminated using dual‐frequency observations given each frequency is affected equally. The resulting

49 In a dispersive medium, the velocity (propagation delay) of the signal depends on its frequency. 50 In a non‐dispersive medium, the propagation delay (velocity) of a signal is independent of frequency.

66 range error is typically up to 2.5m and the total delay along each satellite‐receiver path can be mapped to the zenith (vertically above a receiver) as a Zenith Tropospheric Delay (ZTD) (Glowacki et al., 2006).

The ZTD parameter comprises a hydrostatic (dry) and wet component. The hydrostatic component accounts for approximately 90% of ZTD and can be modelled accurately using temperature and pressure measurements. The remaining wet component is treated separately given water vapour is highly variable both spatially and temporally and is therefore difficult to predict (Dach et al., 2007). Tropospheric models used to compute wet and dry delays include those by Saastamoinen (1973) and Goad and Goodman (1974) (‘modified Hopfield’). Niell (1996) mapping functions are commonly used to map total tropospheric delays to the zenith.

Relative positioning techniques can significantly reduce tropospheric delays by leveraging the spatial correlation in tropospheric delay when stations are close together. It should be noted that this correlation tends to apply over a much shorter distance than the ionospheric delay, particularly when stations are at different heights. NRTK techniques extend tropospheric modelling capabilities across a wider region and although residual wet delays are difficult to model, they only contribute approximately 10% to the total delay.

ZTD range errors are also used for meteorological purposes by mapping the estimated wet component to a measure of Integrated Precipitable Water (IPW) vapour. Rather than estimating water vapour directly, the well‐defined hydrostatic delay component is subtracted from the total ZTD parameter that is modelled within the position solution, leaving an indirect estimate of range error for the wet component. ZTD information can therefore contribute to, and benefit from Numerical Weather Predictions (NWP) of temperature, pressure and humidity. Deriving ZTD information from networks of CORS provides greater spatial and temporal coverage than traditional radiosonde and Water Vapour Radiometer (WVR) techniques (Glowacki et al., 2006).

3.3.6 MULTIPATH

Multipath occurs when transmitted radio signals are reflected off surfaces near the receiver or satellite making the travel path longer than the direct satellite‐receiver path. The delayed code or carrier phase measurements cause range errors. Nearby buildings, trees, water, and other reflective surfaces will increase receiver multipath, which is difficult to model or eliminate.

Satellite multipath occurs from objects near the satellite antenna and can be reduced, in some cases, when measurements from one satellite are measured simultaneously by two nearby GNSS receivers. Receiver multipath is more difficult to mitigate given site‐specific conditions can vary greatly and are therefore difficult to model. Whilst multipath errors vary as a function of signal frequency, carrier‐phase measurements are less affected due to their short wavelength (Hofmann‐Wellenhof et al., 2008).

Multipath models and mitigation techniques are beyond the scope of this thesis, however, the importance of locating CORS sites on flat terrain and away from reflective surfaces is critical to the technical network design of a NPI. Tiered (CORS) infrastructure guidelines developed by the ICSM PCG will be an important resource for selecting sites that minimise signal interference (Burns and Sarib, 2010). The trade‐off between optimum site location, institutional (e.g., land administration systems) and economic (e.g., market driven demand) considerations can however restrict the availability of low‐ multipath environments, particularly in urban settings, as described in Chapters 4 and 6.

3.3.7 OTHER BIASES

A number of other errors must also be considered when striving to achieve millimetre precision via GNSS, particularly for scientific applications such global sea‐level monitoring. The technical nature of these errors is beyond the scope of this thesis and readers are referred to Brown (2006), Hofmann‐ Wellenhof (2008) and Grgich (2008) for an introduction to the biases identified in Table 6.

TABLE 6: GNSS & NON‐GNSS SPECIFIC BIASES

Relativistic effects on satellite clocks, satellite orbits, signal transmissions and receiver clocks GNSS‐ Receiver and antenna offsets and antenna phase centre variation Specific Phase wind‐up effects Biases Receiver noise (e.g., thermal noise) Inter‐channel biases (e.g., between L1 and L2 and other GNSS signals) Non Atmospheric pressure loading GNSS‐ Tectonic plate motion specific Solid Earth tides Biases Ocean tide loading

Additional GNSS and non GNSS‐specific biases effecting high accuracy position solutions (particularly for Precise Point Positioning).

Two biases identified in Table 6 that occur independently of the GNSS measurement system (i.e., non GNSS‐specific) are solid earth tides and ocean tide loading. Both biases are small in magnitude (mm to cm effects on position) and result from the gravitational pull of the sun and moon acting on the Earth’s surface and oceans, respectively. Like all additional biases identified in Table 6, the contribution of these errors to the final position accuracy is greater in the absence of relative positioning techniques to mitigate their effects. The fact that the impact of these biases varies spatially suggests that globally distributed ground and space infrastructure can aid detection, modelling and monitoring of their effects. This is particularly relevant to large geographic countries such as Australia, where CORS infrastructure is not uniformly distributed, and NRTK coverage is limited (see Chapters 4 and 6).

3.3.8 USER EQUIVALENT RANGE ERROR

User Range Error (URE) was first introduced in Section 2.3.3.1 when reviewing formal SIS performance specifications for GPS, and can be further defined as the combined error estimate of satellite orbits (ephemeris data), satellite clocks, and ionospheric and tropospheric delays for code pseudoranges. The GPS SIS Performance Standard (DoD, 2008) requires a URE for each satellite during normal operating conditions (for all ages of data) of ≤7.8m (95% confidence51).

According to Hofmann‐Wellenhof (2008), the User Equivalent Range Error (UERE) is produced when independent estimates (regardless of any correlation) of multipath and equipment biases (e.g., receiver noise and antenna phase centre variations) are included with the URE. Hofmann‐Wellenhof (2008) estimate the average systematic bias and random error contribution of each parameter to the total UERE (Table 752) for a Single Point Positioning (SPP) solution (Section 3.4.1).

TABLE 7: UERE COMPONENTS

UERE Source Systematic Bias (m) Random Error (m) UERE Error (m) Ephemeris data 2.1 0.0 2.1 Satellite Clock 2.0 0.7 2.1 Ionosphere 4.0 0.5 4.0 Troposphere 0.5 0.5 0.7 Multipath 1.0 1.0 1.4 Receiver 0.5 0.2 0.5 Total UERE (m) 5.1 1.4 5.3

Systematic and random error components of UERE for code pseudoranges (adapted from Hofmann‐ Wellenhof, 2008).

Mapping the Signal‐In‐Space UERE (1‐sigma) to a positional error at the user’s location requires knowledge about satellite geometry, which is estimated using Dilution of Precision (DOP) information from the satellite navigation message. Horizontal (HDOP), Vertical (VDOP) and Geometric DOP (GDOP) are common measures that can be multiplied by the UERE to estimate the standalone accuracy of a code pseudorange position solution without any augmentation.

51 Note that the URE comparison in Figure 9 (Chapter 2.3.3.1) identifies a requirement of ≤4.0 m RMS, which derives from the same DoD (2008) performance standard but corresponds to a 1‐sigma (i.e., RMS) confidence interval in contrast to the 95% confidence interval (2‐sigma) quoted in the official standard. 52 UERE errors are the square root of the sum of the squares of each error component.

3.4 GNSS POSITIONING TECHNIQUES

Most GNSS users are accustomed to switching on their mobile phones or in‐car navigation devices to receive position and navigation information instantaneously. All GNSS receivers apply Single Point Positioning (SPP) techniques to process the code pseudoranges transmitted by each satellite, which enables positioning solutions to be computed. The SPP technique requires no additional space or ground infrastructure other than that made available through the relevant satellite positioning system(s), meaning any user across the globe can compute their location provided they can receive signals sent from the satellites. Chapter 6 provides economic evidence that GPS devices have become increasingly common and are now integrated into our everyday lives, particularly as hardware has become cheaper and smaller over time.

There are however various GNSS positioning techniques and associated products and services that improve the utility of PNT information observed from GPS and other GNSS. Common techniques include relative positioning and Precise Point Positioning (PPP) which have evolved over the preceding three decades to overcome the low accuracy (≈5‐10 m) constraints of SPP solutions. Different techniques yield different levels of integrity, reliability, availability, and efficiency for accessing and applying PNT information. Technical characteristics for three forms of GNSS positioning are identified in this Section, primarily to describe how and why the effectiveness of each technique varies with baseline length (the distance between two or more GNSS receivers) and signal type (i.e., code and/or carrier measurements). Chapter 6 analyses these technical characteristics in a unique economic context to evaluate the costs and benefits of investment in Australia’s positioning infrastructure in response to scientific and commercial demand.

3.4.1 SINGLE POINT POSITIONING

SPP determines the three‐dimensional coordinates of a single receiver and the receiver’s clock error by combining simultaneous code pseudorange measurements to at least four satellites. Code pseudoranges are first corrected for satellite orbit and clock errors and ionospheric delays using the satellite navigation message. Residual code pseudorange errors (including measurement noise and multipath) manifest in the position solution. SPP is the most basic form of GNSS positioning available in all commercial receivers, allowing fast access to lower accuracy code information. Higher quality receivers include carrier phase measurements and dual‐frequency code pseudoranges to improve SPP accuracy, particularly in a multi‐GNSS environment as described in Sections 2.3.3.5 and 2.5.

SPP is an absolute53 positioning technique where the position of a single receiver is computed with respect to the absolute position of each satellite. For example, GPS satellite coordinates are defined

53 The concept of absolute positioning is further developed in Section 3.5.

70 with respect to the World Geodetic System 1984 (WGS‐84) and SPP positions are triangulated from the absolute location of each satellite to a single receiver.

3.4.2 RELATIVE POSITIONING

Relative positioning on the other hand requires two or more receivers that observe code and/or carrier phase measurements to the same satellites to further mitigate range errors. The resulting position for one receiver is derived relative to the known location of the second receiver (typically within the coordinate system used to define the location of the second receiver).

3.4.2.1 DIFFERENTIAL GNSS

Differential GNSS (DGNSS) is a form of relative positioning. DGNSS works on the premise that two or more GNSS receivers located within close proximity will have similar (spatially correlated) errors when the same satellites are observed. If one receiver is placed over a reference point with known coordinates, the true geometric ranges between each satellite and the reference receiver can be computed and compared to the measured code pseudoranges. Any differences between the observed and computed ranges will result from the error sources described in Section 3.3. Code pseudorange corrections for each satellite‐receiver range can therefore be calculated, sent to, and applied to the pseudoranges measured by the second (rover) receiver. A reliable communication link is needed between the reference and rover(s) to communicate correction data. Ultra‐High Frequency (UHF) radios and mobile telephony (e.g., 3G ‐ Third Generation Communications) are commonly used for this purpose. Satellite communication mechanisms are also becoming more prevalent (e.g., SBAS).

DGNSS solutions still apply the SPP algorithm, but with corrected pseudoranges. DGNSS significantly reduces spatially correlated errors and can be effectively employed over 10s to 100s of kilometres. Permanent CORS sites within DGNSS networks can therefore be spaced up to 100s of kilometres apart (such as the ground networks supporting different SBAS) to deliver accuracies of 1‐2 metres with high reliability and integrity. Criteria for achieving sub‐metre accuracies using commercial DGNSS services are described in Section 4.4.6.

In the context of this thesis, DGNSS refers strictly to code‐based relative positioning. Differential positioning methodologies using carrier‐phase measurements converge to the more complex Real‐Time Kinematic (RTK) method of relative positioning (Hofmann‐Wellenhof et al., 2008) described below.

3.4.2.2 REAL‐TIME KINEMATIC (RTK)

RTK techniques are a more accurate form of differential positioning given carrier phase measurements are observed far more precisely54 than code pseudoranges. RTK techniques produce centimetre accurate positions in real‐time by employing measurement differencing (the double‐differencing technique in particular). Measurement differencing eliminates satellite and receiver clock errors; satellite orbit errors, and significantly reduces the impact of tropospheric and ionospheric disturbances. It also facilitates fast and reliable integer ambiguity resolution for each satellite‐receiver range. Residual multipath and receiver noise errors remain in the final position solution and the level of spatial correlation of the observed errors between two receivers decreases as the distance between them increases. In practice, using dual frequency receivers over single baseline (single‐base) lengths of 10‐15 km is the limit beyond which centimetre accurate positions are not achievable due to spatial decorrelation of the atmospheric errors. RTK users commonly purchase two GNSS receivers that are sold as a single‐base RTK kit.

Single‐base RTK receivers can be single or dual‐frequency (or multiple‐frequency in a multi‐GNSS environment). Using two (or more) frequencies delivers higher accuracy and efficiency by allowing enhanced mitigation of the ionospheric error (refer to Section 3.3.4). It follows that single‐base RTK products are considerably more expensive than basic SPP and DGNSS products given two geodetic grade (e.g., dual‐frequency) GNSS receivers are needed to optimise processing accuracy, efficiency and reliability. Furthermore, the Intellectual Property underpinning commercial RTK processing is highly valuable and often protected by the use of proprietary data formats to communicate RTK corrections between receivers. The need for separate or integrated communications is an additional cost. The high accuracy RTK positioning market therefore tends to be characterised by specialised users requiring centimetre accurate position information in real‐time for scientific and commercial applications. High accuracy applications tend to be localised, including those for engineering and construction, mining and precision agriculture (The Allen Consulting Group, 2008).

3.4.2.3 NETWORK REAL‐TIME KINEMATIC (NRTK)

A natural extension of single‐base RTK is to broaden positioning coverage using multiple CORS sites deployed at known locations, and then apply the Network RTK (NRTK) positioning technique.

NRTK underpins the high accuracy positioning market examined within this thesis.

It is well established that CORS infrastructure placed at 50–70 km inter‐station distances enables instantaneous three‐dimensional positioning accuracy at ±2 centimetres with 1‐sigma uncertainty using the NRTK technique (Vollath et al., 2000a, Euler et al., 2001, Rizos and Han, 2003, Janssen, 2009). NRTK coverage is identified, mapped and evaluated across Australia in Chapter 4. Institutional requirements

54 Refer to Section 3.3.1.

72 and economic drivers for delivering high accuracy positioning services are described in Chapters 4 and 6, which are related through the NPI Planning Framework in Chapter 7.

The NRTK concept is essentially the same as single‐base RTK in that measurement differencing techniques are applied to carrier phase measurements to mitigate orbit, clock and atmospheric errors, thereby producing centimetre accurate positions. The main difference is that multiple CORS sites improve error mitigation between the network stations and the rover (Figure 23). Rizos and Han (2003) recognise the improved atmospheric modelling capabilities and measurement redundancy that multiple CORS sites provide, and these improvements are reinforced by Wang et al. (2010) when testing the improved accuracy, availability, integrity and productivity (i.e., utility) that commercial NRTK packages deliver.

FIGURE 23: NRTK CONCEPT

Mobile/Radio/Satellite ≈70km CORS Communication

CORS CORS Central Processing Facility CORS

Data from multiple CORS is combined to compute NRTK corrections that are sent to users via communications devices (adapted from SmartNet Aus, 2012).

To deliver NRTK information, Figure 23 illustrates that data from each CORS must be sent to a central processing facility where it can be combined to compute common error sources across a region. These error corrections are interpolated to a user’s position within the network via a one‐way or two‐way communication mechanism, depending on the NRTK technique that is implemented. Rather than purchasing two GNSS receivers for single‐base RTK, hardware costs are reduced given only one dual‐ frequency receiver and communication device are needed by the user. However, users generally pay subscription fees to access commercial NRTK positioning services.

Data volumes received by the user differ for the two most prevalent commercial NRTK processing techniques: the Virtual Reference Station (VRS55) method (Vollath et al., 2000b, Landau et al., 2002) and the Master Auxiliary Concept (MAC56) (Euler et al., 2001, Brown et al., 2005). Janssen (2009) provides a comprehensive review of the processing strategies and communication bandwidth requirements of each. The Area Correction Parameters technique, known formally as the Flächenkorrekturparameter (FKP) (Wubbena et al., 2001) is a third method originally developed to support radio broadcasting as an alternative to mobile communications. VRS and MAC both support the use of the FKP technique. Rubinov (2013) differentiates the technical methodologies and data formats required for all three NRTK techniques.

VRS requires two‐way communications to transmit a user’s approximate location to the central processing facility, which enables network corrections to be computed within the control centre, and then returned to the user as a simplified data message that resembles a single‐base RTK solution. MAC on the other hand supports one‐way communication by allowing correction parameters to be optimised by the receiver instead of the control centre. This decentralised approach allows greater flexibility in the choice of network corrections (e.g., the number of CORS sites) that contribute to the final position solution, which can improve measurement traceability. Bandwidth requirements are however higher for MAC given the increased volume of correction data that is sent, which in turn increases the processing load for the rover. FKP is a simplified linear representation of network corrections that supports one‐ way communication and reduces bandwidth requirements. Each reference receiver transmits an individual FKP correction model in this latter case.

3.4.3 PRECISE POINT POSITIONING

PPP was originally conceived by Anderle (1976 cited in, Rizos et al., 2012). In its simplest form, PPP enables high accuracy positioning down to centimetre accuracy for a single receiver by applying additional information about the exact location and clock error of each observed satellite (Kouba and Heroux, 2001).

PPP can be interpreted as a more accurate version of SPP that utilises precise carrier‐phase measurements to solve for the absolute position of a standalone receiver. In contrast to relative positioning techniques, measurement differencing is not typically applied to mitigate spatially correlated errors and solve the integer ambiguities of the carrier phase measurements (Wubbena et al., 2001). The contribution of each error to the total range error, including GNSS and non‐GNSS specific biases (see Section 3.3.7), must therefore be mathematically modelled, which requires long observation (convergence) times ranging from minutes to hours, depending on the final accuracy requirement.

55 Developed by Trimble Navigation Ltd. (http://www.trimble.com/vrs.shtml). 56 Developed by Leica Geosystems AG (http://www.leica‐geosystems.com/).

Hence, PPP solutions are typically post‐processed once sufficient information about all major error sources is available. Dual‐frequency observations speed up convergence and improve accuracy by providing ionospheric free combinations of code and carrier phase measurements. Rizos et al. (2012) compare the technical requirements of PPP and relative positioning techniques, including a summary of the biases (refer to Table 7) that must be modelled or otherwise accounted for in PPP solutions.

3.4.3.1 REAL‐TIME PPP

In recent times, sub‐decimetre GNSS orbit information and sub‐nanosecond clock information has become available in real‐time through agencies such as the IGS (2013c), which has prompted a greater research effort towards developing Real‐Time PPP (RT‐PPP) solutions (also referred to as PPP Ambiguity Resolution). The term RT‐PPP refers to the process of applying precise orbit, clock and other error information to a single receiver in real‐time using PPP techniques, which requires a period of convergence to achieve sub‐decimetre accuracies. The term PPP‐RTK also reflects57 this process, however a subtle difference in meaning between RT‐PPP and PPP‐RTK is outlined below in the context of a NPI.

Put simply, PPP corrections model the source of each error (primarily those identified in Tables 6 and 7) that affect code and carrier phase observations recorded at the receiver. Relative positioning techniques (e.g., RTK) on the other hand model the effects of each error by combining code and carrier measurements from multiple receivers after these measurements have been observed. PPP is therefore described as a State Space Representation (SSR) given the actual state (functional and stochastic properties) of each error must be modelled and updated on a periodic basis (Wübbena et al., 2005).

On the other hand, relative positioning corrections model and eliminate the effects of these source errors by combining (differencing) spatially correlated carrier‐phase measurements over short distances once the raw signals are observed. Hence, modelling of these relative errors is referred to as Observation Space Representation (OSR), which represents the process of RTK positioning defined previously (Wübbena et al., 2005).

Applying RT‐PPP terminology; OSR mitigates the effect of errors contained within the carrier‐phase (and/or code) observations recorded at the receiver. SSR models the source of each meaning the observation itself can be corrected at the reference station without the need to combine observations from a nearby receiver. Hence, using RT‐PPP to compute SSR corrections in real‐time theoretically allows centimetre accurate positions to be derived globally without deploying CORS networks. SSR corrections can be transmitted using radio, mobile or satellite communications.

However, the time taken to quantify RT‐PPP source errors is a limiting factor given at least 20‐30 minutes of carrier‐phase observations are needed before ambiguities converge to suitably precise

57 Relevant literature is identified throughout this Section.

75 values at the centimetre‐level (Chassagne, 2012, Rizos et al., 2012). The ionosphere remains a limiting factor in the absence of CORS networks given global ionospheric error models do not provide the required accuracy for centimetre positioning without undertaking longer observation times (Huber et al., 2010). Convergence times can however be reduced in regions where infill CORS sites are available (Bisnath and Collins, 2012, Rizos et al., 2012). PPP‐RTK describes the case where additional CORS are used to model the ionosphere more accurately to facilitate ambiguity resolution. The optimum density of CORS infrastructure needed to minimise investment costs while satisfying conditions for PPP‐RTK is unknown, and is a research topic of national interest to Australia (CRCSI, 2013b). Furthermore, triple‐ frequency carrier phase measurements are also expected to extend baseline lengths through improved ionospheric modelling that helps to speed up ambiguity resolution for PPP‐RTK (Feng and Rizos, 2005).

The term PPP‐RTK has subsequently emerged to describe a hybrid solution that leverages regional networks of CORS to model PPP corrections across the same area. RT‐PPP also describes this process, but represents the case where PPP improves accuracy in real‐time regardless of whether the ambiguities are resolved. This important distinction is revisited in Chapter 6 to describe why the economic benefits of improving positioning accuracy in Australia (through a RT‐PPP enabled NPI) are not necessarily contingent on delivering access to ambiguity resolved ±2cm (95% confidence) GNSS positions anytime and anywhere. Lower accuracy augmentation without ambiguity resolution can be sufficient for some applications (e.g., LBS, maritime and aviation navigation). In other cases, ±2cm is vital to enabling the desired productivity benefits (e.g., surveying, engineering, precision agriculture). Chapters 4 and 6 explore the trade‐offs between infrastructure investment and positioning accuracy in greater detail.

To implement a RT‐PPP solution, new data formats are needed to communicate SSR messages, and receiver firmware must be designed with PPP functionality to process these corrections in real‐time. The RTCM‐SSR data standard is subsequently described in Section 3.4.4. Commercial approaches to RT‐PPP, which commonly use L‐Band communications satellites to transmit proprietary data formats, are also reviewed in Section 4.4.6.

3.4.4 DATA FORMATS

Different data formats are used to store and exchange code and carrier phase measurements for real‐ time and post processing. Commercial manufacturers develop proprietary data formats that are optimised to improve real‐time processing efficiency for their own GNSS hardware and software products, and to protect Intellectual Property for value‐added features such as data compression and quality control techniques. Rubinov et al. (2011a) examine the message structure, efficiency and bandwidth usage of common proprietary formats developed by leading GNSS manufacturers.

Open data standards have also been developed to facilitate data exchange and promote interoperability and compatibility between different GNSS receivers, satellite positioning systems and applications.

Receiver Independent Exchange (RINEX58) format is an industry standard used for data exchange and is supported by most commercial grade receivers. RINEX is an ASCII59 format that is regularly updated to account for new and modernised signals, meaning its large size would require a large amount of bandwidth that is unsuitable for real‐time applications (Yan, 2006). Instead, real‐time DGNSS and RTK data formats and transfer protocols are published by the Radio Technical Commission for Maritime Services (RTCM) Special Committee number 104 (SC‐10460). .

RTCM version 3.1 (RTCM, 2006) is the latest industry standard used to format NRTK61 corrections, and supports the VRS, MAC and FKP techniques. Network Transfer of RTCM via Internet Protocol (NTRIP) casters are used to transport the RTCM messages from the network to a receiver. Three components are therefore necessary to deliver a NRTK solution via the internet: a compact data format (e.g., RTCM 3.1); a reliable data protocol (e.g., NTRIP) that determines how the information is sent over the internet; and a communication device that provides access to the internet (e.g., a portable modem) (Heo et al., 2009). Given the accuracy of a NRTK solution depends on the time taken for correction information to arrive at the rover (latency), more compact data formats are generally desired to preserve bandwidth and improve performance. RTCM 3.1 provides a significant reduction in bandwidth requirements from previous versions and has the flexibility to incorporate multi‐GNSS signals.

In light of RT‐PPP developments, RTCM‐SSR corrections were developed by the RTCM SSR Working Group and officially adopted as an RTCM Standard in March 2011 (Caissy et al., 2012). RTCM‐SSR is used to disseminate IGS orbit and clock corrections via NTRIP. To implement a RT‐PPP solution however, receiver firmware must be compatible with RTCM‐SSR messages, and PPP algorithms must be developed to apply these absolute corrections within a single receiver as an independent process from relative positioning techniques. At the time of writing, no commercial manufacturers have incorporated PPP functionality using RTCM‐SSR messages.

A new format known as Multiple Signal Messages (MSM) is now being developed by RTCM‐SC104 to enable interoperability among different GNSS receiver types by standardising observations from multiple GNSS (Boriskin et al., 2012). RTCM‐MSM is effectively the ‘next step’ needed to consolidate raw observations, and SSR and NRTK messages into one generic format accessible via NTRIP. MSM messages form a key component of the IGS Multi‐GNSS Experiment (MGEX) and associated IGS Real‐Time Service (IGS‐RTS), and a complete RINEX format compatible with the MSM format has been designed (Caissy et al., 2012). RTCM‐MSM is not officially published as an RTCM standard at the time of writing.

58 RINEX was originally developed by the Astronomical Institute of Bern. RINEX 3.02 is the latest version (IGS and RTCM, 2013). 59 American Standard Code for Information Interchange. 60 RINEX is the shared responsibility of RTCM‐SC104 and the IGS (IGS and RTCM, 2013). 61 RTCM version 2.0 only supported single‐base RTK, which is why the simplified FKP technique was developed to transfer linear network corrections using this earlier version.

The IGS provides free and open access to NTRIP and all RTCM formats to encourage their widespread adoption. GNSS manufacturers that incorporate this functionality into their receiver firmware will have direct access to standardised real‐time GNSS corrections from a global network of CORS. Leica Geosystems is planning to include the HP‐MSM format in its next version of Leica Viva firmware (D Dixon 2013 pers. Comm., 13 June). Details on proprietary data formats developed by manufacturers to differentiate their products and services are provided in Section 6.2.4, which reviews the economic implications of open and proprietary formats.

3.5 THE GEOSPATIAL REFERENCE SYSTEM (GRS)

In its simplest form, the GRS is a coordinate system to which all position and spatial data is referenced (Johnston and Morgan, 2010). A GRS is often referred to as a reference frame or geodetic datum. National GRS (NGRS) are commonly derived from a global GRS (e.g., the ITRF), which allows spatial data (e.g., GNSS information) from across the world to be referenced to, and compared in the same reference system. All GRS must be monitored and updated to account for changes in the dynamic Earth system such as crustal deformation.

The instrumentation used to establish a GRS includes a range of geodetic infrastructure such as Very Long Baseline Interferometry (VLBI), Satellite Laser Ranging (SLR), Lunar Laser Ranging (LLR), Doppler Orbitography and Radio Positioning Integrated by Satellite (DORIS), and GNSS (AuScope Geospatial Team, 2008).

Prior to the advent of GNSS, terrestrial measurement techniques were a primary means of accessing the GRS for day‐to‐day positioning activities such as surveying and engineering. Angle and distance measurements between physical ground survey marks remain a common form of terrestrial positioning today, which is why ground marks are distributed with varying density across Australia. The technical criteria used to define the quality (e.g., stability) of these ground marks forms part of the physical site characteristics underpinning Tiered classifications (Section 3.2.1.2) for CORS infrastructure today.

GNSS has revolutionised the way in which a GRS is realised and monitored, and the way in which users access a GRS to reference and compare their position information.

Appendix A details the science of establishing a GRS by describing the processes used for datum definition and datum realisation, including the need for a reference ellipsoid to approximate the Earth’s size and shape, or a region of it. The geoid is also introduced as a surface related to the Earth’s gravity field meaning it can be used as a zero‐height reference surface for mapping real world processes such as the direction of water‐flow.

3.5.1 POSITION ACCURACY

By establishing a coordinate system in which the unique position of any point can be described, a GRS is used to determine the absolute (or ‘point’) position of an object (e.g., the location of a satellite or CORS). Any uncertainty in the absolute coordinates of an object (e.g., a ground survey mark) will manifest in the coordinates of a second object whose location is derived with respect to the first (e.g., using relative positioning techniques). Any uncertainty (e.g., GNSS errors, angular errors) in the measurements used to connect the second object to the first will add (relative uncertainty) to the absolute uncertainty of the second object when referenced in the same datum, as described in Section 3.5.2.2 below.

According to Gauss (1809 cited in, Fraser, 2007) all measurements are only an approximation of the true value, meaning all measurements are subject to the influence of error:

But since all our measurements and observations are nothing more than approximations to the truth, the same must be true of all calculations resting upon them, and the highest aim of all computations made concerning concrete phenomena must be to approximate, as nearly as practicable, to the truth. (Gauss, 1809)

It follows from Section 3.3 that systematic (e.g., clock bias), random (e.g., clock instability) and in some cases gross errors (e.g., user error) are implicit in all GNSS measurements. Modern positioning techniques such as NRTK can however be used to observe GNSS measurements very precisely (e.g., at the cm‐level); in some cases even more precisely than the original measurements that were used to establish the underlying measurement reference frame (datum). The resulting coordinates derived from the newer and more precise measurements in this case could conflict with coordinates computed for the same points in the original (less precise) datum adjustment. In light of these issues concerning datum accuracy and measurement precision, Johnston and Morgan (2010) identify two distinct criteria for evaluating positional accuracy:

i. The user’s ability to connect to the datum (i.e., position accuracy depends on the precision of the chosen measurement technique);

ii. The inherent accuracy of the datum itself (i.e., position accuracy is constrained by the accuracy of the underlying datum).

Criterion (i) implies that a user cannot derive coordinates with the same accuracy as the underlying datum if their chosen measurement technique cannot deliver the same (or higher) accuracy as the datum itself. Criterion (ii) on the other hand implies that no matter how precise the user’s chosen measurement technique, derived coordinates cannot be more accurate than the datum to which they

79 are connected. For example, Dawson and Woods (2010) report the absolute uncertainty of GDA94 coordinates at 30 mm horizontal and 50 mm vertical (at the 95% confidence level) for CORS sites in the Australian Fiducial Network (AFN) (see Section 3.5.2), therefore limiting the inherent accuracy of all other geodetic infrastructure connected to this datum through the AFN.

These criteria raise four important datum considerations to be evaluated in the context of a NPI: coordinate traceability, relative versus absolute accuracy, the difference between global and regional reference frames, and the need for a modernised datum in Australia. All four topics are related by the objective of enabling a uniform high accuracy positioning capability accuracy across Australia, and the implications of each are described below for Australia’s NGRS.

3.5.2 AUSTRALIA’S NGRS

Australia’s NGRS is the Geocentric Datum of Australia 1994 (GDA94). Johnston and Morgan (2010) describe Australia’s NGRS as a combination of the infrastructure, data, software and knowledge needed to establish all aspects of a coordinate datum, including the tools, utilities, standards and recommended practices for accessing and using the datum. GDA94 is the foundation for all positioning applications, and therefore all spatial data in Australia.

Previous datums include the Australian Geodetic Datum 1966 (AGD66) and AGD84, neither of which were established using GNSS measurements. AGD84 significantly densified and extended AGD66 and included SLR and VLBI measurements with terrestrial measurements. AGD66 and AGD 84 were both purely horizontal datums, and were optimised to fit the geoid across the Australian continent as opposed to being referenced to the Earth’s centre of mass by fitting the geoid on a global basis. Earth‐ centred or geocentric datums enable global compatibility with satellite navigation systems such as GPS. The transition to a globally compatible datum in Australia came with the introduction of GDA94, which connected physical ground marks to the ITRF using GPS measurements from the Australian Fiducial Network (AFN) and Australian National Network (ANN) (Steed and Luton, 2000).

The AFN (Figure 24) consists of eight permanent GNSS CORS spread across Australia with coordinates fixed to ITRF1992.0 at epoch 1994.0 to establish GDA94. The ANN consists of approximately 80 ground marks that were observed using GNSS measurements to link each site to the AFN. The AFN is comprised of high stability Tier 1 CORS, whilst ANN sites were typically observed at Tier 2 standard. It is noted from Section 3.2.1.2 that lower grade Tier 3 sites owned by jurisdictional governments and industry providers are deployed as infill sites to access the datum as opposed to defining it. This well‐defined hierarchy of infrastructure standards enhances coordinate traceability within a GRS, as described in Section 3.5.2.1. Australia’s NGRS is now managed through the Australian Regional GNSS Network (ARGN) comprising 35 permanent Tier 1 CORS.

FIGURE 24: AFN & ANN STATIONS

Geographic distribution of primary AFN and ANN sites used to establish Australia’s GDA94 (GA, 2013)

3.5.2.1 COORDINATE TRACEABILITY

Coordinate traceability is the process of verifying the uncertainty of a coordinate with respect to a datum. In Australia, the uncertainty of a coordinate is formally verified in accordance with the National Measurement Act 1960 and Regulation 13 of the National Measurement Regulations 1999. GA is a legal metrology authority appointed under the Act to provide this legal chain of traceability, which they achieve by issuing a Regulation 13 Certificate that displays a station coordinate and the uncertainty of that coordinate with respect to GDA94 (Geoscience Australia, 2013c).

Government and industry providers of CORS infrastructure can apply for Regulation 13 Certificates to report their station coordinates relative to the national standard. Certification requires a rigorous geodetic adjustment incorporating data from elements of the ARGN combined with GNSS observations recorded by the CORS. There is no obligation to undertake certification in Australia. However, many service providers identify technical (e.g., datum compatibility) and economic benefits from undertaking certification as a free public service to market the link between their infrastructure and the NGRS. Certification is however only one step for ensuring service providers and users are confident in the absolute and relative accuracy of their coordinates.

3.5.2.2 RELATIVE VERSUS ABSOLUTE ACCURACY

Regulation 13 certification applies to the CORS coordinates, not to coordinates derived from these certified CORS. This gives the service operator and its user’s confidence that by connecting to a certified CORS, their coordinates will be derived from a reliable starting point. But it says nothing (other than by implication) about the process used thereafter, or the quality of the derived coordinates. Hence, derived coordinates have local or ‘relative’ uncertainty (ICSM, 2007), in addition to the absolute positional uncertainty that manifests at a CORS site relative to the datum itself. This important distinction between absolute and relative accuracy raises technical and institutional (Hale et al., 2007) considerations for users who seek legal traceability in their derived coordinates.

From a technical standpoint, criterion (i) identified by Johnston and Morgan (2010) implies that a number of empirical factors influence the relative uncertainty of a derived coordinate, which include the length of observation time, the type of GNSS measurements observed (e.g., single or dual‐frequency), environmental (e.g., sky visibility) and atmospheric (e.g., the level of solar activity) conditions, and the rigour of the processing algorithm itself (e.g., multipath mitigation, outlier detection). These empirical variations are the reason that certification procedures such as those defined for Regulation 13 are needed to standardise observation conditions and infrastructure quality (e.g., Tiers) in the first place.

To ensure users can independently manage the uncertainty of derived coordinates when connecting to a certified CORS, the ICSM (2013) publish Standards for the Australian Survey Network (SP162). The total uncertainty for a derived coordinate is a statistical combination (i.e., propagation of variances) of absolute and relative uncertainties. This notion is reaffirmed by Johnston and Morgan (2010) who state that users are often mislead into believing that the internal (relative) precision of the positioning technique being used to compute the coordinates is an estimator of the absolute accuracy. But the internal precision is only a measure of relative uncertainty with respect to a CORS site or ground mark.

A combination of technical (e.g., datum compatibility), institutional (e.g., legal certification) and economic drivers63 (costs/benefits) for quantifying the absolute and relative accuracy of coordinates in Australia lends weight to technical arguments by Dawson and Woods (2010) for modernising Australia’s current datum, particularly as absolute positioning techniques such as RT‐PPP evolve in a multi‐GNSS environment, as described in the following Sections.

3.5.2.3 GLOBAL AND REGIONAL REFERENCE FRAMES

GDA94 is a static datum meaning GDA94 coordinates remain fixed to values as they were on 1st January 1994. In a global context however, the coordinate axes of GDA94 and more recent versions of ITRF no longer coincide (in absolute terms) due to plate tectonics.

62 Version 2.0 was released in October 2013 and supersedes Version 1.7 (ICSM, 2007). 63 Detailed in Chapter 6.

ITRF is a dynamic datum that accounts for plate tectonics and intra‐plate movements globally, meaning the absolute locations of AFN sites have shifted64 by upwards of 1m from GDA94 when compared with the most recent realisation of ITRF65. Tectonic plate motion in Australia is approximately 7cm per year. This total shift has not caused issues for most applications to date in Australia given relative positioning techniques are predominantly applied on a local scale within a highly stable tectonic plate, and without connecting to sites outside of Australia. Furthermore, datum transformations parameters (Dawson and Woods, 2010) between GDA94 and the ITRF have been developed for applications requiring millimetre level accuracy in a Global Reference Frame (GRF) such as ITRF.

Australia is not unique in this regard as many countries manage static datums that are linked to the ITRF such as the North American Datum of 1983 (NAD83) which services the US and Canada. It follows that most users are accustomed to accessing and applying position information that has been recorded in a Regional Reference Frame (RRF) such as GDA. On the other hand, scientific users and geodetic agencies that study the entire Earth system must maintain a stable and compatible link between GRF and RRF.

Haasdyk and Janssen (2011) observe that various commercial providers are increasingly adopting a GRF as their primary means of reporting coordinate information within their PNT services, such as the OmniSTAR66 service. In Australia, GA manages the free online GPS processing service known as AUSPOS which reports location in GDA94 (a RRF) and ITRF08 (a GRF). AUSPOS is used to post‐process ‘static’ GPS observations recorded at any location across Australia, or worldwide.

Returning to the positioning techniques described in Section 3.4.1, orbit positions (ephemerides) and clock products such as those computed by the IGS are also computed in a GRF. For example, the WGS84 datum (most recently updated in 2004) is the GPS standard, and IGb08 is the most recent datum adopted by the IGS. Hence, WGS84 and IGb08 are both dynamic GRF that are regularly updated with respect to ITRF. Whilst global orbit and clock products have little effect on positioning accuracy when using relative positioning techniques, PPP users working in a RRF commonly derive their position in a GRF, and then apply a‐posteriori (i.e., after‐the‐fact) transformations from the GRF to their RRF (Huisman et al., 2012). This a‐posteriori method is a ‘User‐side’ approach as illustrated in Figure 25. In recent times however, organisations such as the IGS have started supplying their orbit and clock products in RRF to ensure they are readily useable for all types of applications. This ‘Server‐side’ approach illustrated in Figure 25 eliminates the need for user input given orbit and clock products themselves are delivered to users in the required RRF to compute the position.

64 According to Dawson & Woods (2010) the metre level difference between GDA94 and ITRF at the present time is a consequence of: tectonic motion of the rigid Australian Plate, which is approximately 70 mm yr‐1 in the North‐ North‐East direction; differences between ITRF1992 and later ITRF realisations, which are caused by modelling and input data differences; station velocities of 5 mm yr‐1; and residual intra‐plate, regional and local deformation, which is generally less than 1 mm yr‐1 in the horizontal components. 65 ITRF2008 is soon to be superseded by ITRF 2013. 66 OmniSTAR is owned by Trimble Navigation Ltd (http://www.omnistar.com/Home.aspx).

FIGURE 25: SERVICE‐SIDE & USER‐SIDE REFERENCE FRAME TRANSFORMATIONS

(b)

(a)

User‐side (a) point transformation from GRF (e.g., ITRF) to RRF (e.g., GDA94) versus Server‐side (b) orbit and clock transformation from GRF to RRF for point computation (Huisman et al., 2012).

Huisman et al (2012) provide evidence that, in Australia, the Server‐side approach can yield errors of up to 80 mm relative to the User‐side approach due to scale differences between the RRF (e.g., GDA94) and the GRF (e.g., ITRF). Huisman et al (2012) test a method of applying a‐posteriori scale factors that significantly reduce the errors observed in the standard Server‐side approach and require limited (if any) input from the user. In light of Section 3.4.3, both transformation approaches are important considerations for managing the datum and subsequent accuracy of position information derived using PPP techniques.

PPP requires space and ground infrastructure whose coordinates must be accurately determined in the same reference frame in order to computer the user’s position. The accuracy and consistency of the datum itself, whether global or regional in nature, will therefore influence the level of uncertainty that manifests in the computed position. Hence, the accuracy of a satellite positioning system is intrinsically linked to the accuracy of its datum.

Users can transform coordinates between the satellite positioning system’s datum, and the GRF or RRF that is adopted within their NGRS. However, the dynamic Earth system is increasingly driving the need to align national datums with dynamic datums such as ITRF to support absolute positioning techniques such as PPP. At present, a user can observe two different coordinates for the same point with respect to GDA94 and the ITRF. Modernising Australia’s datum to become dynamic through time is however no easy feat given the technical and institutional extent to which the nation’s static datum is embedded in legacy datasets, legal frameworks and professional services. Technical drivers described in the following

Section 3.5.2.4 are however evolving in response to public and commercial demand for high accuracy and high integrity positioning capabilities.

Economic drivers explored throughout this thesis, and Chapter 6 specifically, may provide the most compelling case for moving to a truly three‐dimensional dynamic datum to remain competitive in a multi‐GNSS future.

3.5.2.4 A MODERNISED DATUM FOR AUSTRALIA

To ensure Australia manages a NGRS that is consistent with international standards in a multi‐GNSS future, five major drivers are identified by Dawson and Woods (2010) for modernising Australia’s datum:

1. The current accuracy of GDA94 coordinates is not consistent67 between AFN sites when compared with more recent ITRF adjustments for the same datum (determined by transforming modern ITRF adjustments back to GDA94). Nation‐wide positioning at the 1cm level is not therefore possible at present;

2. The absolute coordinate uncertainty of all geodetic and other positioning infrastructures in Australia is currently limited by the inherent uncertainty68 of GDA94;

3. The increasing divergence between GDA94 and modern realisations of the ITRF is upwards of 1m. Transformations are needed to relate both datums which can introduce absolute coordinate errors along with small discrepancies in orientation due to the rotation of the Australian plate since 1994. A modernised datum will limit the need for transformations.

4. Densification of CORS infrastructure through scientific initiatives such as AuScope described in Section 4.2.1.2 present new opportunities for densifying the recognised value‐standard for position (i.e., AFN sites). Over 100 stations can now be used to improve access to, and the integrity of legally traceable positions in Australia. The NPI concept set out in this thesis could significantly increase these station numbers.

5. Ongoing deformation of the Australian crust due to geophysical, anthropogenic and hydrological processes means a static model does not account for internal changes in the NGRS, which should be reported through coordinate updates and revised measures of coordinate uncertainty.

3.5.2.5 ASIA‐PACIFIC REFERENCE FRAME (APREF)

Beyond its responsibility to manage the NGRS, and its contribution to the next generation datum project within the CRCSI (2013a), GA is leading an international project to create and maintain an accurate

67 Up to 12 mm horizontal and 51 mm vertical for ITRF2008. 68 30 mm horizontal and 50 mm vertical at a 95% confidence level.

85 geodetic framework across the Asia‐Pacific. The project, known as APREF, is addressing the growing positioning needs of industry, scientific programs and the general public by offering a consistent, dynamic and easily accessible reference frame (Geoscience Australia, 2011a). APREF addresses technical and organisational issues associated with the definition, realisation and maintenance of a regional reference frame to achieve greater alignment with leading international examples across Europe and the Americas.

The project aims to increase data sharing by aggregating GNSS data from independently managed CORS sites, which will assist development of an authoritative source for station coordinates and velocities for high quality geodetic stations located in the Asia‐Pacific. The National GNSS CORS Infrastructure (NGCI) web map introduced in Section 4.3.1 is a tool developed through this research to record and display authoritative coordinate datasets such as APREF.

3.6 CONCLUSION

CORS infrastructure is strategically placed for applying relative and PPP techniques that enhance the accuracy of standalone GNSS services. The chosen technique often depends on the specified service performance criteria for the application. These criteria help to determine the infrastructure Tier that best suits the application, which reflects the type and quality of technical and physical CORS resources that are needed to establish a positioning infrastructure.

Different positioning techniques are more cost‐effective for specific applications, and the availability of these techniques depends on the availability of supporting positioning infrastructure. As a general rule, integrating more space and ground infrastructure within a positioning infrastructure leads to better positioning information being delivered with greater confidence. Each augmentation helps to model and mitigate the variety of GNSS error sources described within this Chapter. Increasing access to CORS infrastructure therefore increases the accuracy and coverage of augmented positioning services that are made available to users. Increased access also contributes to managing a country’s NGRS, which establishes a common and authoritative reference for all spatial data, and must be updated and maintained to account for the dynamic Earth system.

CHAPTER 4 EVOLUTION OF AUSTRALIA’S CORS INFRASTRUCTURE & POSITIONING SERVICES

EVOLUTION OF AUSTRALIA’S CORS INFRASTRUCTURE & POSITIONING SERVICES

4.1 INTRODUCTION

The first three Chapters of this thesis have provided an institutional review of international space policies, and described the technical space and ground infrastructures that are used to observe, process and distribute PNT information in response to policy and business drivers. In Australia, CORS infrastructure has been identified as the primary means of enhancing the accuracy of GNSS position information as opposed to investing in space assets. This Chapter provides evidence of where and why governments and industry deploy CORS infrastructure in Australia by addressing two inter‐related research questions:

1. In what locations do governments and industry deploy CORS infrastructure across Australia?

2. How do governments and industry fund CORS infrastructure?

Both questions are used to evaluate the supply of CORS infrastructure and associated positioning services in Australia, which reflects the level of access that users have to high accuracy position information. Supply criteria include the location of CORS infrastructure and the funding and licensing arrangements for data sharing and distribution. International examples of CORS infrastructure development and global collaboration initiatives are also provided for comparison.

4.1.1 RESEARCH RATIONALE

The rationale (Figure 26) behind Chapter 4 is to progress from a purely technical description of the physical characteristics and functions of CORS resources and positioning infrastructure (Chapter 3), to a discussion on the scientific (technical), policy (institutional) and commercial (economic) drivers that influence where this infrastructure is deployed in Australia. The overarching public good and commercial drivers identified throughout this thesis reveal that different positioning activities have different technical, institutional and economic requirements, which influence the type (e.g., Tier) of CORS that can be deployed to support these functions.

This Chapter reviews policy frameworks established at Federal, State and Territory levels of government in Australia that specify technical and institutional standards and guidelines for deploying and accessing CORS infrastructure. The market driven response from industry to license government and privately owned infrastructure and deploy additional infill CORS, is explored. Figure 26 highlights the technical and institutional relationships examined within this Chapter.

Chapter 5 then introduces the NPI concept and Chapter 6 develops a unique economic context for relating technical and institutional drivers and barriers to entry for deploying CORS infrastructure, which builds clarity around the cost‐benefit decisions that influence investment in positioning infrastructure.

FIGURE 26: CHAPTER 4 RATIONALE

Rationale for Chapter 4 which identifies technical, institutional and commercial drivers for government and industry investment in Australia’s CORS infrastructure.

4.2 GOVERNMENT & INDUSTRY CORS INFRASTRUCTURE

This Section identifies the location of government and industry owned CORS infrastructure across Australia that is used to access the NGRS and enable positioning services. The evolution of policy and business frameworks that guide the operation and management of this infrastructure are identified and evaluated.

4.2.1 GOVERNMENT INFRASTRUCTURE & SERVICE PROVIDERS

A common argument used to justify investment in geodetic infrastructure worldwide is that governments have a responsibility to establish, maintain and provide access to the NGRS as a public good (Rizos, 2007). Geodetic infrastructure includes the SLR, VLBI, LLR and DORIS technology introduced in Section 3.5, along with the ground marks, CORS, data, software, tools, utilities, knowledge, standards and recommended practices for accessing and using the datum.

As technology has evolved and become cheaper over time, government owned CORS networks have been densified beyond the sparse distribution (hundreds of kilometres) typically needed for geodetic purposes. Governments in the United Kingdom (Ordnance Survey, 2012), Ireland (Martin and McGovern, 2012), Germany (Stronk and Wegener, 2005), Sweden (Jamtnas et al., 2010), Japan (Sagiya, 2004), Turkey (Yildirim et al., 2011) and New Zealand (Blick and Sarib, 2010) have enabled nationwide high‐ accuracy (i.e., NRTK) real‐time positioning services (either directly, or in downstream commercial

89 markets) that support government and business activities. These services are commonly delivered to users in partnership with industry providers who also deploy additional CORS in under‐serviced regions to expand service coverage. These foreign networks typically contain between 150 and 250 CORS, as detailed in Section 4.4.

Geographically, Australia is at least 20 times larger than each of these countries, implying that at least 20 times the number of CORS sites is required to achieve comparable high accuracy positioning coverage on a national scale. This level of investment has not occurred in Australia given the country’s large land mass, low population density, and a lack of national governance for maximising the utility of existing positioning infrastructure and services (Hausler and Collier, 2013a). These challenges are reviewed within this Section to evaluate the current supply of CORS infrastructure in Australia.

4.2.1.1 INSTITUTIONAL ROLES & RESPONSIBILITIES

Australia’s constitution follows the Westminster system of government and law that was inherited from the United Kingdom after colonisation in 1788. Administrative responsibilities are divided between a Federal Government that deals with national policy and legislation, and six State and two Territory parliaments that govern the geographic regions illustrated in Figure 27.

FIGURE 27: AUSTRALIAN STATES & TERRITORIES

Map of Australian States and Territories.

Federal, State and Territory governments are responsible for funding and managing CORS sites as part of their positioning infrastructure. Each jurisdiction has a significant degree of autonomy in developing ‘spatial’ policies that articulate roles and responsibilities for deploying, accessing and managing CORS infrastructure and broader positioning frameworks (Hale, 2007). The extent to which geodetic CORS infrastructure supports internal government services and generates public good benefits therefore varies between jurisdictions. It should be noted that not every jurisdiction has built CORS infrastructure; some have opted out of this ‘responsibility’ in favour of allowing market forces to drive private sector investment. In such cases, the geodetic infrastructure in these jurisdictions is the traditional ground (survey) mark network.

It follows that no uniform ‘spatial’ policy exists in Australia for deploying and managing positioning infrastructure. Independent ownership and operations led Australia’s Federal government in the first instance to deploy sparse (i.e., spaced at hundreds of kilometres) CORS infrastructure through the AFN to define, monitor and provide access to the region’s geodetic reference frame as a public good. The progression from a sparse, ‘passive’ (post‐mission data processing) geodetic CORS network in the 1990s, to the higher‐density (i.e., spaced at tens of kilometres) ‘active’ (real‐time data processing) networks made available by Federal, State and Territory governments today, is summarised by Zhang et al. (2007), Rizos (2007) and Hausler and Collier (2013a).

Increased demand for higher‐density networks reflects global trends in the countries identified in Section 4.4 towards enabling public and commercial high accuracy positioning goods and services nationally. Demand is often driven by new applications beyond the traditional spatial sector (GSA, 2012), and a growing market for high accuracy positioning services has been identified in Australia through various economic (The Allen Consulting Group, 2008) and industry studies (Bowman, 2008, Position One Consulting, 2008, McPhee, 2009, ASC, 2012). Global and national trends towards ubiquitous positioning have thus prompted densification and technical upgrades in physical ground infrastructure (i.e., CORS). These upgrades are needed to ensure the integrity, accuracy, reliability and compatibility of the nation’s geodetic framework is sufficient for society’s present and future positioning needs (Blick, 2010).

Hausler and Collier (2013a) find that some jurisdictions in Australia have been more successful than others at justifying additional investment in CORS for public good and commercial purposes. In weighing up the costs and benefits of providing CORS infrastructure, not all jurisdictions have reached the same conclusion, meaning some States have built CORS and some have not, leading to a disparate spatial distribution on a national basis. Hence, demand for high accuracy positioning services has not been sufficient to justify NRTK coverage nationally. Further investigation is undertaken within this thesis to identify where existing Federal, State, Territory and industry CORS infrastructure and service coverage has been, and should be supplied in Australia.

The location and ownership properties of government and industry funded CORS are analysed spatially and statistically in the following Sections as indicators of where and why consumer demand is strongest in these regions.

4.2.1.2 FEDERAL INFRASTRUCTURE (ARGN & AUSCOPE)

At a Federal government level, GA is responsible for managing the NGRS, primarily through the ARGN, within the broader AuScope network. ARGN contains 35 geodetic CORS, 21 of which are on mainland Australia (including Tasmania); three on Antarctica, one on Macquarie Island and another 10 spread across the South Pacific islands. ARGN establishes the geodetic datum for spatial data infrastructure in Australia, which facilitates measurement and monitoring of Earth’s processes, including crustal motion and sea level rise (Geoscience Australia, 2011a). Data from this network contributes to the IGS.

AuScope is a $42.8 million project that was funded under the National Collaborative Research Infrastructure Strategy (NCRIS) of the Australian Government’s former Department of Innovation, Industry Science and Research (DIISR69). The key driver for AuScope is to understand the structure and evolution of the Australian continent, and to mimic the goals of the Global Geodetic Observing System (GGOS) and EarthScope (see Sections 4.4.3.1 and 4.4.7) to align with and facilitate use of ITRF in Australia (Johnston and Morgan, 2010). The Geospatial component (AuScope Geospatial Team, 2008) of AuScope was allocated $15.4 million of NCRIS funding, and a further $4.5 million from Federal, State and Territory governments and several universities. These funds were used to procure and/or build the following geodetic infrastructure:

• Three new 12m VLBI telescopes;

• A VLBI observation correlation facility at Curtin University;

• Four new gravity meters (One Microg FG5 absolute gravimeter and three gPhone Earth Tide Meters);

• A laser power upgrade at the Mt Stromlo SLR observatory in Canberra;

• A mobile SLR campaign at Burnie, Tasmania;

• Approximately 100 new GNSS CORS.

AuScope CORS sites are jointly funded by the Federal Government, with some co‐investment from State and Territory governments who in turn are responsible for the ongoing operational and maintenance costs for sites located in their jurisdictions (see Table 8). A total of 102 sites were funded in total as of August 2013, with 86 of these operational and the remainder due for construction. Four of these

69 Now the Department of Industry.

92 proposed sites are funded as part of the Australian Geophysical Observing System (AGOS) program that contributed an additional $23 million to the AuScope initiative in 2010 (AuScope, 2012). Once AuScope is fully deployed, a total of 123 CORS of Tier 2 quality or higher will be publicly available when combined with the 21 existing mainland (including Tasmania) ARGN sites.

Station spacing ranges from 200 km or less in some regions to over 500 km in other regions, meaning the AuScope network is not designed for NRTK processing. This sparse, non‐uniform distribution of geodetic infrastructure reflects GA’s primary responsibility of managing the geodetic framework as opposed to operating real‐time positioning services. Each CORS site does however provide a real‐time RTCM‐3.1 data stream that is free to access, and some States and Territories have funded upgrades to telecommunications resources (e.g., dual‐communications for higher bandwidth) for integration into their own real‐time positioning services (e.g., GPSnet). Data made freely available from the AuScope network provides research and commercial opportunities for testing and implementing emerging positioning techniques such as RT‐PPP using a sparse CORS network.

The Federal Government’s Australian Maritime Safety Authority (AMSA) also provides a Differential GPS (DGPS) network that comprises 16 remote CORS (see Figure 28) distributed around the Australian coastline. This network is used for maritime navigation, not geodetic purposes. AMSA is responsible for the provision of navigational services for ocean and coastal navigation across the Australian jurisdiction and delivers a decimetre accurate (95% confidence) positioning capability within selected coastal regions. While these code‐based differential corrections are made freely available, the fundamental observation data from this network is not publicly available.

FIGURE 28: AMSA CORS NETWORK

Location of AMSA’s DGPS CORS sites and approximate maritime positioning coverage enabled by each CORS (decimetre accuracy).

4.2.1.3 STATE AND TERRITORY INFRASTRUCTURE

State and Territory funding for CORS preceded the AuScope roll‐out in some jurisdictions given QLD, VIC and NSW were early adopters of commercial DGNSS and RTK technologies from the mid‐1990s. A brief summary of CORS network developments in each State and Territory is provided below. The number of CORS sites estimated for each State and Territory is approximate only given network expansions, site changes, and site removals are difficult to monitor without a centralised and authoritative source of CORS network information. In response, the NGCI database and web map were developed through this research and are introduced in Section 4.3 to consolidate the information presented below.

Victoria: The Victorian Government’s Department of Environment and Primary Industries (DEPI) owns and operates the Vicmap Position‐GPSnetTM service (DEPI, 2013b), which consists of approximately 104 CORS (including 10 AuScope and one ARGN sites), plus 11 CORS shared across the border with NSW, and one in SA. Network construction began in 1994 and State‐wide NRTK70 service coverage has been available since 2012. Victoria is the only Australian State to have achieved full, jurisdictional coverage. GPSnet is managed using a ‘cooperative’ model that brings together contributors and partners from all levels of government, industry, academia and the community to establish and host CORS sites, and therefore gain mutual benefits through free access to the network (Hale and Ramm, 2007).

FIGURE 29: GPSNET VICTORIA

GPSnet stations in VIC, including shared sites from NSW and SA (DEPI, 2013b).

70 This research assumes that networks capable of delivering NRTK corrections are also capable of delivering single‐ base RTK and DGNSS corrections, as well as providing access to raw GNSS carrier‐phase and code‐pseudorange information recorded by the CORS. These data products are commonly output from commercial processing software that is purchased by governments to operate and deliver positioning services.

New South Wales (NSW): The Land and Property Information (LPI) Division within the NSW Government’s Department of Finance and Services owns and operates CORSnet‐NSW, which consists of approximately 102 CORS (including 13 AuScope and two ARGN sites) and additional sites shared across the Victorian (13) and ACT (4) borders. LPI’s first CORS dates back to 1992 before a seven‐station Sydney Network (SydNET) was deployed in 2004 (Janssen et al., 2010). The CORSnet‐NSW rebranding and expansion from SydNET commenced in 2009 and is ongoing. Areal NRTK coverage across the State at August 2013 is estimated by LPI at 40.3% and aggregate coverage at a 50 km radius from each CORS site is estimated at 62.5%. Accuracy can vary from centimetres to metres at this radius depending on the adopted positioning technique.

FIGURE 30: CORSNET NSW

CORSnet NSW stations (LPI, 2013).

Queensland (QLD): The QLD Government’s Department of Natural Resources and Mines (DNRM) operates the 11‐station SunPOZ network to deliver NRTK corrections to the south‐east corner of the State. Additionally, 20 AuScope sites and two ARGN sites are distributed across the State. Ergon Energy, a QLD Government‐owned electricity distribution company recently proposed an additional 600 CORS sites to be prioritised at existing Ergon asset locations as opposed to being optimised for uniform NRTK coverage. The outcome of Ergon’s proposal has not been decided at the time of writing, however the business case submitted to the QLD Government is a prime example of the value that CORS infrastructure can provide beyond traditional geodetic applications. Ergon are particularly interested in deploying CORS for precise time synchronisation by co‐locating each CORS with utility assets (e.g., electricity substations).

FIGURE 31: SUNPOZ QLD AND PROPOSED ERGON ENERGY NETWORK

SunPOZ

A potential design presented by Higgins (2012) for the Ergon CORS network, which would incorporate DNRM’s SunPOZ network. Yellow hatching represents potential NRTK coverage.

Western Australia (WA): Landgate, WA’s Land Information Authority, co‐funds 28 AuScope sites across the State. No additional investment has been provided by Landgate to densify CORS infrastructure or operate a NRTK positioning service.

South Australia (SA): No direct government investment has been committed by the Land Services Group (LSG) within the Department of Planning, Transport and Infrastructure (DPTI) beyond co‐investment for 10 CORS sites funded through the AuScope project.

Tasmania (TAS): In 2010/2011 the TAS Government undertook planning to construct approximately 20 CORS across the State as part of the Innovative Farming Practices Project (DPIPWE, 2012). This funding was however discontinued in June 2011 due to budget restrictions. The Department of Primary Industries, Parks, Water & Environment (DPIPWE) co‐funds four CORS sites through AuScope.

Northern Territory (NT): The NT Government’s Department of Lands and Planning (DLP) currently operate five stations across the Territory and co‐funds an additional 17 AuScope CORS sites.

Australian Capital Territory (ACT): The Planning and Land Authority (PLA) within the ACT’s Environment and Sustainable Development Directorate (ESDD) fund one CORS site and partner with GA (also based in the ACT) for the AuScope program.

Table 8 shows the number of CORS in Australia for each jurisdiction as of August 2013. The government agencies identified previously that independently fund ‘other CORS’ (i.e., non‐AuScope sites) are also the ‘Responsible Authorities’ (RAs) for AuScope. Location details have been obtained through consultation with each RA and have been compiled since 2010 as an ongoing contribution to governments, industry, academia and the broader user community through this research. Figure 32 maps the approximate geographic location of government owned CORS from Table 8.

TABLE 8: STATE & TERRITORY CORS

AuScope Responsible Other Total Jurisdiction ARGN GA RA Authority (RA) CORS CORS Victoria (VIC) 1 4 6 DEPI 93* 104* New South Wales (NSW) 2 6 7 DFS ‐ LPI 97* 112* Australian Capital Territory (ACT) 2 0 0 ESDD ‐ PLA 1 3 Queensland (QLD) 2 11 9 DNRM 11 33 Northern Territory (NT) 3 8 9 DLP 0 20 Western Australia (WA) 7 14 14 Landgate 0 35 South Australia (SA) 2 9 1 DPTI ‐ LSG 0 12 Tasmania (TAS) 2 4 0 DPIPWE 0 6 Total Government CORS 21 56 46 202 325

Approximate number of CORS located in each jurisdiction across Australia (excluding islands) at August 2013 (adapted from Hausler and Collier, 2013a). AuScope‐RA sites, including proposed CORS, are funded in‐kind by each jurisdiction. ARGN sites are funded by GA. Note that each agency is responsible for the operational and maintenance costs of all AuScope sites in their jurisdiction once deployed (i.e., GA + RA sites). *Shared sites from other States/Territories are not included in ‘Total CORS’. VIC contains 15 additional sites from NSW, whilst NSW contains 13 additional sites from Victoria and four from the ACT.

FIGURE 32: STATE & TERRITORY CORS

Location of government funded CORS infrastructure across Australia. Ownership is differentiated by colour for Federal (ARGN); co‐funded (AuScope); and State‐owned (VIC‐GPSnet, NSW‐CORSnet, QLD‐SunPOZ) CORS. Symbol size is arbitrary and does not represent coverage extent (adapted from Hausler and Collier, 2013a).

4.2.2 POSITIONING SERVICES

In the context of this thesis, a positioning service refers to the computation and delivery of real‐time GNSS data corrections to users to improve the accuracy of standalone GNSS positioning. This definition is not limited to high accuracy NRTK corrections, given some providers specialise in single‐base RTK, DGNSS or PPP corrections. The term high accuracy positioning services is used to qualify a NRTK or equivalent service that delivers ±2cm accuracy in real‐time (at the 95% confidence level). CORSnet‐NSW and GPSnet are high accuracy positioning services. Post processed and non‐GNSS positioning services (e.g., Locata) are not evaluated in the following Sections.

4.2.2.1 SERVICE PROVIDERS

Any organisation or individual that operates a real‐time positioning service (e.g., GPSnet) is termed a Service Provider (SP) in this thesis. Industry SPs (detailed in Section 4.2.4) are often established as subsidiary or partner companies of GNSS manufacturers, including Leica Geosystems who partner with C.R. Kennedy and Co. to run SmartNet Australia (C.R.Kennedy, 2013); Topcon Positioning Systems Inc.

98 who partner with Position Partners to run AllDayRTK (Position Partners, 2013); and Trimble Navigation Ltd. who own OmniSTAR CORS Tasmania (Ultimate Positioning, 2013).

Government SPs in Australia purchase network processing software that is developed and sold commercially by GNSS manufacturers. All three government SPs in Australia use the VRS3Net software developed by Trimble (Trimble, 2013b). Whilst network processing software is optimised for a specific brand of receiver using proprietary data formats, most GNSS manufacturers also stream open data formats such as RTCM‐3.1 from their receivers. Open data formats allow SPs to integrate data from different brands of receiver.

4.2.2.2 DATA SERVICE PROVIDERS

The Victorian Spatial Council (VSC) defines a Data Service Provider (DSP) as any individual or organisation (typically a private company) that does not use, enhance or modify a dataset in any way (VSC, 2010b), but distributes the data, typically for profit. In other words, the service offered by a DSP is to distribute data as opposed to producing the data (e.g., NRTK corrections). For example, the VIC Government on‐sells data subscriptions from its GPSnet service to multiple DSPs. All users of the GPSnet service must sign a Distribution Access License Agreement (DALA) with the State of VIC, meaning each customer of the DSP must also accept the terms and conditions of this agreement (see Figures 33 and 34). Agricultural dealers are a prime example of DSPs that bundle subscriptions for positioning services with the sale of a tractor to offer complete ‘turn‐key’ (i.e., ready to use) solutions. SPs typically partner with multiple DSPs to distribute and therefore increase the size and diversity of their user market.

4.2.2.3 VALUE ADDED RESELLERS

The VSC (2010b) defines a VAR as any individual or organisation (typically a private company) that is licensed to enhance, combine and resell these data. VARs license data from third‐party SPs and individual owners of CORS to process and resell this data as part of their own positioning service. Data licensing allows any SP to extend or densify service coverage without the cost burden of deploying physical CORS infrastructure. It follows that most industry SPs do not own all CORS infrastructure within their network; they are VARs of data provided by third‐party SPs and individual owners of CORS (e.g., a local GNSS equipment distributor). VAR Agreements are signed between the primary SP71 and the VAR to specify liabilities, Intellectual Property rights, sub‐licensing conditions, fees and warranties for accessing the data (VSC, 2010b). For GPSnet in VIC, end users sign an End User Licence Agreement (EULA) with the VAR, which reflects the terms and conditions set out in the VAR Agreement between the primary SP (GPSnet) and VAR (VSC, 2010b). The VIC Government’s EULA incorporates the terms and conditions of the DALA described previously (see Figures 33 and 34).

71 A ‘primary SP’ is defined as the SP from which data is licensed (i.e., by a third‐party SP or DSP).

There is no uniform data licensing agreement for VARs in Australia given each government and industry SP negotiates access and distribution rights independently. For example, local distributors of GNSS equipment (e.g., C.R. Kennedy) in Australia often deploy CORS for commercial projects and provide exclusive access to a SP in return for access to the SP’s positioning service. Individual owners of one or multiple CORS can also earn money by licensing their data to SPs and VARs (SmartNet Aus, 2013). VAR Agreements typically allow the third‐party SP (i.e., the VAR) to integrate and resell this data. However, some VARs are limited to distributing data as a DSP rather than accessing their source data. For example, prior to October 2013, CORSnet‐NSW imposed data licensing agreements that prohibited VARs from accessing raw data streams. Industry SPs were limited to on‐selling data corrections as DSPs or ‘Authorised Resellers’ (Position Partners, 2013) on behalf of CORSnet‐NSW (i.e., the primary SP). Wholesale access to CORSnet‐NSW’s source data was granted in October 2013.

The VIC Government’s DEPI has licensed wholesale access to raw data streams from all sites within the GPSnet network for several years now. Industry SPs integrate data from GPSnet to deliver value‐added and competitive positioning services. DEPI implements VAR Agreements, DALAs and EULAs (see Section 4.2.5 for wholesale and retail examples) that determine how this data can be redistributed by third‐ party SPs and DSPs (VSC, 2010b). These policies can be written to limit industry SPs to re‐distributing RINEX data as opposed to on‐selling real‐time RTCM‐3.1 data streams.

Figure 33 illustrates the licensing and distribution supply chain that government and industry SPs and DSPs use to target consumers in the market for high accuracy positioning services. Wholesale and retail business models that are used to earn commercial revenue across this supply chain are identified in Section 4.2.5.

100

FIGURE 33: CORS LICENSING & DISTRIBUTION ARRANGEMENTS

Licensing and distribution supply chain for positioning services in Australia. ‘Infrastructure’ can be owned by governments, industry or private consumers. SPs deliver ‘value‐added positioning services’ by deploying CORS infrastructure and by licensing source data from third‐party SPs and owners of CORS through ‘VAR Agreements’. Some private users choose to purchase and manage their own positioning services directly. DSPs distribute data on behalf of a SP subject to the terms and conditions of the Distribution Access Licence Agreement (DALA). End User Licence Agreements (EULAs) between a SP and a user incorporate the terms and conditions of the DALA, such as that for the VIC Government’s GPSnet service.

4.2.2.4 DATA CUSTODIANS

Custodianship is a key concept pertaining to the collection, storage and maintenance of data. A broader definition of data custodians is firstly provided to acknowledge that custodianship is important for any type of data, not just position information. The Australian Government’s National Statistical Service (NSS72) defines data custodians as:

“...agencies responsible for managing the use, disclosure and protection of source data used in a statistical data integration project. Data custodians collect and hold information on behalf of a data provider (defined as an individual, household, business or other organisation which supplies data either for statistical or administrative purposes). The role of data custodians may also extend to producing source data, in addition to their role as a holder of datasets.” (Australian Government, 2013c)

72 NSS is a community of government agencies led by the Australian Bureau of Statistics (ABS).

101

It’s useful to compare the definition of custodianship provided by the VSC:

“Through the Custodianship Program, an organisation acknowledges that it is the single authoritative source for a dataset. It agrees to take appropriate care in the collection, storage and maintenance of the information.” (VSC, 2010a)

Combining these definitions provides insight into the roles, rights and responsibilities of a data custodian. Three key terms are reviewed in the context of positioning services: source data; data providers; and integration. ‘Source data’ represents the raw GNSS data (e.g., real‐time RTCM‐3.1 data) that are recorded from a CORS. ‘Data providers’ are the individuals and organisations that own each CORS. ‘Integration’ implies that source data from multiple data providers can be coordinated into a single authoritative dataset. Data custodians therefore collect, store and maintain this source data, and specify rights pertaining to the use, disclosure (i.e., distribution) and protection of this data, such as the rights specified in a VAR Agreement.

Custodianship helps to understand why VAR Agreements, EULAs and DALAs are needed to protect the ownership and use of source data for high accuracy positioning services, as illustrated in Figure 34. For example, GPSnet is the data custodian for all CORS sites within its network. A third‐party SP that licenses source data from GPSnet will sign a VAR Agreement subject to the terms and conditions specified by GPSnet as the data custodian, including any limits on re‐distributing source data. The same concept applies to industry SPs who protect access to the CORS that they own. However, industry SPs often license and integrate source data from third‐party data providers (e.g., a farmer or local equipment distributor). In line with both definitions above, the industry SP will typically collect, store, maintain, use, disclose and protect source data on behalf of the data provider subject to the VAR Agreement between the two parties (the same arrangement applies to GPSnet in some instances through ‘cooperative’ hosting arrangements). In most cases in Australia industry SPs negotiate the right to resell this data by paying money to the data provider and/or providing them with free positioning services.

Critically, the two definitions above do not imply that a data custodian must operate a positioning service. The NSS definition states that a data custodian manages source data (i.e., raw data) on behalf of a data provider, and their role may extend to producing this source data. Hence, any organisation that collects, stores, maintains, uses, discloses and protects its own source data and/or that of a third‐party provider is a data custodian.

102

FIGURE 34: DATA CUSTODIAN ARRANGEMENTS

Data custodians collect, store and maintain source data from CORS. Data custodians include third‐party owners (e.g., a farmer) of a CORS (green); SPs (blue) that function as data custodians (e.g., SmartNet Aus) on behalf of a third‐party data provider (green); and SPs (purple) that own the CORS infrastructure (purple) within their network (e.g., GPSnet) and license this data to third‐party SPs (blue) using VAR Agreements.

For example, GA upholds its geodetic responsibility by functioning as a data custodian for collecting and distributing RINEX data from the ARGN and AuScope networks for post‐processing. GA implements a Data Access Policy (i.e., a VAR Agreement) that allows any user to access this RINEX data free of charge. GA also functions as a data custodian for real‐time (e.g., RTCM‐3.1 data streams) source data from the ARGN, but assigns custodial responsibilities for real‐time AuScope data to State and Territory governments that maintain these sites (Geoscience Australia, 2013b). Hence, any SP can access real‐ time source data from the ARGN sites free of charge. However, GA’s Data Access Policy does not extend its custodial responsibilities to managing the performance of any third‐party positioning service that integrates real‐time data from ARGN. For example, the quality of the geodetic data collected by GA to define and maintain the geodetic datum is the responsibility of GA as the data custodian. However, the quality of position information that is referenced to the geodetic datum using a real‐time positioning service is the responsibility of the SP that computes this data (refer to Section 3.5.2.2). SPs implement EULAs that specify their performance responsibilities to the user.

4.2.2.5 SERVICE LEVEL MANAGEMENT

Differentiating and enforcing custodial responsibilities and service performance responsibilities across the positioning service supply chain requires knowledge of Service Level Management (SLM). In simple terms, SLM procedures are used to establish, monitor, report and improve service performance in response to user expectations (Wustenhoff, 2002b). In addition to the rights and responsibilities that are negotiated for accessing and distributing data through VAR Agreements, SLM criteria proposed within this thesis include performance metrics such as service uptime, data completeness, service availability and position accuracy, all of which are enforceable via Service Level Agreements (SLAs). SLAs should be negotiated between data custodians and SPs; between a primary SP and VAR; and between SPs and users. SLM procedures as a general concept aren’t well defined for positioning services in Australia

103

(Hausler and Collier, 2013b) compared with those for ICT and telecommunications industries; an important driver for developing a NPI which is addressed in Chapters 5, 6 and 7.

The remainder of this Chapter builds technical, institutional and economic context for examining (in Chapters 5 and 6) why the roles and responsibilities of data custodians, primary SPs, VARs (i.e., third‐ party SPs) and DSPs are important considerations for improving access to CORS infrastructure through a NPI.

4.2.3 COMPETITIVE NEUTRALITY

In light of the CORS infrastructure resources identified in Section 3.2.1.1, the costs to governments and industry that own CORS infrastructure and function as SPs must be higher than the costs of managing CORS infrastructure for geodetic purposes alone (e.g., as a data custodian). This logic implies that government SPs either justify all expenditure based on public good benefits alone, or develop alternative business models that attract other sources of public and/or commercial funding. The geodetic agency Land Information New Zealand (LINZ) is an example of the former case given the NZ Government’s primary justification for infrastructure investment is to monitor crustal‐deformation (Blick and Sarib, 2010). Whilst LINZ uses this infrastructure to offer geophysical services, they act as the data custodian for industry SPs who provide commercial positioning services to the public. These positioning services are used by LINZ for internal geodetic purposes. GA also functions as a data custodian on geodetic grounds alone.

VIC, NSW and QLD on the other hand leverage their traditional geodetic responsibilities as data custodians to also function as commercial SPs. In order to offset (partially or fully) ongoing operational and maintenance costs, government SPs establish a revenue stream by selling subscriptions to their positioning services. Government SPs must however operate on a cost‐neutral (non‐profit) basis according to competitive neutrality guidelines (Commonwealth of Australia, 2004), where all revenue generated from the service is allocated to funding ongoing operational and maintenance costs (Cranenbroek et al., 2006, Hale et al., 2006, Higgins, 2008).

4.2.4 INDUSTRY INFRASTRUCTURE & SERVICE PROVIDERS

Identifying the location of CORS infrastructure deployed by industry service providers in Australia helps to determine where demand is strongest, and where technical and economic issues from duplication have occurred. The following SPs are the leading providers of NRTK or equivalent high accuracy positioning services.

104

SmartNet Australia: SmartNet Aus is a joint venture between the company Leica Geosystems73, a leading manufacturer of GNSS hardware and software, and the Australian company C.R.Kennedy and Co. (C.R.Kennedy, 2013), a national importer and distributor of surveying and other equipment with exclusive rights to Leica products. SmartNet Aus offer a subscription‐based service for accessing data corrections that have been computed by licensing real‐time source data from governments and other industry SPs across Australia.

SmartNet Aus currently integrates over 150 privately funded CORS (i.e., in addition to government‐ owned infrastructure) across Australia, the majority of which are used to compute NRTK corrections. Approximately 40 of these sites were recently funded by the Fitzroy Basin Authority (FBA) who commissioned the development of a CORS network along the central‐eastern coast of QLD. SmartNet Aus was awarded the contract to manage data from these sites to deliver positioning services that assist broad acre cropping enterprises and horticulturalists to improve their efficiency, and reduce the amount of pesticides and fertilisers reaching the Great Barrier Reef. Importantly, whilst SmartNet Aus is the data custodian for these sites, funding for the FBA network was provided through the Australian Government’s Reef Rescue Program (Australian Government, 2013b, FBA, 2013).

Differentiating government and industry ownership is therefore important for identifying the downstream benefits of public good investments, which is further explored when mapping high accuracy positioning coverage in Section 4.3 and evaluating public good benefits in Chapter 6.

SmartNet Aus uses Leica Geosystem’s GNSS Spider Suite (Leica Geosystems, 2011) of network software, including GNSS Spider, SpiderWeb and GNSS SpiderQC74. The GNSS Spider Suite is purchased and implemented by governments and industry SPs from around the world including the US, UK, Germany, Italy, Sweden, Denmark and New Zealand.

AllDayRTK: The AllDayRTK positioning service is owned and operated by the Australian company Position Partners who provide positioning and machine control solutions for civil engineering projects (Position Partners, 2011). Position Partners is a national distributor for the global company Topcon Positioning Systems Inc. (Topcon, 2013) which manufactures GNSS hardware and software amongst other positioning products.

Position Partners license data streams from SPs across the country, whilst deploying additional CORS in regions of high demand, particularly for engineering and construction projects.

RTKnetwest: RTKnetwest, formerly known as GPSNET PERTH, is a NRTK service in WA that is privately owned and operated by the surveying company JBA Surveys (RTKnetwest, 2013). RTKnetwest currently

73 Owned by the Swedish company Hexagon Group. 74 Spider Quality Control.

105 contains 24 CORS primarily located in the south‐west of the State within and around Perth, and the company sells subscriptions direct to consumers.

OmniSTAR CORS Tasmania: The company Ultimate Positioning is a national distributor of GNSS equipment and software for the global GNSS manufacturer Trimble which operates the global DGNSS satellite‐based positioning service known as OmniSTAR (see Section 4.4.6.1). OmniSTAR CORS Tasmania is a NRTK positioning service managed locally by Ultimate Positioning that contains approximately 17 CORS and leverages existing OmniSTAR processing and delivery systems to distribute corrections to users (Ultimate Positioning, 2013).

Global CORS: The privately owned company Global CORS also delivered high accuracy corrections by licensing data streams across Australia before its service was decommissioned in July 2013 due to a lack of funding and user uptake. Global CORS developed in‐house network processing software known as Checkpoint CORS and deployed several infill CORS around urban regions of SA, however limited literature is available on the processing methodologies and the associated performance of Checkpoint CORS (Rubinov et al., 2011b).

Many users who require access to high accuracy PNT information have also invested in their own single‐ base RTK products, some of which are fixed in location for specific applications, whilst others can be operated on a project‐by‐project basis across different geographic regions. Whilst single‐base RTK can be a valuable option in some instances (i.e., in the absence of a nearby CORS network), such an approach can lead to considerable overinvestment if high accuracy service coverage is already available from surrounding government and industry networks. Single‐base RTK products can also be limited by proprietary data formats that restrict access to third‐party users who own a different brand of receiver. The ad‐hoc use of multiple terrestrial radio frequencies also places additional pressure on the allocation of radio spectrum, and can lead to confusion when multiple users establish independent base stations for different applications in the same geographic region (i.e., different corrections are sent on the same frequencies).

Figure 35 maps the approximate location of CORS provided by data custodians from industry in Australia. Third‐party SPs (VARs) that license data from these sites are not identified. Figure 36 compares the location of CORS provided by data custodians from government and industry. A substantial amount of single‐base infrastructure owned by industry and private consumers remains unidentified in Figures 35 and 36 as a result of uncoordinated deployment between governments and industry (ASC, 2012). For example, Hale (2007) identifies the company GPSag as a specialised agricultural dealer that has established approximately 50 CORS sites on an ad hoc basis across Australia to support precision farming applications. GPSag sites aren’t identified in Figure 35.

106

FIGURE 35: INDUSTRY CORS

Sample of CORS owned by industry SPs in Australia.

FIGURE 36: GOVERNMENT & INDUSTRY CORS

Simplified map comparing the location of CORS managed by data custodians from governments (Figure 32) and industry (Figure 35). Individual government and industry SPs are combined into single layers to generalise the private market’s response to consumer demand where government investment is absent.

107

Fifty‐four percent of CORS are owned by government in Figure 36. Approximately 40 industry sites that are managed by SmartNet Aus were however funded through government investment allocated to the FBA, which theoretically increases the percentage of government funded sites to over 60%. Whilst this finding implies that governments have contributed more investment than industry, some studies (The Allen Consulting Group, 2008, Lateral Economics, 2009) estimate that upwards of 3000 CORS sites exist across Australia . Many of these sites remain unidentified as they are funded through private investment and operate independent (i.e., they are single‐base RTK sites) of the positioning services identified in this Section. In the hypothetical case that 3000 sites do exist, government investment would account for less than 11% of total investment based on findings from this study. A conservative estimate of 1000 CORS sites in total would equate to roughly 32.5% of sites being funded by government.

Chapter 5 reviews these findings in an economic context to explain why unidentified sites are likely to be located where SPs already offer high accuracy service coverage; why this duplication can lead to economic inefficiencies through over‐investment; and why governments and industry should coordinate future investment in order to capture this ‘additional’ demand that has led to duplicated investment.

4.2.5 WHOLESALE AND RETAIL DISTRIBUTION

Early work by Hale (2007) broadly introduces wholesale and retail distribution concepts for supplying positioning services. This Section defines how and why real‐time source data and correction products are accessed through wholesale and retail distribution channels in Australia’s high accuracy positioning market. Comparisons are made with Australia’s telecommunications industry.

As a general concept, wholesale distribution refers to the bulk purchase of a product by an organisation or ‘retailer’. The retailer sells individual units of the product to consumers to earn profit. Put simply, retailers purchase from a wholesaler and sell to consumers. Wholesale purchases are typically cheaper on a per unit basis given the retailer must cover additional costs such as rent, employees, taxes, breakage and advertising in order to earn profit from consumers.

4.2.5.1 NATIONAL BROADBAND NETWORK

A modern example of a government company that supplies access to data products using a wholesale distribution model is the Australian Government’s National Broadband Network Co Limited (NBN Co, 2012). The NBN is a national infrastructure project originally valued at over $40 billion that will enable access to high‐speed internet anywhere across the country. However, a user does not contact NBN Co in order to access its network. The NBN Co business model is to sell wholesale access by certifying third‐ party wholesale providers through its Wholesale Broadband Agreement (WBA). Wholesale service providers then distribute a range of products and services to retail clients such as Internet Service Providers (ISPs).

108

For example, a user wishing to access the NBN will purchase a product from an ISP such as a specific quantity of data at a specific price. The ISP can supply this product having licensed access to the NBN network from a wholesale service provider that has been certified by NBN Co (the data custodian). The NBN Co Product and Pricing Overview for Service Providers states that:

“By ensuring that the NBN Co network is both wholesale only and open access, we are enabling a level of retail competition in downstream telecommunications markets. NBN Co will not compete with Service Providers’ customers in providing services to End Users and is required to provide non‐discriminatory access to all Service Providers” (NBN Co, 2011)

4.2.5.2 HIGH ACCURACY POSITIONING SERVICES

Applying the NBN analogy to the market for positioning services, NBN Co represents a data custodian with contractual SLM responsibilities (e.g., service uptime). According to the previous quote, SPs and DSPs can be classified as ‘Service Providers’ that deliver retail access to positioning services.

In the positioning market, data custodians provide access to real‐time source data as a wholesale product which SPs purchase, process and sell as corrected data in the retail market (see Figure 37). Data custodians that provide free access to their source data such as GA also implement wholesale agreements that govern the use, disclosure and protection of the data (e.g., GA’s Data Access Policy). Chapter 6 explores business drivers underpinning the public good investment model adopted by GA as opposed to the commercial models described within this Section.

Another commercial benefit of operating a positioning service is that a SP who sells retail access to data corrections can also function as a wholesale provider by selling source data to third‐parties, subject to VAR Agreements. This model is not unique given various retail telecommunications providers such as Optus (Optus, 2013) and Telstra (Telstra Wholesale, 2013) also operate wholesale divisions to provide third‐party access to their networks. For example, the company Virgin Mobile provides telecommunications coverage by licensing wholesale access to the Optus network (Virgin Mobile, 2013). Optus is the primary data custodian in this case.

At the wholesale level, data licensing between data providers and SPs, and between SPs themselves has become an increasing trend over the past five years in order to densify and extend service coverage and to earn revenue. Data licensing can remove the cost burden of deploying and physically managing CORS infrastructure, and results in more consistent standards of infrastructure quality (i.e., Tiers) when the same CORS nodes are integrated within multiple positioning services (Hausler and Collier, 2013b). Data licensing therefore helps to limit duplication of CORS infrastructure and typically requires open (public) data standards such as RTCM‐3.1 to stream real‐time data to multiple service providers.

109

FIGURE 37: WHOLESALE & RETAIL DISTRIBUTION

SPs access raw data streams (e.g., RTCM‐3.1) in several ways: deploy their own CORS; purchase wholesale access from third‐party data custodians; obtain free access from data made available to the public (e.g., GA). Data custodians earn revenue from selling wholesale access to source data. SPs and DSPs earn revenue from selling raw (e.g., RINEX) and corrected data (e.g., NRTK corrections) to users. DSPs collect royalties from distributing positioning services to their broader client base on behalf of a SP. Figure 37 has been adapted from work by Hausler and Collier (2013b).

In light of Section 3.4.4 however, manufacturers continue to develop proprietary formats to differentiate their products and services with unique features such as faster processing techniques and additional quality control measures. Proprietary formats are a method of controlling pricing and access to information technologies, but can also restrict compatibility and interoperability with other GNSS hardware and software. Hence, proprietary formats can lead to further duplication where data access cannot be enabled or agreed between service providers for commercial reasons. Economic drivers for open and proprietary formats are further explored in Section 6.2.4. Indeed, SPs will continue to duplicate infrastructure where the benefits of deploying additional CORS outweighs potential cost savings that data licensing can provide.

At the retail level, government and industry SPs earn revenue from selling data subscriptions to consumers either directly or through affiliated DSPs (see Figure 37). The cost of retail subscriptions is often differentiated based on the type (raw or corrected GNSS data), quality (accuracy, reliability, coverage) and the quantity purchased (Hausler and Collier, 2013b), as discussed in Chapter 6. As a general guide, NRTK subscriptions for existing SPs in Australia in 2013 ranged from $2000 to $4000, and different SPs often charge similar prices and offer different levels of service coverage.

DSPs choose to retail subscription services that value‐add to their own products. DSPs therefore act as a data broker for SPs, which shifts their responsibilities towards client management. Given SPs typically have responsibility for operational and maintenance tasks, difficulties arise when DSPs (instead of the SP

110 who operates the network) are the first point of call for technical support, but don’t have the necessary resources for accessing and validating the data (Hausler and Collier, 2013b).

4.3 MAPPING CORS INFRASTRUCTURE & HIGH ACCURACY SERVICE COVERAGE

Most SPs who license access to data managed by a third‐party data custodian will advertise the CORS site as part of their own network. This leads to information duplication when multiple SPs advertise the same CORS in their individual networks. CORS sites should therefore be classified according to the primary data custodian who collects, stores and manages the real‐time source data. For example, GPSnet is the primary data custodian for sites within its network regardless of who licenses its data. GA is the primary data custodian for ARGN sites regardless of which industry SPs access this source data. These classification concepts have been developed through this research and are further refined through the NGCI web map and database introduced below.

4.3.1 NATIONAL GNSS CORS INFRASTRUCTURE (NGCI) WEB MAP

The National GNSS CORS Infrastructure (NGCI) web map has been developed as an interactive online tool to visualise and review a range of infrastructure locations and metadata (Hausler and Collier, 2013b). Previously, there was no centralised record of Federal, State/Territory and industry operated CORS infrastructure across Australia (AuScope Geospatial Team, 2008). Location metadata is critical for identifying where to optimally deploy future CORS to facilitate the growth and development of a NPI.

The web map provides a direct response to the NPI Policy (2010) produced by ANZLIC, which recommends developing a national plan defining existing and planned infrastructure locations. The web map also supports the ASC’s Strategic Plan for GNSS (2012) to identify and coordinate the activities of government and private sector CORS providers as part of a whole‐of‐nation approach for developing a sustainable, multi‐GNSS enabled NPI.

The NGCI web map combines a range of CORS metadata made public by government and commercial SPs and offers a standardised format for displaying this metadata. However, data custodians have no obligation to publish the locations of their infrastructure, meaning a large amount of privately owned single‐base infrastructure remains unidentified.

111

FIGURE 38: NATIONAL GNSS CORS INFRASTRUCTURE (NGCI) WEB MAP

Snapshot of the NGCI75 web map available at: .

Government and industry SPs can use the web map to guide the deployment and upgrade of their infrastructure by identifying regions where infill sites of a particular quality (Tier) are required to further support development of a NPI. Planned developments include interactive functionality that will allow each service provider to update stations details, and provide tools to query inter‐station distances and determine which services operate within a specified proximity. By providing a standardised format and centralised record for displaying CORS metadata, the web map is intended to establish a dynamic database for managing and updating station details in real‐time.

4.3.1.1 NGCI DATABASE

Rather than listing a CORS multiple times for different SPs (Figure 39a), the NGCI76 classifies each CORS node according to the primary data custodian who owns the site. Metadata for a specific node is used to identify third‐party SPs that license access from the primary custodian (Figure 39b). Existing online resources that use a similar metadata approach, such as GA’s APREF (Geoscience Australia, 2013a) and the National Geospatial Reference System (NGRS) web map (Geoscience Australia, 2011b), contain metadata for government sites only.

75 The prototype NGCI web map has been developed by ThinkSpatial Pty Ltd, a partner of the CRCSI. The web map is hosted on GeoServer; an open source software written in Java that is designed to enhance interoperability when sharing and editing geospatial data (GeoServer, 2011). The data is served as Geo Java Script Object Notation (GeoJSON) through a Web Feature Service (WFS) interface, to allow geographic features to be directly and easily parsed into JavaScript (J Romeril 2011, pers comm, 6 July). JavaScript libraries used for the web map include: Ext JS, OpenLayers, and GeoExt. 76 Data is still being populated in this format for the NGCI database.

112

FIGURE 39A AND 39B: NGCI METADATA

Figure 39a. Current situation ‐ duplicated Figure 39b. From the NGCI web map and metadata for a single CORS that is accessed database ‐ one node identifies the primary by multiple SPs. data custodian & third‐party SPs.

Metadata for existing and planned CORS sites has been compiled using authoritative information from government and company websites, XML databases, RINEX files, text files and Microsoft EXCEL spreadsheets. Common information was extracted from each data source according to specific metadata fields defined within the internationally recognised IGS Site Information Form77.

Providing the NGCI web map as a public resource is intended to expose this research to a broader audience of SPs and users to encourage their participation. Public feedback also helps to identify where duplicated metadata exists within the web map due to a lack of public information on infrastructure ownership. The prototype web map has been welcomed by government and private managers of CORS infrastructure as a valuable tool to guide the deployment of future infrastructure, and to assist the development and communication of future positioning standards and guidelines. Private sector feedback has encouraged use of the website as a mission planning tool for identifying the closest station or network within a specific region, and for reviewing the services that are offered by each. Section 4.3.3 presents a case study highlighting these benefits.

4.3.2 HIGH ACCURACY GNSS SERVICE COVERAGE

The following analysis uses data from the NGCI database to map (Figure 40) and therefore estimate (Table 9) the percentage of area within each State and Territory where access to one or more high accuracy positioning services is available. Combined national service coverage is then estimated to identify and evaluate what proportion of this total coverage is supplied by government and industry (Table 10). The purpose of this spatial and statistical analysis is to identify where most investment in high accuracy positioning services has been allocated to date. Chapter 6 establishes a unique economic interpretation of this spatial evidence to demonstrate why public and commercial demand has driven higher investment in these regions.

77Available at: .

113

Figure 40 and Table 9 were compiled by Hausler and Collier (2013a) using location details published by each SP as of January 201378, and these findings represent the first attempt to map (collectively) and quantify high accuracy positioning coverage across Australia. The methodology and measurement criteria used to create Figure 40 are summarised in Appendix B.

FIGURE 40: AUSTRALIAN NRTK COVERAGE

Geographic service coverage79 contributed by government and industry SPs. Coverage from industry services is outlined to identify overlapping coverage with government SPs (Hausler & Collier, 2013a).

The two most important findings from Figure 40 are that high accuracy positioning coverage is not national, and that no one supplier provides positioning services across all areas shown in Figure 40. This second finding is illustrated by the fact that no single polygon covers the entire service region. Independently operated government and industry services are differentiated based on colour, meaning a separate data subscription is needed to access raw or corrected data streams within different coloured polygons. Significant coverage overlap occurs in some jurisdictions given industry providers typically license data streams from existing SPs to avoid the cost of deploying and operating additional

78 Table 9 and Figure 36 do not project the additional coverage that will be provided by SmartNet Aus across the FBA region in QLD once this network is complete. Any additional sites that DSPs in Australia have licensed or deployed since January 2013 are not included. 79 Note in Figure 40 that SPs who license data from GPSnet sometimes publish coverage regions that differ from GPSnet. This may result from different processing methodologies and strategies for optimising network performance.

114 infrastructure. Licensing contracts generally require royalty payments to be made to the relevant infrastructure provider in order to cover ongoing operational costs, as described in Section 4.3.2.2.

A user can therefore choose from multiple high accuracy positioning services where overlapping coverage occurs, which encourages SPs to compete on the cost of subscriptions and the quality of service they offer. Industry providers extend service coverage by deploying CORS infrastructure adjacent to existing SPs from whom they can license raw data streams to consolidate service coverage. In some regions, industry funded infrastructure is the only source of positioning coverage, as demonstrated in Figure 40.

In light of these findings, Table 9 estimates the percentage of NRTK coverage that is enabled by each SP in each State and Territory of Australia. Table 9 also identifies the NRTK software that is used by each SP to compute high accuracy correction data. Each software package is typically optimised to process proprietary data formats that are linked to a specific brand of GNSS receiver. Whilst open data standards such as RTCM‐3.1 are enabled in most NRTK processing software, manufacturers and software developers promote ‘value‐added’ benefits from using proprietary data formats, which can be used to optimise the length of the data message and the efficiency with which the data is processed.

TABLE 9: GOVERNMENT & INDUSTRY NRTK COVERAGE

NRTK Apx. % State Apx. % Aust. Service Provider (SP) State Software covered covered GPSnet Trimble VRS VIC 100.0 3.0 Government CORSnet NSW Trimble VRS NSW 28.7 3.0 SunPOZ Trimble VRS QLD 0.9 0.2 VIC 84.5 NSW 0.2 QLD 0.6 AlldayRTK TopNet VRS WA 1.6 SA 1.6 TOTAL 3.4 VIC 94.6 Industry NSW 2.0 Leica QLD 2.5 SmartNet Aus SpiderNet WA 0.1 SA 4.5 TOTAL 4.2 RTKnetwest Trimble VRS WA 0.4 0.0 OmniSTAR CORS TAS Trimble VRS TAS 51.0 0.4

Government and industry SPs that offer NRTK coverage with positioning accuracy of ± 2cm (95% confidence).

In light of the licensing arrangements described throughout Section 4.2.2, it is difficult to identify in Table 9 who owns the physical CORS infrastructure that is leveraged by multiple SPs to enable high accuracy positioning coverage. For example, the VIC Government’s GPSnet service enables 100% service

115 coverage across the State, whilst SmartNet Aus also enables 94.6% coverage across the same region. Clearly a substantial amount of wholesale data licensing occurs in VIC given GPSnet owns the vast majority of CORS infrastructure within this State. Furthermore, the SmartNet Aus business model is based solely on licensing data. It’s therefore critical to understand why data licensing is a key technical, institutional and economic driver for enabling access to CORS infrastructure, in line with the research hypothesis.

4.3.2.1 DATA LICENSING ARRANGEMENTS

Industry SPs in VIC provide most of their coverage by processing and delivering NRTK corrections using ‘raw’ data observations that have been licensed from GPSnet. The flow of data and revenue between SPs in Figure 37 demonstrates these wholesale data licensing arrangements. In NSW however, industry SPs have typically functioned as DSPs of Government positioning services rather than licensing data from government‐owned CORS infrastructure. Until recently, CORSnet‐NSW did not license wholesale access to their raw data streams, therefore prohibiting industry SPs from computing and marketing their own value‐added positioning services. Prohibiting wholesale access allowed CORSnet‐NSW to maintain full control of the supply chain from data observation to processing and delivery. Hence, the same industry providers that were identified as SPs in VIC were limited to redistributing correction data as DSPs of CORSnet‐NSW corrections. Independent coverage in NSW was only enabled where industry providers had deployed infill CORS, and had licensed access to privately owned CORS. In October 2013 however, CORSnet‐NSW began licensing access to their raw RTCM‐3.1 data streams in much the same way as the VIC Government.

Although licensing is now possible in NSW, Figure 40 does not display service coverage where SPs now license data, which is why a vast proportion of high accuracy service coverage is provided by CORSnet‐ NSW alone in this Figure (compared with a large amount of overlapping industry coverage in VIC). However, it will be demonstrated that the geographic assumptions used to estimate total positioning coverage across Australia in Section 4.3.2.4 remain valid despite these omissions.

It’s important to note that issues of infrastructure duplication and quality control result when overlapping coverage is provided from multiple SPs who deploy independent, uncoordinated networks of CORS in the same region. These issues are further explored in Chapter 6 when reviewing economic drivers for greater coordination. Royalty arrangements introduced in the following Section also influence cost‐benefit decisions for deploying new infrastructure or licensing existing data streams to densify and extend service coverage.

116

4.3.2.2 DATA LICENSING ‐ ROYALTIES

Data licensing arrangements in VIC, NSW and QLD have been identified as a cost‐effective method for extending service coverage without the cost burden of deploying and maintaining physical ground infrastructure. However, ongoing operational costs must somehow be recovered by those who deploy and manage the CORS infrastructure that is licensed to third‐party SPs. These cost considerations underpin the commercial business models discussed throughout Section 4.2. For reference, a government provider who can justify infrastructure investment on geodetic grounds alone may provide free access to data streams as a secondary (indirect) benefit of public good resources (e.g., GA). Alternatively, governments who densify public good infrastructure may operate positioning services that are sold to users on a competitively neutral basis, which is common in VIC, NSW and QLD at present. Data custodians and SPs that also license wholesale access to this data can receive royalties from third‐ party SPs to fund ongoing operational costs.

For example, the Victorian Government receives royalties from each SP that licences access to its source data. Royalty agreements are beyond the scope of this thesis given they are often commercial‐in‐ confidence and negotiated individually between SPs and data custodians. General feedback from government SPs suggests that a 30% royalty from all revenue earned from CORS sites licensed by SPs accounts for ‘back‐end’ infrastructure costs and any loss of customers. A small percentage of industry coverage in Australia is also provided by licensing privately owned sites in addition to, or as a substitute for government owned CORS. Privately owned third‐party CORS may be cheaper to access than paying GPSnet royalties, and may also help to densify the existing GPSnet network (also licensed by the SP) in regions of higher demand. Densification, which often improves vertical accuracy in the service region, is one benefit that industry SPs can advertise as a value‐added service, in addition to their proprietary hardware, software and processing procedures that are used to process, validate and distribute raw and corrected data streams.

4.3.2.3 PSEUDO‐NATIONAL POSITIONING SERVICES

On a national scale, the biggest ‘value‐add’ for industry SPs is their ability to license data streams across State and Territory borders, thus opening the potential to deliver high accuracy positioning coverage nationally. The recent decision by NSW to license raw data is therefore an important development in a national positioning context. A key finding by Hausler and Collier (2013a) is that SPs often promote ‘national’ positioning services, which are in fact ‘pseudo‐national’ given they are limited to regions where government and private investment in CORS has already occurred in response to scientific and commercial demand (see Figure 41). Furthermore, total service coverage for pseudo‐national services is often advertised as a combination of NRTK, single‐base RTK and DGNSS products, meaning high accuracy coverage at the ±2cm level is not necessarily uniform across the entire service coverage region that is advertised.

117

FIGURE 41: PSEUDO‐NATIONAL POSITIONING SERVICES

SmartNet Aus AlldayRTK

‘Pseudo‐national’ positioning services provided by the industry SPs SmartNet Aus and AlldayRTK who license positioning data from multiple government providers, and also deploy/license infill sites. Access to high accuracy (NRTK) data is not uniform across all of the regions shown above given some areas of DGNSS and single‐base RTK coverage are also displayed (primarily for AlldayRTK in Figure 41).

Recent discussions with government SPs in VIC and QLD indicate that their core business responsibilities are shifting towards the operation of positioning services for internal purposes, whilst maintaining their responsibilities as data custodians for the network. The same can be said for CORSnet‐NSW in light of their recent decision to license raw data streams. Whilst all three government providers currently sell positioning services to the public, their custodial responsibilities focus on managing ‘back‐end’ infrastructure as opposed to marketing and selling subscriptions. Section 4.2 highlighted that data distribution and user management are often viewed as the role of industry, which reinforces the notion that commercial positioning services are not typically the mandate of government.

A remaining question addressed within this thesis is to identify the extent to which pseudo‐national services can become truly national through increased technical, institutional and economic coordination between government and industry SPs.

4.3.2.4 GOVERNMENT VERSUS INDUSTRY COVERAGE

A first step towards evaluating the potential for SPs to supply national positioning coverage is to quantify total geographic coverage across the country, and to identify what percentage of this total coverage can be serviced by government and industry CORS infrastructure alone. In light of the data licensing arrangements and the number of government and industry CORS identified in previous Sections, it is concluded that industry SPs have incentive to license access to existing government owned CORS rather than duplicating infrastructure in the same region.

118

Table 10 has therefore been developed on the assumption that governments are the primary data custodian of CORS infrastructure to enable high accuracy positioning coverage in Australia. This assumption holds true regardless of whether industry deploy infill infrastructure in the same region given the user can always substitute to the government service. Hence, industry coverage is only quantified as ‘added’ coverage outside of the geographic regions that are ‘serviced’ by governments. This assumption also explains why estimates of total coverage for NSW, as computed in Figure 40 and Table 10 for January 2013, remain valid despite CORSnet‐NSW’s recent decision to license their source data; licensing will only increase overlapping coverage as opposed to enabling new coverage.

TABLE 10: STATE & TERRITORY NRTK COVERAGE

% of State/ % of total NRTK % of total NRTK % of total NRTK % Aust. Territory cov. serviced by cov. added by (8.4%) cov. in Aus covered covered Gov. industry ACT 100.0 0.4 100.0 0.0 0.0 TAS 51.0 5.1 0.0 100.0 0.4 VIC 100.0 35.4 100.0 0.0 3.0 NSW 29.6 36.9 97.1 2.9 3.1 SA 4.8 7.3 0.0 100.0 0.6 NT 0.0 0.0 0.0 0.0 0.0 QLD 2.6 6.9 33.4 66.6 0.6 WA 2.0 8.0 0.0 100.0 0.7 JBT 100.0 0.0 100.0 0.0 0.0 AUS 73.9 26.1 8.4

The percentage of total coverage in each State/Territory that is serviced by governments, plus the additional coverage (cov.) provided by industry, including Jervis Bay Territory (JBT).

Table 10 shows that 8.4% of Australia is covered by a government and/or industry operated high accuracy positioning service. Based on the distribution of CORS infrastructure as of January 2013, 73.9% of this total NRTK coverage is enabled by government SPs alone. VIC and NSW contribute 71.2% of this total NRTK coverage provided by governments, which is clearly illustrated in Figure 40. Industry SPs therefore contribute 26.1% of additional coverage outside of existing regions serviced by government owned CORS infrastructure. Despite increased industry coverage in the FBA region (which is not mapped in Figure 40), these ratios remain roughly the same given government funding was used to establish this infrastructure.

Critically, no single SP or data custodian provides a single point of access to the entire 8.4% coverage region (Chapters 5 and 6 explore this finding in greater detail). For example, due to independent ownership and management between governments, only 35.4% of total NRTK coverage is accessible from the VIC government’s GPSnet service, and 35.8% from the NSW government’s CORSnet NSW

119 service. It is noted that GPSnet80 and CORSnet‐NSW81 share selected CORS across jurisdictional boundaries; however this does not overcome the need for separate subscription services once a user moves beyond the boundary of each service.

Whilst governments and industry in NSW contribute 36.9% of total NRTK coverage across Australia, one can deduce from Table 10 that 35.8% of this coverage is enabled by government infrastructure alone (i.e., 1.1% provided by industry). This finding is reinforced by the low percentage of industry coverage identified in Table 9 for NSW, which is slightly higher (2.2%) than in Table 10 as it includes regions of overlapping coverage. CORSnet‐NSW’s recent decision to license raw data streams will significantly increase industry coverage estimates for NSW in Table 10 to resemble that of industry coverage in VIC, where 94.6% is provided by SmartNet Aus through data licensing arrangements.

It is therefore concluded that industry SPs rely heavily on accessing government owned CORS infrastructure, regardless of whether a government provider functions as a SP or data custodian.

4.3.3 CASE STUDY 1 – NETWORK EXPANSION

This case study demonstrates how technical (e.g., scientific), policy and commercial concepts discussed throughout Chapter 4 can be addressed to coordinate network expansion of existing CORS infrastructure and positioning services. By detailing an example of local coordination (i.e., within and between States), Case Study 1 identifies various decisions to be considered by governments and industry for transitioning towards a truly NPI. The remainder of this thesis identifies and addresses criteria for achieving this transition.

Suppose a commercial service provider operates an independent positioning service containing eight CORS spaced at approximately 70 km, which are networked to deliver real‐time positioning solutions across a region of 40,000 km2. The network was primarily established for precision agriculture and provides high accuracy coverage across the entire network region with some overlap from a nearby government‐owned positioning service. The coordinates of each CORS within the network have been derived from surrounding GDA94 ground marks but their absolute positions have not been certified under Regulation 13. Correction data is therefore referenced to a local realisation of GDA94 that has been computed within the network software.

The network provider decides to expand service coverage by weighing options for deploying new infrastructure or licensing data streams from nearby government owned and operated CORS infrastructure.

80 An additional 6.7% of total NRTK coverage can be accessed by VIC users in NSW through shared licences. 81 An additional 1% of total NRTK coverage can be accessed by NSW users in VIC through shared licences.

120

A technical officer who manages the commercial network logs onto the NGCI web map to compare location and metadata for the two networks. The officer identifies that five of the government operated CORS are already positioned where the commercial provider is looking to expand, and one site overlaps the current service region. Discussions with the government provider reveal that the cost (e.g., royalty payments) of licensing government data streams are significantly less than the investment required to deploy and operate new infrastructure, especially given maintenance costs will remain the responsibility of the State government provider.

Preliminary comparisons via the NGCI web map reveal that the State owned CORS are linked to a national realisation of GDA94, in contrast to the commercial provider’s local adjustment derived from existing ground monuments. All CORS sites owned by the government provider are certified under Regulation 13. The commercial provider has adopted the MAC processing technique, whilst the government provider delivers VRS corrections.

The technical officer contacts the Responsible Authority (RA) within government (e.g., GPSnet) to gain temporary access to real‐time data streams from the CORS station that overlaps the two networks. By actively observing and recording GNSS data from the overlapping CORS site, the technical officer computes a location using the company’s MAC NRTK processing software, and compares these (localised) coordinates with those computed for the same location using the government service (i.e., GDA94). An overall difference of 150 mm horizontally is detected and the officer finds that differences in datum realisation (i.e., local versus absolute) are the primary cause. The officer also concludes from information presented within the NGCI that the accuracy and quality of the position corrections computed from the two networks may vary due to the different processing strategies, station densities and GNSS equipment used in each network.

Having chosen to license existing data streams, the commercial provider wants to ensure that data from the government network is compatible with its existing network, particularly for quality control purposes. The commercial provider therefore implements the necessary observation and adjustment procedures for certifying each CORS under Regulation 13.

To ensure the extended network will provide a robust connection to the NGRS (i.e., GDA94), the commercial provider also reviews ICSM standards, guidelines and recommended practices for establishing and operating CORS. The provider recognises that a network of this size should include at least one Tier 2 CORS to deliver more reliable access to the NGRS, and to provide greater compatibility with the State‐owned network. The provider identifies three options for integrating a Tier 2 site within the existing network:

License data from an external Tier 2 provider ‐ the provider visits the web map to determine whether any nearby Tier 2 sites owned by independent providers can be licensed for inclusion in the network. If a potential site is identified, its location is reviewed by comparing inter‐station distances to determine its

121 geometric agreement with the provider’s network. Further economic analysis is then needed to determine whether this potential site would expand the provider’s existing customer base by attracting new clients, and whether it would broaden the range of services they can offer. The cost‐benefit outcomes of this analysis also depend on the (competing) services offered by the third‐party provider of the Tier 2 site, and the associated licensing arrangements (e.g., royalties) they negotiate.

Upgrade to a Tier 2 CORS – the provider decides to upgrade an existing Tier 3 site to Tier 2 standard. The web map is accessed as a strategic planning tool to assess which existing site, if upgraded, would firstly improve the reliability of the provider’s existing service, and secondly offer the greatest support to surrounding networks that may also require additional Tier 2 infrastructure. Inter‐station distances between the commercial provider’s existing CORS and the nearest third‐party Tier 2 CORS are used to determine which existing station would deliver the greatest geometric support in a national context. The commercial provider recognises their potential to receive commercial gain from licensing an upgraded site to third‐party providers.

Deploy a new Tier 2 CORS – The same optimisation strategies described above are used to determine where a new site would offer the greatest benefits to the provider’s existing network and surrounding networks. The user consults the ICSM CORS guidelines for deploying a new site to Tier 2 standard, and uses the web map to optimise its compatibility with surrounding infrastructure managed by independent providers (e.g., datum, equipment quality, data formats and correction types).

The NGCI web map is used as a research tool to assess each option, which ultimately serves to minimise infrastructure duplication and improve the performance and governance of operating the commercial network, in line with State government and future NPI standards. Each option improves the quality of the provider’s own service capabilities, whilst simultaneously contributing to the ongoing monitoring and enhancement of the country’s NGRS.

122

4.4 INTERNATIONAL COMPARISONS

This Section reviews current investment and business models for supplying CORS infrastructure in countries that face similar geographic and geopolitical constraints to Australia. Comparisons are made with countries that have access to truly national high accuracy positioning services. Global service providers are then evaluated as alternatives to national positioning services.

CORS infrastructure in most countries has typically evolved in a similar manner to Australia. Sparse networks of CORS are deployed for geodetic purposes and then upgraded and densified over time to enable service coverage nationally, or within a particular geographic region of the country. Fundamental geodetic infrastructure is mostly funded by governments that partner with industry SPs to infill, manage and deliver a variety of positioning services. Appendix C lists a range of CORS networks across the globe that are primarily funded by government. Several examples are explored in this Section to compare geographic, institutional (i.e., policy) and commercial factors that influence how and why governments and industry access CORS infrastructure nationally and internationally.

4.4.1 GREAT BRITAIN

Some networks are managed centrally within government by a single geodetic or equivalent agency. Ordnance Survey for example is the National Mapping Authority of Great Britain that creates, maintains and disseminates geospatial data and manages the NGRS. To access the NGRS, Ordnance Survey manages over 100 CORS (Figure 42) as part of their OS Net service which enables NRTK coverage across Great Britain. Whilst Ordnance Survey maintains responsibility for deploying and managing physical CORS infrastructure, they partner with commercial SPs to deliver positioning services, including SmartNet (UK & Ireland) managed by Leica Geosystems; VRS Now managed by Trimble; TopNetPlus managed by Topcon Positioning Systems; FarmRTK managed by AXIO‐NET; and Essentials Net by Soil Essentials (Ordnance Survey, 2013).

Applying terminology developed throughout this Chapter; Ordnance Survey is a data custodian that licenses access to its raw data streams, which are processed and distributed by SPs in the retail market. Industry SPs (e.g., SmartNet) also deploy a small number of infill sites in regions of higher demand and upgrade existing sites where necessary. OS Net partners with SPs to access correction data for internal business purposes in return for licensing access to its raw data streams. Internal business services include the management and monitoring of the NGRS (Ordnance Survey, 2012). OS Net also offers public access to its online RINEX archive, which reaffirms the definitions of data custodians and SPs provided in Section 4.2.2.4.

123

FIGURE 42: CORS – GREAT BRITAIN

SmartNet provides access to OS Net stations in Great Britain along with those managed by Ordnance Survey Ireland and Ordnance Survey Northern Ireland.

4.4.2 GERMANY

Countries such as Germany that are governed by a hierarchy of State and Federal governments (like Australia) have also been successful in coordinating a single point of access to CORS infrastructure (Hale, 2007). The Satellite Positioning Service (SAPOS) of the German Surveying and Mapping Authority (AdV, 2011) integrates a uniform national network of approximately 270 CORS (see Figure 43) which, in combination with other ground monuments, establishes the country’s NGRS. SAPOS CORS are owned and managed by State governments in each jurisdiction.

SAPOS is a joint project of the Working Committee of the Surveying Authorities of the States of the Federal Republic of Germany, known in short as AdV82. AdV is a forum similar to ICSM in Australia to discuss technical and policy matters in a national context. Official surveying activities in Germany must prove a traceable link to the NGRS, which the SAPOS network is certified to provide. SAPOS is operated on a commercial business model based on the fee structure shown in Figure 44, and three positioning services are offered to customers.

Similar to GPSnet and CORSnet NSW, industry SPs (e.g., SmartNet Germany and AXIO‐NET) license access to SAPOS data to distribute value‐added positioning services across Germany.

82 Arbeitsgemeinschaft der Vermessungsverwaltungen (AdV).

124

FIGURE 43: CORS ‐ GERMANY

Reference stations in the German SAPOS network (AdV, 2013).

FIGURE 44: FEE STRUCTURE – SAPOS GERMANY

Fee (€: euro) structure for SAPOS services (AdV, 2011). HEPS: High Precision Real‐Time; EPS: Real‐Time; GPPS: Geodetic Post Processing Positioning Service; GPRS: General Packet Radio Service; UMTS: Universal Mobile Telecommunications System; GSM: Global System for Mobile Communications; p.a: per annum.

125

4.4.3 UNITED STATES

Similar to Australia, no government or industry SP in the US has established a high accuracy positioning service with national coverage, let alone one that offers a single point of access to regions where coverage is enabled by independent service providers. The US and Australia are both federated nations with geodetic responsibilities managed across different jurisdictions, however both countries are at least 20 times larger in geographic size than Germany. In the US, National Geodetic Survey (NGS) within the National Oceanic and Atmospheric Administration (NOAA) is responsible for managing Federal Government CORS infrastructure and other positioning infrastructure (NGS, 2013a).

The roles of NGS and GA are equivalent in providing the geodetic framework for all national positioning activities. A key difference however is that NGS now coordinates access to over 1800 multi‐purpose CORS sites (Figure 45) that are contributed on a cooperative basis by independent government, research and private data custodians from across the country. In contrast, GA provides access to approximately 150 sites across Australia and its surrounding islands. The purpose of this cooperative model in the US is to define and maintain the country’s NGRS using a dense network of CORS, which allows all users to benefit from a more robust geodetic framework. Each organisation shares their data with NGS who in turn analyses and monitors this data and distributes it free of charge to the public for post‐processing purposes. The NGS has custodial responsibilities to manage a central repository for accessing this RINEX data.

FIGURE 45: US NATIONAL CORS NETWORK

Snapshot of CORS infrastructure (September 2013) managed by governments, research bodies and private organisations that contribute data to the US NGS (available at: ).

126

Similar to the ARGN, NGS owns and operates a subset of Tier 1 CORS that form the backbone of its National CORS Network. The NGS then invites organisations and individuals to augment the National CORS Network by sharing data from their permanent stations, so long as they meet specific CORS Site Guidelines that are published by the NGS (2013b). The ICSM PCG is currently developing equivalent CORS Site Guidelines for Australia, as described in Section 3.5.2.2 and 3.2.1.2. Supplementary data provided by each partner in the US is typically of Tier 2 standard or better, allowing the NGS to coordinate all networks by enforcing strict technical standards that ensure national consistency.

4.4.3.1 SCIENTIFIC DRIVERS

A significant number of CORS within the NGS network are provided from the Plate Boundary Observatory (PBO) network operated by UNAVCO83. The PBO network contains over 1100 CORS (Figure 46) that are combined with other instrumentation such as strainmetres, tiltmetres, meteorological instruments and web cameras to form the geodetic component of the EarthScope Facility funded by the National Science Foundation. The EarthScope Facility is a multi‐disciplinary scientific research community dedicated to understanding dynamic Earth processes and contains three components: the PBO, the San Andreas Fault Observatory (SAFOD) and the USArray – a nationwide seismic reference network. AuScope (see Section 4.2.1.2) and EarthScope share common objectives.

The PBO is a primary example of why governments invest in CORS infrastructure to enable public good benefits. Precise management and monitoring of geodetic frameworks supports research into plate‐ boundary deformation, earthquakes, volcanic processes, sea‐level rise and climate change. Each of these scientific drivers can be linked to social, environmental and economic benefits such as increased education and public safety, improved emergency management systems (e.g., tsunami warnings) for social and economic purposes, and better protection of critical infrastructure assets. The PBO does not operate commercial positioning services and provides free access to data observed from the network (including real‐time data from a sub‐set of the network). Opportunities for research and commercial innovation result from having public access to this data, along with public access to the broader findings of the EarthScope program.

83 UNAVCO is a non‐profit university‐governed consortium that facilitates geoscience research and education. The UNAVCO consortium consists of more than 100 US academic members and over 75 Associate Members (domestic and international).

127

FIGURE 46: US PBO CORS NETWORK

Snapshot of CORS infrastructure on US west coast from the PBO network (February 2014), which is managed by UNAVCO as part of the EarthScope program (available at: http://pbo.unavco.org/network/gps>).

Similar examples of public good investments in geodetic CORS infrastructure include the GNSS Earth Observation Network (GEONET) managed by Japan’s Geographical Survey Institute (GSI), and the EUREF Permanent Network (EPN) across the EU. GEONET (Figure 47a) contains over 1200 CORS sites primarily used to monitor crustal deformation from earthquakes and volcanic activity. GSI enables free access to GEONET data, and selected sites are equipped with resources to enable single‐base RTK and NRTK services. The EPN (Figure 47b) is used to establish and access the European Terrestrial Reference System 89 (ETRS89) using data contributed voluntarily by over 100 European agencies and universities.

FIGURES 47A AND 47B: JAPANESE & EUROPEAN CORS

Figure 47a. Snapshot of GSI’s real‐time Figure 47b. Snapshot of the EPN network ‐ September 2013 GEONET network in Japan (available at: (available at: ) )

128

4.4.3.2 STATE NETWORKS

Hale (2007) provides examples of collaborative approaches to establishing CORS networks at State and local levels in the US that have evolved in a similar manner to GPSnet in VIC. The New York State Department of Transport for instance manages its own network using the SpiderNet software developed by Leica Geosystems. The Washington State Reference Network (WSRS) is managed by Seattle Public Utilities through collaboration with other State government and research partners. Similar to Australia, coverage from government funded State networks in the US tends not to extend beyond State boundaries, except at specific sites that have been licensed by neighbouring governments. For example, the WSRS integrates neighbouring CORS sites from Portland (Oregon), Idaho, Montana as well as Canada (Figure 48).

FIGURE 48: CORS ‐ WASHINGTON

WSRS CORS sites are primarily located across Washington, with selected sites shared across neighbouring borders (http://www.wsrn3.org/Map/SensorMap.aspx).

In North America, industry SPs have begun networking pseudo‐national positioning services using similar commercial business models to those described previously for Australia. SmartNet North America for example adopts a licensing model similar to that of its counterpart SmartNet Aus to network approximately 600 sites across selected pockets of North America. Figure 49 provides a snapshot of network coverage provided by SmartNet on the south‐west coast of the US where data has been licensed from government and privately owned CORS, such as those deployed by local distributors to service regional clients. SmartNet North America typically partners with local distributors of Leica Geosystems equipment for this purpose.

129

FIGURE 49: SMARTNET NORTH AMERICA

Snapshot of NRTK coverage (red polygons) enabled by SmartNet North America on the south‐west coast of the US (available at: ).

In some US States however, CORS infrastructure is funded independently through public or private investment, but SmartNet is contracted to deliver positioning services from the network. SmartNet therefore advertises its presence as a service provider in these regions, but does not provide direct access through the SmartNet North America service given data access policies are determined by the infrastructure owners (data custodians). Users who wish to access these services are directed to ‘affiliate’ networks through the SmartNet North America web portal (Figure 50). A primary example is the Iowa RTN (IaRTN), which SmartNet manages on behalf of the Iowa Department of Transport who funds the CORS infrastructure. The Department of Transport grants free access to the IaRTN, meaning it is managed independently as an ‘affiliate’ network that is governed by standards and access policies stipulated by the client (Iowa Department of Transport).

FIGURE 50: SMARTNET NORTH AMERICA AFFILIATE NETWORKS

Kansas, Iowa, Illinois and Indiana are advertised as ‘affiliate’ services (green polygons) to SmartNet North America, meaning access to these networks is governed by those who fund the underlying CORS. Access to networks in Wyoming, Nebraska and Colorado is centralised through the SmartNet North America (red polygon) service. Note that each polygon identifies States that provide some degree of coverage (e.g., Figure 49), but the extent of each polygon in Figure 50 does not represent total service coverage within each region.

130

Trimble has adopted a similar licensing model to SmartNet in the US through it VRS Now service (Trimble, 2013a), which primarily services central and eastern parts of the North America as demonstrated in Figure 51.

FIGURE 51: US TRIMBLE VRS NOW SERVICE

Service coverage across North America that is enabled by Trimble’s VRS Now service as of September 2013 (Trimble, 2013a).

4.4.4 CANADA

Technical, institutional and economic arrangements for deploying and managing CORS infrastructure in Canada present the closest comparisons to Australia. Both countries have a vast geographic land mass, with concentrated population densities and ad‐hoc networks of independently managed ground infrastructure. The Geodetic Survey Division (GSD) within the Earth Sciences Division of Natural Resources Canada (NRCan) is responsible for managing the Canadian Spatial Reference System (CSRS) in partnership with Geological Survey Canada (GSC). NRCan and GSC implement national regulations, guidelines and standards for establishing a traceable link to the CSRS using traditional ground marks or ‘passive’ monuments (e.g., a survey control point). Approximately 58 ‘active’ CORS (Figure 52a) (equivalent to those of ARGN in Australia and the NGS National CORS Network in the US) managed by NRCan and GSD represent the Canadian Active Control System (CACS). The Canadian Government also offers the CSRS‐PPP service as an online tool for post‐processing data. CSRS‐PPP implements PPP techniques for post‐processing user data compared with the relative post‐processing techniques adopted in AUSPOS and OPUS.

Provincial (i.e., jurisdictional) governments manage approximately 40 CORS (Figure 52a), whilst industry SPs have been most active in deploying over 500 CORS (Figure 52b) to deliver high accuracy positioning

131 services within particular provinces. Leading industry SPs are SmartNet North America and Can‐Net, a privately owned network established by the Trimble distributor known as Cansel (Can‐Net, 2013).

FIGURES 52A AND 52B: CORS ‐ CANADA

Figure 52a. Federal (red) and provincial (blue) CORS Figure 52b. Industry funded CORS sites in Canada (Hains, sites in Canada (Hains, 2013). 2013).

4.4.5 DATA LICENSING – AN INTERNATIONAL TREND

It follows that industry SPs such as Leica Geosystems (SmartNet), Trimble (VRS Now) and AXIO‐NET (FarmRTK) increasingly offer trans‐national services, primarily across Europe, by integrating data from SPs in multiple countries. The same business model is used to deliver pseudo‐national positioning services across jurisdictional and provincial borders in Australia and Canada, respectively. Data licensing is therefore a common business model adopted by SPs worldwide to extend service coverage and avoid deployment costs for installing new CORS infrastructure.

The key point here is that CORS infrastructure is increasingly becoming the standard for monitoring and accessing a country’s NGRS. Governments continue to invest in CORS infrastructure to uphold their geodetic responsibilities, which enables secondary benefits to the economy where these investments are leveraged to deliver positioning services. From a geodetic perspective, data licensing enables multiple SPs to access the same CORS infrastructure, which ultimately improves the compatibility and consistency of their computed PNT information. From an economic perspective, coordinating access to a single CORS site is more cost‐effective for all providers than deploying multiple CORS in the same location. Economic evidence supporting this finding is provided in Chapter 6.

Ultimately, examples of national and international data licensing arrangements presented throughout this Chapter support the findings from Section 4.3 that industry SPs depend heavily on maintaining access to government owned CORS infrastructure. Regardless of whether governments or industry operate positioning services across a specific region, geodetic investment will continue.

132

4.4.6 GLOBAL SERVICES PROVIDERS

Global SPs use global space and ground augmentations to deliver global positioning services. Firstly, note that government‐owned and operated services such as AUSPOS and CSRS‐PPP employ post‐ processing techniques (i.e., not real‐time). Whilst these government services are optimised for Australia and Canada respectively, they are also capable of post‐processing GNSS solutions globally. As described in the next section, real‐time global positioning services are currently provided by industry SPs who enable access to global space and ground‐based augmentations.

4.4.6.1 INDUSTRY SERVICE PROVIDERS

Several industry providers have deployed sparse global networks of CORS to produce real‐time data corrections globally, using relative and PPP techniques. These corrections can be uploaded to high‐ powered geostationary communications satellites and broadcast as proprietary data streams that are optimised for satellite transmission via L‐Band frequencies. Global service providers typically license capacity on third‐party communications satellites rather than owning satellite assets. However, these corrections are not available to everyone. Third‐party communications satellites are not typically part of a GNSS constellation meaning a specific type of GNSS receiver or external device is needed to access these signals. Global service providers develop specific brands (e.g., OmniSTAR) of GNSS receivers for this purpose, and various manufacturers (e.g., Leica Geosystems) sell devices that are compatible with global services (e.g., Trimble’s OmniSTAR service). Upon purchasing a compatible receiver, users must also purchase a subscription from the global service provider in order to access correction information. Four industry examples are described below.

OmniSTAR: Trimble’s OmniSTAR service is comprised of over 100 global CORS (approximately 13 located in Australia), eight independently owned communications satellites, and two global control centres, and data corrections are delivered via L‐Band satellite communications (OmniSTAR, 2013). Global OmniSTAR services include OmniSTAR HP, G2, XP, and VBS, which range from ±10cm horizontal accuracy (95% confidence) for HP services, to sub‐metre horizontal accuracy for VBS. Vertical accuracies are typically up to two and a half times worse than horizontal accuracies. Some positioning techniques implemented by OmniSTAR (e.g., DGNSS – see Chapter 3) require less data to be transmitted to the user (such as L1‐ only solutions), meaning the data format is highly compact and requires limited bandwidth, therefore allowing efficient transmission via satellite. These data products are typically used for lower accuracy applications given residual atmospheric and system errors are not fully minimised.

OmniSTAR HP and XP also use dual‐frequency (e.g., L1/L2) carrier phase measurements to further reduce range errors between a satellite and receiver, but users must operate dual‐frequency receivers in order to apply these higher accuracy (e.g., ±10cm) corrections. OmniSTAR sells a range of OmniSTAR receivers that are optimised for different applications and positioning services, and various

133 manufacturers have developed OmniSTAR compatible receivers. The current datum for OmniSTAR is ITRF2008 meaning Australian users must transform their coordinates to GDA94 if needed.

NavCom StarFire: StarFire broadcasts global data corrections via geostationary satellites using dual‐ frequency observations from over 80 global CORS sites, which enables multi‐GNSS positioning solutions of around ±5cm horizontal, and ±10cm vertical (95% confidence) in good operating conditions (Murfin, 2013). Standard convergence times of 30 to 45 minutes apply (Navcom, 2014). Single frequency applications deliver around ±50cm horizontal and ±100cm vertical accuracies (95% confidence).

StarFire was developed by NavCom Technologies Inc. (NavCom) and Ag Management Systems (AMS), which are both part of Deere and Company, one of the largest suppliers of agricultural products and services worldwide. StarFire is marketed as a global SBAS, and whilst the system maintains a strong presence in the global agriculture market, around 10 per cent of its customers are from other sectors including surveying, GIS, aviation, maritime and government. StarFire offers two primary subscriptions: Land Only and All Areas. L‐Band data corrections are delivered via the third‐party inmarsat satellite network (inmarsat, 2013).

StarFire presents an interesting case of commercial collaboration between government and industry providers. Since 2001, NavCom have licensed software known as Real Time GIPSY (RTG) that was developed by NASA’s JPL. RTG is used to compute real time orbit and clock corrections which are implemented by StarFire to enable sub‐decimetre horizontal accuracies globally.

Veripos: Veripos, owned by TERRASTAR, is a third global service provider that offers similar correction products to StarFire via the same satellite communications network (inmarsat). Veripos has its roots in marine positioning services and continues to increase its presence for land applications. Veripos was purchased by Hexagon Ground in 2013, which also owns Leica Geosystems.

CenterPoint RTX: Trimble’s CenterPoint RTX product uses PPP techniques to deliver global positioning solutions at sub‐decimetre accuracies. PPP is traditionally a post‐processing methodology that requires time to model orbit, clock and other error corrections with sufficient accuracy to enable sub‐decimetre positioning accuracy (see Chapter 3).

Trimble markets horizontal positioning accuracy for its CenterPoint RTX service at ±4cm (95% confidence) globally, with a convergence time of 20‐30 minutes, meaning the service does not provide an instantaneous real‐time positioning capability. However, once initial convergence is achieved, CenterPoint RTX can operate in real‐time so long as the user maintains visibility to multiple satellites. If visibility is lost, new carrier‐phase measurements require time to re‐converge. RTX typically delivers higher accuracy than Trimble’s OmniSTAR services once convergence is achieved. Trimble leverages ground and space based infrastructure from OmniSTAR to deliver RTX services. Trimble is also evaluating the benefits of including additional satellites from China’s Beidou system to improve the performance

134

(e.g., orbit and clock quality) of CenterPoint RTX, which offers the potential to decrease convergence times across a larger service area (Landau et al., 2013).

To achieve faster convergence times, Trimble currently offers the CenterPoint RTX Fast product which is designed to converge in less than one minute. However, service coverage is limited to central North America (within a region of approximately 50,000 km2), where supporting CORS infrastructure is spaced at approximately 120 km, allowing regional error models (similar to NRTK) to support faster convergence and greater accuracy.

The resulting RTX corrections are optimised using proprietary data formats developed by Trimble, which are compact enough for transmission via L‐Band satellite frequencies. Trimble and Trimble‐affiliated receiver brands are needed to implement RTX corrections. RTCM formats used for standard NRTK solutions are not typically suited to satellite delivery given their high bandwidth and low latency requirements. Trimble also notes that CenterPoint RTX operates as a standalone global positioning service rather than relying on access to any external data products such as orbit and clock corrections provided by the IGS.

4.4.6.2 IGS REAL‐TIME SERVICE

The IGS Real Time Service (IGS‐RTS) is a global service operated by the IGS as a public good, to provide free access to global orbit, clock and ionospheric corrections that can be implemented by any user or GNSS manufacturer. Chapter 2 described the voluntary role that the IGS has undertaken since 1994 to compute and deliver precise satellite orbit and clock data for post‐processing purposes. The IGS‐RTS, launched in April 2013, extends this role to delivering real‐time orbit and clock products that can be used to compute sub‐decimetre PPP solutions. IGS‐RTS products are formatted as RTCM‐SSR messages and broadcast using the NTRIP protocol, and RTS orbits are expressed in ITRF08. The RTS also provides one Hertz (Hz84) data streams of GPS and GLONASS observations from approximately 130 real‐time IGS receivers within the 370 station global IGS CORS network.

The global benefit of the IGS‐RTS is that RTCM‐SSR messages are non‐proprietary, meaning they can be implemented free of charge by all users. RTCM‐SSR messages are therefore beneficial for scientific and public good purposes, such as weather forecasting, geophysical hazard detection and warning systems, and GNSS performance monitoring. Geophysical applications are a key driver given open, and globally available real‐time GNSS information is complementary to other information, such as seismic data, for rapidly detecting, locating, and characterising hazardous events such as earthquakes and tsunamis (IGS, 2013d).

Alternative global positioning services provided by industry typically require fee‐based subscriptions and a specific brand of GNSS receiver to access proprietary data formats. The IGS therefore encourages

84 1 Hz equals 1 measurement per second.

135 manufacturers to integrate RTCM‐SSR and future RTCM‐MSM functionality into their receivers to promote global compatibility and performance management of PPP and other positioning services. No manufacturers have incorporated PPP functionality using RTCM‐SSR messages at the time of writing. Hence, whilst the IGS‐RTS is a global positioning service, the service is typically used by researchers and scientific agencies with the expertise to apply and compare RTCM‐SSR data.

4.4.6.3 GLOBAL VERSUS NATIONAL POSITIONING INFRASTRUCTURES

Whilst the four industry SPs identified previously have made significant progress towards enabling sub‐ decimetre positioning accuracy using dual‐frequency multi‐GNSS signals, no service provider delivers global three‐dimensional positioning accuracy at ±2cm (95% confidence) in real‐time. Some providers augment their global services by deploying or accessing local or national networks of CORS infrastructure to deliver high accuracy corrections within specific geographic regions (e.g., CenterPoint RTX Fast).

It follows that global service providers are not considered a direct substitute for existing high accuracy positioning services in Australia, which is why governments and industry continue to densify their CORS networks in regions of higher demand. The decision to substitute to a global positioning service depends on a user’s opportunity costs for accuracy and coverage (refer to Section 6.2.1.1). User education is also a key factor given different types of technology and services are marketed by businesses that have a stronger presence and brand in particular market sectors, such as Deere and Company. In the context of a NPI however, the capacity for global service providers to function as a complement, alternative, backup and competitor to existing and future high accuracy positioning services in Australia is an important consideration addressed in Chapter 6.

Readers are also reminded that Chapter 3 introduced QZSS LEX as a potential alternative to using third‐ party communications satellites as the primary means of delivering data corrections. LEX is a dedicated communication channel for broadcasting more complex correction data than standard SBAS signals, and is directly interoperable with GPS L1 meaning any GPS‐enabled device could potentially receive data corrections where QZSS coverage is available. QZSS is however a RNSS meaning the benefits of LEX will be limited to the Asia‐Pacific region, including Australia.

4.4.7 GLOBAL COLLABORATION

A unique property of CORS infrastructure is that the same individual CORS sites that augment positioning infrastructures at a local (e.g., State) and national scale also contribute to global positioning infrastructure. These positive externalities85 mean that CORS sites create additional benefits (e.g., economic), beyond their direct benefits, which help to justify ongoing investment in CORS. A prime

85 Introduced in Chapter 1 and revisited throughout Chapter 6.

136 example is the Australian‐owned Tier 1 CORS that contribute to developing the IGS orbit and clock products. GA owns and operates these Tier 1 sites that are primarily used to manage GDA94, but they also contribute to strengthening the global IGS CORS network. Tier 1 sites would still be needed for datum management in Australia regardless of whether they contributed to the IGS, but the positive externalities they create further justify their value.

It follows that a key expectation of national geodetic agencies is that they share their CORS infrastructure with the global user community to maximise public good benefits (see Section 6.4). For example, the global user community benefits from increased redundancy and integrity (i.e., scalability) in the IGS tracking network. This collaboration fosters research and commercial innovation for developing cost‐effective GNSS products and services, the benefits of which ultimately flow to consumers. Hence, the extent to which global and regional users benefit from the global IGS network depends on the number of other people that are using it, which is an example of the network effect (see Section 6.2.4)

In a geodetic context, the IGS is only one example of global collaboration that supports Earth science research, commercial PNT applications and multi‐disciplinary education. Various international associations and unions have been established to promote scientific cooperation and research. Leading organisations that benefit from public access to geodetic CORS infrastructure and positioning services include the IGS, the Global Geodetic Observing System (GGOS, 2011), and the International Earth Rotation and Reference System Service (IERS, 2014), all of which are services and observing systems of the International Association of Geodesy (IAG, 2013).

4.5 CONCLUSION

This Chapter has described the evolution of CORS infrastructure from its geodetic origins to the multitude of scientific and commercial networks that now operate locally, nationally and globally. Approximately 150 CORS are sparsely (>200 km) distributed across Australia as part of the ARGN and AuScope networks to support geodetic and other Earth science applications.

CORS infrastructure investment by State and Territory governments was found to be inconsistent and primarily driven by commercial incentives in regions where a suitable RoI has been identified. VIC and NSW have contributed most investment to date in response to commercial demand from agriculture, engineering, mining, construction and surveying industries. VIC and NSW operate commercial positioning services on a competitive neutral basis, but leverage these services for internal business purposes such as monitoring the geodetic datum.

The number of government services that require access to high accuracy PNT information is likely to increase as cross‐sectoral engagement and awareness continues to expand in light of Australia’s

137

Satellite Utilisation Policy; the NPI Plan; and the outcomes of this research. Service coverage and accuracy is however limited across Australia at present due to different spatial policies, business models and scientific and commercial drivers for investment in CORS infrastructure.

Industry SPs market their own value‐added positioning services that are differentiated in terms of GNSS equipment, quality control systems and proprietary data formats. Industry SPs often license source data from government and third‐party data providers and deploy additional sites in regions of higher to demand. All SPs can attract a broader client base by distributing data through affiliated DSPs.

Data licensing increases access and compatibility when the same CORS sites are integrated into multiple positioning services. SPs are also encouraged to include high stability Tier 1 and Tier 2 CORS with cheaper Tier 3 infrastructure to establish a robust and traceable link to the NGRS. Maintaining compatibility between local, national and international CORS networks within a global GRS (e.g., ITRF) will be important in a multi‐GNSS future, where global data products and absolute positioning techniques such as PPP become commonplace. Open data standards such as RTCM‐SSR messages will help to improve the availability and compatibility of positioning services on national and global scales.

Data licensing was therefore found to extend service coverage across jurisdictional borders without the cost burden of deploying and managing physical CORS infrastructure, which has allowed industry to play a vital role in enabling national positioning services. However, existing high accuracy service coverage has been identified at only 8.4%, and no individual SP manages a single point of access to this entire service coverage region. Furthermore, the majority of total coverage has been enabled by government‐ owned CORS, particularly in VIC and NSW.

This thesis advocates the need for truly national positioning coverage through a coordinated investment and data sharing approach, as guided by the NPI concept introduced in Chapter 5, and examined economically in Chapter 6.

138

CHAPTER 5 THE NPI CONCEPT

THE NPI CONCEPT

5.1 INTRODUCTION

The evolution of CORS infrastructure has been described in Chapter 4 to identify the current supply of high accuracy positioning services operated by government and industry SPs in Australia. This Chapter introduces the NPI concept as the next phase of this evolution that will establish a single point of access to CORS infrastructure across Australia.

Chapter 1 identified technical, policy and business discussions between governments, industry, and the research and user communities of Australia, which have formalised the NPI concept. This Chapter discusses why a single point of access is needed to improve access to, and the functionality of CORS infrastructure within a NPI.

5.1.1 RESEARCH RATIONALE

The rationale behind Chapter 5 is to demonstrate the infancy of the NPI concept at a technical, institutional and economic level, and therefore outline the contribution of this research towards generating knowledge for planning and implementing a NPI (Chapters 6 and 7). To achieve this, the concept of creating a single point of access to existing CORS infrastructure through the NPI is explored, as illustrated in Figure 53.

FIGURE 53: CHAPTER 5 RATIONALE

Rationale for Chapter 5 which introduces the need to create a single point of access to CORS infrastructure in Australia by developing a NPI.

140

5.2 BUILDING CONSENSUS

5.2.1 ANZLIC NPI POLICY

The NPI concept was officially accepted at the national level in Australia with publication of the NPI Policy by ANZLIC86 in 2010. The Policy outlined a set of principles for ensuring sustainable and compatible deployment of GNSS CORS infrastructure to service the positioning needs of a diverse user community with efficient and effective Australia‐wide positioning coverage. Five guiding principles were defined in the NPI Policy: Purpose; Interoperability; Performance; Governance; and Privacy.

In light of Section 3.2, the NPI Policy recognised that CORS sit at the heart of positioning infrastructure, and that positioning infrastructure underpins the referencing and application of all spatial data:

“While early development of the CORS infrastructure is desirable and will deliver positioning capabilities to Australian governments and industry yielding significant economic benefits, this early development is not currently funded or coordinated on a national basis. CORS infrastructure will however continue to be rolled out in this ad hoc manner, with the rate of the roll out determined by the levels of investment that can be made by various public and private sector players. Regardless of the rate of development of the infrastructure, it is timely to develop a national policy that will help steer the development of Australia’s precise positioning infrastructure in a coordinated way so as to deliver optimum benefits to the nation as soon as possible.”

(ANZLIC, 2010)

5.2.2 AUSTRALIAN STRATEGIC PLAN FOR GNSS

Further consensus on the need for a whole‐of‐nation approach towards managing positioning infrastructure in a multi‐GNSS future was formalised in the Australian Strategic Plan for GNSS, published by the Australian Spatial Consortium (ASC) in 2012. Partners87 of the ASC represent the views of governments, industry and the research community, to establish a high level forum in which the core spatial information organisations in Australia can share information, explore areas of common interest, and accelerate their collective achievements. The Australian Strategic Plan for GNSS recommends that a NPI will coordinate government and industry investment in CORS infrastructure, and will facilitate the modernisation and operation of this infrastructure through national and international collaboration.

86 ANZLIC is Australia’s peak intergovernmental organisation for spatial data collection and management, and is governed by 10 senior officials from the Australian and New Zealand Federal governments and State and Territory governments of Australia. 87 The ASC represents the views of government, industry and research through partnerships with ANZLIC, SIBA (Spatial Industries Business Association), CRCSI, SSSI (Surveying and Spatial Sciences Institute), PSMA Australia and 43 Pty Ltd – a unit trust that brings together over 50 companies to conduct research through the CRCSI.

141

5.2.3 AUSTRALIA’S NPI PLAN

Chapter 1 introduced the need for a NPI Plan in alignment with Principle one of the Australian Satellite Utilisation Policy. The NPI Plan will examine investment in domestic ground infrastructure that is needed to deliver accurate and reliable positioning information to users across Australia (Australian Government, 2013). Chapter 1 specifies that the Intellectual Property developed through this research is assisting the Australian Government to develop the NPI Plan. Whilst the Plan has not been released publicly at the time of writing, its Terms of Reference (Geoscience Australia, 2012) are summarised below to demonstrate in subsequent Chapters why this research will be used as a resource for implementing the Plan.

It is noted however that the outcomes of this research are not contingent on the outcomes of the NPI Plan. The research findings stand alone as an original contribution to knowledge identifying challenges and opportunities for enabling greater access to CORS infrastructure in Australia, particularly in response to ANZLIC’s NPI Policy. In light of Section 1.4, the contribution of this work has already been validated by informing development of the NPI Plan itself.

NPI Plan Terms of Reference (Geoscience Australia, 2012): With a view of enhancing coordination of current and future investment in positioning, navigation and timing infrastructure and developing an interoperable coherent national network, the development of a national positioning infrastructure plan will examine and make recommendations on:

1. the appropriateness of an interoperable coherent national positioning network;

2. how positioning infrastructure supports the delivery of government services and programs and drives innovation and productivity benefits for Australia;

3. the overall investment required over a ten‐year timeframe to adopt and build a coherent national positioning network; and

4. the benefits derived from Australia’s unique geographic position and ability to access new GNSS systems and the need for use of these systems within Australia.

Importantly, ‘Infrastructure’ is taken to include the full extent of enabling systems required to deliver value from GNSS, from the physical acquisition of space‐based signals through to the delivery of precise positioning information to users.

This is the first Australian research study to identify and relate technical, institutional and economic evidence that supports the arguments set out in the ANZLIC NPI Policy, Australian Strategic Plan for GNSS, and the NPI Plan, regarding why a NPI will facilitate greater coordination of CORS infrastructure. The concept of creating a single point of access to all CORS infrastructure is subsequently addressed throughout this thesis to examine the research hypothesis.

142

5.3 NPI: A SINGLE POINT OF ACCESS

Chapter 4 identified that no individual SP has established a single point of access (technically) to the existing 8.4% high accuracy service coverage region across Australia (see Figure 40). Section 6.4.1.3 explains that no central department within the Australian Government is recognised (institutionally) as the single point of contact for matters related to real‐time high accuracy GNSS positioning infrastructure and services. The challenge of developing uniform spatial policy within a federated government system was reviewed in Section 4.2.1.1, and the economic (cost‐benefit) implications of these technical (infrastructure and data standards) and institutional (access policies, funding and certification) shortfalls are examined in Chapter 6.

To adequately address these economic implications in light of recent policy and technical work, comparisons are needed with earlier research by Hale (2007) and Higgins (2008) addressing coordination or ‘unification’ issues preceding the NPI concept. This background research is reviewed in the following Sections to identify similarities with the technical, institutional and economic themes presented throughout this thesis. The NPI Planning Framework developed in Chapter 7 then demonstrates that empirical spatial data analysis and economic theory applied throughout this thesis contributes a level of innovation and originality that significantly enhances the relevance and impact of previous and current research, by articulating more clearly the underlying business case for supplying CORS infrastructure. These findings are summarised within NPI Planning Framework to identify criteria for establishing a single point of access (technically, institutionally and economically) to CORS infrastructure across Australia.

5.3.1 PAST RESEARCH

The ‘GNSS CORS Network Management Model’ (CNMM) (Hale, 2007) and ‘Higgins model’ (Higgins, 2008) for unifying access to CORS infrastructure are briefly reviewed within this Section. Both models address two key challenges examined throughout this thesis:

1. To coordinate Federal, State and Territory government funding and management of Australia’s positioning infrastructure;

2. To coordinate public and private sector investment in positioning infrastructure.

Both models are contrasted with the NPI concept in this Chapter to articulate why the economic research contribution presented in Chapter 6 is unique.

143

5.3.1.1 GNSS CORS NETWORK MANAGEMENT MODEL

In developing the GNSS CORS Network Management Model (Figure 54), which explores the relationships between CORS network operators, data custodians, researchers, developers, data providers and data users, Hale (2007) identifies that:

“Optimising the utility and productivity of CORS networks depends as much on CORS network management arrangements and how well they meet institutional, legal, operational and commercial requirements, as it does on developing the technical capability of GNSS/CORS technology”.

(Hale, 2007)

This statement is particularly relevant to the institutional and economic themes identified throughout this thesis regarding the need for a more national approach to coordinating policy and investment in Australia’s positioning infrastructure. In fact, the CNMM was primarily developed as a tool to stimulate future research on addressing unification issues (Hale, 2007), which are themes this research directly responds to.

The CNMM focuses on leveraging the public sector’s national capabilities for coordinating policies and standards at State, Territory and Federal levels of government, whilst highlighting the technical innovation, marketing and distribution capabilities of the private sector (Hale et al., 2006). It also illustrates the flow of revenue, royalties and user fees that could be distributed between the various participants in the market for high accuracy positioning services. Although the model is national in scope, it assumes that Australian Government CORS infrastructure would continue to be in‐filled by State and Territory governments who would establish multi‐lateral agreements to ensure consistency in their core institutional, operational, commercial and legal management requirements.

This ‘partnership’ model differs somewhat from public policy discussions in Chapter 6 regarding the need for uniform regulation, funding and standards, implemented through an Australian Government mandate to create a single point of access. Whilst this thesis encourages ongoing investment by State and Territory governments, it details the benefits of creating partnerships between the Australian Government and each State and Territory government, rather than relying on multi‐lateral agreements between States to enable uniform and centralised access to CORS infrastructure. Partnering with the Australian Government aligns more closely with the positioning objectives set out in the NPI Policy and Satellite Utilisation Policy towards maximising utility from all existing infrastructure, thereby recognising the national significance of previous government investment.

144

FIGURE 54: GNSS CORS NETWORK MANAGEMENT MODEL

GNSS CORS Network Management Model (Hale, 2007).

However, in clear alignment with recent NPI discussions, the CNMM identifies CORS infrastructure as a ubiquitous spatial utility where positioning infrastructure forms another component of fundamental national infrastructure, in addition to transport, telecommunications, water and power. Hence, the CNMM shifts the focus from traditional geodetic applications to identify ‘position’ as a key enabler of direct and external benefits (positive externalities) across the entire economy. Under this scenario, geodesy is the scientific tool for managing and monitoring the underlying integrity of the nation’s positioning infrastructure, but is not the primary justification for investing in CORS infrastructure.

The NPI Planning Framework introduced in Chapter 7 builds on this concept by identifying that a new, whole‐of‐government and industry approach to deploying, operating and managing CORS infrastructure is needed rather than limiting coordination to a set of multi‐lateral partnerships. Conceptually, the CNMM can be interpreted as an intermediate solution towards building a consolidated NPI. Regardless of the final coordination model that is adopted, the NPI Planning Framework developed through this research will inform the underlying business case for coordinated infrastructure investment and management in Australia.

145

5.3.1.2 THE HIGGINS MODEL

The Higgins Model also advocates partnerships between State and Territory government providers to generate cross‐sectoral value from positioning infrastructure:

“Given that it is difficult for single organisations to justify covering large areas of regional Australia there is a need to devise partnership models to develop a unified GNSS reference station network for Australia. ... A unified network of precise positioning reference stations would minimise duplication and optimise the outcomes from infrastructure investment ... more importantly, it would enable accelerated take up across major sectors of the economy, especially in regional areas”. (Higgins, 2008)

Rather than developing a partnership model for establishing a single point of access, Higgins (2008) identifies five discrete organisational roles played by key organisations who supply CORS infrastructure and high accuracy positioning services across Australia. Figure 55 identifies these roles and the types of supply activities they entail.

FIGURE 55: HIGGINS MODEL

Specify Stations Network Process Deliver

Specify System Own Stations Network the Data Process Network Deliver Service • Target Density, • Site Selection •Data Comms • Copy of • Retail Sale of Coverage •Site from Network Network Data Products Reliability and Construction Stations •Data •Marketing Availability • Equipment • Control Centre Processing •Rover •Site Quality Purchasing •Data Archive • Production of Equipment • Equipment • Station Data Data Streams support Quality Comms • Distribution of • End User • Geodetic •Site Data Streams Support Reference Maintenance •Data • Liaison with Frame • Equipment Wholesaling User Comms • Data Services Replacement • Retailer Providers Produced Cycle Support • Data Access Policy

Governance

A Model for Describing Organisational Roles in Precise Positioning Services (Higgins, 2008)88.

It follows from Figure 55 that the Higgins Model represents a linear supply chain that can be used to identify different roles for governments and industry towards establishing and delivering positioning services. However, the Higgins Model does not explicitly identify or differentiate technical, institutional and economic criteria for undertaking each role. Put simply, the Higgins Model focuses on optimising

88 Comms: Communications

146 the supply chain for a unified CORS network once the business case for coordination has been justified. The NPI Planning Framework has therefore been developed to inform the underlying business case for national investment before Higgins (2008) and other models are needed to optimise supply criteria. Section 7.2 explores the relationship between the Higgins Model and the NPI Planning Framework in greater detail.

5.3.2 NPI: A NEW APPROACH TO COORDINATING ACCESS

In essence, the purpose of this research is to demonstrate that questions of why, and how to increase access to CORS infrastructure across Australia are multifaceted. Whilst users often demand access to high accuracy positioning services at the click of a button, governments and businesses who fund, produce and distribute these services are faced with more complex technical, institutional and economic decisions on how to enable an instantaneous positioning capability. Collectively these decisions influence the value chain and supply chain for managing, and therefore accessing positioning services. However, these criteria are not explicitly identified or addressed within the CNMM or Higgins models described previously. These earlier models primarily focus on refining and consolidating supply chains, whereas this research addresses public good and commercial challenges and opportunities for supplying CORS infrastructure in the first place.

In response to these challenges and opportunities, the concept of access is examined throughout this research from an institutional perspective, with regard to the policy‐driven roles and responsibilities, data access policies, funding arrangements (public and/or private), regulatory requirements (standards and certification procedures) that influence the rights and restrictions of those who produce and use position information; from a technical perspective, with regard to the physical radio signals, ground infrastructure, data formats and communication mechanisms needed to process and distribute position information; and from an economic perspective, with regard to cost‐benefit decisions that determine whether the direct (e.g., financial) and indirect (e.g., public safety) benefits of investment in positioning infrastructure, outweigh the fixed and variable costs needed to establish wholesale and retail markets for high accuracy GNSS positioning services.

To create a single point of access, these technical, institutional and economic criteria need to be addressed in a way that engages all relevant stakeholders (producers, managers, users). A NPI will create this single point of access, meaning a NPI is not just a physical infrastructure; it is the people, principles, policies, guidelines, standards, institutions and technology needed to enhance the value of multi‐GNSS position information to the Australian economy. Similar to the NBN, Figure 56 illustrates that a NPI will underpin a competitive market in which multiple SPs and VARs of positioning (and other) services can offer a single point of access to a truly national real‐time positioning network.

147

FIGURE 56: CONCEPTUAL NPI MODEL

Wholesale Wholesale & Competitive Access Retail Access NPI

Coordinating CORS ‐ Service Body Providers

CORS Principles ‐ Value Added Policies Resellers Guidelines ‐ Governments CORS Standards People ‐ Academia Institutions CORS Technology ‐ ’Public Good’

Public & Private Single Point of Positioning Market

Stakeholders Access

Revenue/Royalties Revenue

Conceptual supply chain for distributing CORS data through a single point of access nationally to increase wholesale and retail access for public good and commercial purposes.

The coordinating body in Figure 56 is the organisation(s) responsible for coordinating (licensing) wholesale access to data from independently owned CORS infrastructure, contributed by NPI stakeholders from across Australia. The coordinating body would facilitate wholesale and retail access to this data in Australian and international positioning markets. This data could be used directly89 by governments, academia and the broader scientific community (e.g., for public good purposes), and sold (for a fee) in the retail market either directly without augmentation, or with a level of value‐added augmentation (e.g., accuracy, quality assurance). Revenue from the positioning market would be used to fund operational costs and ongoing maintenance, upgrades and expansion (within and outside of Australia) of a NPI. Stakeholders that contribute data to the NPI would receive royalties from this revenue stream to compensate their investment in CORS infrastructure, meaning a larger royalty would be paid to those who contribute more data.

Chapter 4 provided international examples of existing markets in the United Kingdom and Germany where governments have funded a backbone of national CORS infrastructure, similar to the model in Figure 56, which can be accessed for public good (e.g., geodetic) and commercial purposes. Commercial SPs in these countries have a single point of access90 (e.g., provided by Ordnance Survey in the UK) to national CORS infrastructure, which enables them to enter competitive markets and sell access to national positioning services. This single point of access ensures each service is linked to the same

89 Access could be provided free of charge or at a cost depending on the chosen funding model. 90 Subject to potential licensing fees and certification criteria.

148 infrastructure, thereby promoting technical and institutional traceability. In other words, assuring users of a nationally consistent and standardised (i.e., certified) connection to the NGRS (through a single point of access) ultimately addresses and protects the technical, institutional and economic interests of all stakeholders.

Similarly, State governments in VIC and NSW have already created single points of access to CORS infrastructure located within their individual States (including infrastructure shared across the VIC‐NSW border in some areas). Both governments license access to standardised (RTCM) data from Regulation 13 certified CORS for use by commercial SPs. Table 10 in Section 4.3.2.4 highlighted that the VIC and NSW governments enable 100% and 97.1% of high accuracy positioning coverage, respectively, in each State regardless of additional investment by industry. A single point of access is now available to industry providers in these States to avoid further duplication, and to promote competition in retail markets.

Furthermore, two or more SPs collectively have greater resources (e.g., finances, employees, existing and prospective users) for marketing and selling positioning services than one SP alone, meaning multiple SPs can attract a larger network of users without the cost burden of deploying new infrastructure. Findings by Hale (2007) in Section 5.3.1.1 support this argument by reinforcing the private sector’s strengths in innovating, marketing and distributing positioning services to a broader user base.

To summarise, creating a single point of access to data through a NPI lowers access costs for SPs (rather than deploying new CORS), and increases competition between SPs who access the NPI. Greater price competition can therefore lead to lower access costs (e.g., subscription costs), meaning more users have incentive to purchase high accuracy positioning services. Chapter 6 provides unique economic evidence to support this argument by examining the case for consolidating access to existing CORS infrastructure across Australia, thereby generating a larger and more competitive national market for positioning services.

5.3.2.1 NPI: A NATURAL EVOLUTION

To set the scene for the economic analysis presented in Chapter 6, it is useful to summarise key technical and institutional arguments for coordinating access to CORS infrastructure by interpreting the NPI as a natural evolution in Australia’s management of geodetic and commercial positioning infrastructure. In this broader positioning context, the NPI should be viewed as a resource not only for accessing and referencing GNSS data, but spatial data more generally.

A key theme examined throughout this thesis is that government and industry providers in countries with large geographic extents such as Australia face challenges trying to justify ground infrastructure investment on a national scale using current GNSS technology and positioning techniques. Governments

149 and industry need to be convinced that an increasing number of activities (e.g., transport, engineering, agriculture) will require accurate and reliable position information (i.e., an accurate and traceable link to the NGRS), made available to users at low cost and with high simplicity, regardless of where these activities are located (i.e., within or outside of existing high accuracy service regions). Communicating this requirement is particularly important as multi‐GNSS technology becomes embedded in the information economy (see Chapter 6), and as absolute GNSS positioning techniques such as RT‐PPP evolve to become the standard (see Chapter 4). Put simply, deploying a uniform distribution of CORS infrastructure nationally enables better modelling of the dynamic relationship between a country’s NGRS and GNSS/RNSS systems. Any positioning application, in any location of Australia (and ultimately the Asia‐pacific) will therefore benefit from having access to authoritative position information that accurately describes this relationship. The NPI is a technical, institutional and economic mechanism for producing and distributing this position information, nationally. Chapter 6 examines this relationship from the user perspective, to evaluate why the economic (i.e., public good and commercial) benefits of a NPI are the primary justification for facilitating mass market uptake through a single point of access.

In a broader context, whether spatial data is applied locally (e.g., a building site), State‐wide (e.g., topographic mapping, asset management), nationally (e.g., elevation models, monitoring intra‐crustal motion, building and connecting transport infrastructure), or regionally (e.g., APREF), the NGRS is the reference for all spatial data in a country, and GNSS technology improves the accuracy and national consistency of a NGRS. Consequently, deploying a uniform distribution of CORS infrastructure across a country brings technical (accuracy, quality assurance), institutional (traceability) and economic (more ‘valuable’ data) benefits to anyone who collects and applies spatial data referenced to the NGRS; not just those who specialise in GNSS applications. Hence, the value chain for supplying CORS infrastructure not only relates to GNSS applications, but the value it contributes to producing and referencing spatial data more broadly. Given most users will have no concept of what the NGRS is, let alone why a consistent connection to it creates significant value, Chapter 6 establishes an economic narrative for evaluating and communicating the value that high accuracy multi‐GNSS positioning services create in consumer markets.

5.4 CONCLUSION

This Chapter has described why the NPI concept centres on improving coordination of existing and future CORS infrastructure, nationally, to increase access to positioning services. The business case for a NPI must reflect the direct and external benefits that coordination through a single point of access will enable for producers and consumers. Collaborative planning to create a single point of access will require a governance structure that brings together stakeholders from across government and industry to clarify roles, responsibilities and reporting mechanisms for discussing and negotiating national and international requirements for a NPI.

150

Early planning and policy work by ANZLIC, the ASC, and GA has opened communication between governments and industry. Technical, institutional and economic requirements must now be articulated in a way that informs the business case and subsequent development of a NPI. A new model (the NPI Planning Framework) for identifying and relating these coordination objectives is summarised through this research to support planning and implementation of Australia’s NPI.

151

152

CHAPTER 6 ACCESSING GNSS POSITIONING SERVICES: UNDERSTANDING THE ECONOMICS

ACCESSING GNSS POSITIONING SERVICES:

UNDERSTANDING THE ECONOMICS

6.1 INTRODUCTION

This Chapter identifies and evaluates economic criteria that influence supply and demand for CORS infrastructure and positioning services across Australia. Evidence of positioning coverage is combined with economic theories for information goods, economies of scale, network externalities, public goods, market competition and marginal utility, to demonstrate that the costs and benefits of deploying CORS infrastructure are not evenly distributed spatially.

No other research has established an economic context for communicating technical and institutional criteria for supplying CORS infrastructure and high accuracy positioning services. Economic studies have focussed on quantifying the macroeconomic value that high accuracy position information provides to the economy (The Allen Consulting Group, 2008, ACIL ALLEN Consulting, 2013), however limited focus has been given to addressing the microeconomic decisions made by suppliers of positioning infrastructure. Macroeconomic studies pay little attention to the economic inefficiencies that arise from duplication and a lack of standardisation in the national supply of CORS infrastructure.

This Chapter establishes a microeconomic context for interpreting and analysing technical, institutional and commercial decisions faced by suppliers of high accuracy positioning services, and describes the potential benefits that producers and consumers of position information can leverage from a single point of access to CORS infrastructure: the NPI.

6.1.1 RESEARCH RATIONALE

Chapter 6 revisits two key questions raised in Chapter 4: where do governments and industry deploy CORS in Australia; and how do they fund this infrastructure? This Chapter adds a why component to each of these questions by applying economic theory and reasoning to the technical (e.g., multi‐GNSS, positioning techniques, data formats, scientific research), institutional (space policies, geodetic responsibilities, funding models, custodianship) and commercial (data licensing, wholesale and retail distribution) supply challenges identified throughout this thesis so far (see Figure 57).

This Chapter does not quantify dollar values91 for the costs and benefits of deploying CORS infrastructure, but does identify the cost‐benefit decisions that will determine how a NPI can enhance the value of Australia’s high accuracy GNSS positioning market. Economics principles are therefore reviewed and applied in the context of producing, operating and distributing positioning services, which will guide future investment decisions by Australian governments and industry for establishing a NPI.

91 Dollar values for costs and benefits are approximated in some examples to demonstrate economic theories.

154

FIGURE 57: CHAPTER 6 RATIONALE

Chapter 6 defines and evaluates economic principles for relating and communicating the technical, institutional and economic concepts that are examined in this thesis for establishing a NPI.

6.1.2 ECONOMIC THEORY

The economics theory and analysis applied within this Chapter is introductory. The purpose is to develop economic context and structure rather than applying quantitative economic analysis. This Chapter does not implement a formal Cost‐benefit Analysis (CBA) but does articulate the various economic decisions a CBA should address for understanding where and how to supply high accuracy positioning services across Australia. Original knowledge is developed by defining and validating economic theories and models as they apply to producing, distributing and accessing GNSS position information.

6.1.2.1 BACKGROUND

Economics is a social science that studies how individuals, governments and companies make choices for allocating resources to support the production, distribution and consumption of goods and services (Frank et al., 2008). Economics theory is premised on the fact that society’s resources are scarce, meaning limited resources are available for supplying the goods and services that consumers demand. Economists study the decisions and interactions of buyers and sellers to determine how governments and businesses allocate scarce resources. Pareto efficiency occurs in a market when all resources are allocated in the most efficient way possible, therefore making it impossible for one individual to benefit without disadvantaging another (Frank et al., 2008). The concept of pareto efficiency is revisited

155 throughout this Chapter to evaluate production and pricing decisions made by governments and industry in the market for high accuracy positioning services.

Microeconomics is primarily focused on the decisions that affect supply and demand for goods and services within specific markets. These decisions influence the price, quantity and quality of goods that are produced and consumed in different markets. Macroeconomics on the other hand focuses on behaviours in the ‘aggregate’ economy including factors such as Gross‐Domestic Product (GDP), unemployment rates, interest rates, inflation, trade deficits, exchange rates and national budgets. Both fields of economics are interdependent given the aggregate behaviour of organisations and consumers in each market contribute to the overall state of the economy. Decision‐making at the macro level therefore affects decision‐making within individual markets (Mankiw, 2007).

Previous studies aimed at quantifying the macroeconomic value (measured in terms of contributions to national GDP) that is generated by Australia’s high accuracy GNSS market have primarily focussed on quantifying benefits to industries such as agriculture, construction and mining (The Allen Consulting Group, 2008). These benefits are quantified in terms of productivity gains and associated cost savings from reduced inputs, which increases value for users that can access positioning services. Section 6.3.1.6 explores these benefits in greater detail. The challenging task of quantifying benefits to user groups in the utilities, finance, and transport (road, rail, maritime and aviation) sectors has also been attempted by ACIL Allen Consulting (2013).

These macroeconomic studies primarily focus on demand‐side economics as opposed to analysing production decisions for optimising the supply of GNSS infrastructure that is needed to service this demand. Individual decisions made by consumers, governments and businesses, to produce, distribute and access positioning services, such as those analysed in a CBA, have received little attention in the public literature. Hence, limited research is available on the cost‐benefit criteria faced by individual governments and businesses for optimising the supply of their positioning infrastructure resources. Chapter 6 is therefore dedicated to establishing an economic context for interpreting, relating and communicating the technical, institutional and commercial decisions identified in Chapters 1 to 5 for supplying positioning services across Australia.

6.1.2.2 SPATIAL DATA & POSITION INFORMATION

A number of comparisons are made throughout this Chapter with ANZLIC’s Economic Assessment of Spatial Data Pricing and Access in Australia, which was completed in 2010 (PwC, 2010a, PwC, 2010b). The first stage (PwC, 2010a) comprehensively reviewed economic principles, issues and funding models for producing and distributing fundamental spatial data. The second stage (PwC, 2010b) evaluated these models using a CBA. Of relevance to this Chapter is the definition that:

156

“Fundamental spatial data constitute data about the location and attributes of features that are on, above or beneath the surface of the earth, that are captured from primary sources and, typically, cannot be derived from other data.” (PwC, 2010a)

According to this definition, GNSS positioning services constitute a primary source of position information that is captured to produce fundamental spatial data. For example, fundamental data includes the cadastre, roads, administrative boundaries, and other physical features, whose location and other attributes are recorded as spatial data, which is captured using high accuracy GNSS position information (note that raw spatial data according to the definition above is the high accuracy position information that is captured using high accuracy GNSS data corrections). This Chapter demonstrates similarities between the value chain for producing and distributing (i.e., supplying) spatial data in Australia, and the value chain for supplying high accuracy GNSS data corrections. Economic models for pricing and accessing fundamental spatial data are therefore used to compare pricing and access models for producing and distributing positioning services.

6.2 MARKET STRUCTURE & COMPETITION

A market is a group of buyers and sellers of a particular good or service. Businesses typically compete with one another on the price and quality of their products to earn profit and increase their share of a given market.

Developing a satellite positioning system requires access to different markets for space (e.g., satellites) and ground (e.g., GNSS receivers) resources. Combining these resources creates a highly diverse and competitive market for GNSS technology, which can be segmented by the differing needs of customers who demand access to PNT information (RAND Corporation, 1995). For example, GSA (2013) defines the GNSS market as the GNSS‐based products (receivers and other devices) and services that support markets for agriculture, transport, surveying, mining and Location‐Based Services (LBS).

This thesis evaluates supply and demand for high accuracy GNSS positioning services across these different segments of the broader GNSS market in Australia. To achieve this, economic pricing and access models for producing and distributing data corrections from positioning services as an information good must first be explored.

6.2.1 INFORMATION GOODS

Conventional goods and services are produced and consumed everyday including physical goods such as cars, computers, houses, GNSS receivers, and services such as haircuts, financial advice, and public

157 transport etc. Microeconomic theory analyses supply and demand criteria for these products to determine the quantity of each good that should be produced, and the price at which these goods should be sold based on all available resources (Mankiw, 2007, Frank et al., 2008).

However, modern economies dedicate considerable resources to producing information goods, which are defined by Krugman and Wells (2010) as goods whose value comes from the information they contain. Information is defined by Shapiro and Varian (1999) as anything that can be digitised, such as computer software (e.g., operating systems, programming tools, games), online services (e.g., Google, stock exchanges, customer support), and other forms of digital content (e.g., movies, television programs and music).

In markets for high accuracy position information, Hausler and Collier (2013a) identify that the actual product delivered to consumers is the digital information contained within the data correction message (e.g., RTCM data messages). Users typically purchase this data through a paid subscription to a government or industry positioning service. Early work by RAND Corporation (1995) defines GPS itself as a worldwide information resource, and similar information properties can be observed in the modern high speed data networks and mobile telecommunications networks that are commonplace today. A more recent US Government definition provided in Section 2.3.3 states that GPS is a global information infrastructure that establishes a free and open utility for accessing PNT information (GPS.gov, 2013).

However, no literature has been identified in Australia that explores the economic characteristics of supplying high accuracy GNSS data corrections as an information good. In particular, the market structures that drive competition for producing and delivering high accuracy data corrections in Australia are not well understood. Limited evidence is available for identifying and describing barriers to entry for supplying and therefore accessing positioning services. Hence, limited economic criteria have been defined for evaluating the decisions made by governments and industry to supply and differentiate their positioning services and the information they provide.

This Chapter evaluates public good and commercial decisions for supplying CORS infrastructure (an industrial good) as a fixed input for producing high accuracy data corrections (an information good). Maximising the utility of this correction information requires knowledge of the opportunity costs faced by producers and consumers, as described in the following Sections.

6.2.1.1 OPPORTUNITY COST

The opportunity cost of any item represents the value of an alternative item that is forgone in pursuit of the first item (Frank et al., 2008). Put simply, opportunity cost is what you lose by choosing one alternative over another. Every decision has an opportunity cost. For example, the opportunity cost of reviewing this thesis is the time that is forgone in completing one’s own research. If the knowledge gained by the reader outweighs the time lost, the benefit was worth the cost.

158

General assumptions can therefore be made regarding positioning services; a user with low opportunity costs for accuracy, but high opportunity costs for service coverage would use a national DGNSS service such as WAAS (not available in Australia) rather than a localised high accuracy NRTK service. Conversely, an agricultural user requiring ±2cm accuracy (95% confidence) for Controlled Traffic Farming (CTF) purposes has high opportunity costs for accuracy across their farming region, and low opportunity costs for national service coverage (i.e., WAAS).

Opportunity cost can therefore be used to analyse the value that consumers place on accessing high accuracy positioning services. Value can depend on a range of criteria including position accuracy, positioning techniques, service coverage, data formats, subscription costs and customer support options. SPs prevent users from substituting to an alternative service by differentiating their products to increase value for their customers. The service that offers most value is said to offer the highest utility.

6.2.1.2 UTILITY

Utility is an abstract concept that reflects the level of happiness or satisfaction a person receives from consuming a good or service (Mankiw, 2007). Buyers and sellers maximise their utility in an economy that is pareto efficient. The concept of utility underpins the notion of social welfare and is essential to understanding the law of demand discussed in Section 6.3.1.1. Put simply, goods and services that generate greater utility are more valuable to consumers, meaning buyers have incentive to pay a higher price. The additional satisfaction obtained from consuming an additional unit of a good is known as marginal utility (Section 6.3.2.4). Marginal utility typically decreases as more of the product is consumed, which decreases the demand price that consumers are willing to pay to purchase higher quantities of the product. Economists call this the law of diminishing marginal utility.

It follows that utility can be quantitative or qualitative, meaning it is difficult to measure and varies depending on a user’s opportunity costs. Economists study consumer behaviour as an indirect measure of utility, such as the price at which demand for a product is highest. For example, the utility of high accuracy position information will vary depending on the price and quality of the information, which influences the number of users that choose to access this information. The cost structure of producing position information is therefore critical to understanding the price and quality at which it is sold to consumers to generate utility.

6.2.1.3 COST STRUCTURE

Shapiro and Varian (1999) explain that information goods are costly to produce but cheap to reproduce. Put simply, the fixed‐cost of producing the first copy of information such as music or a piece of software can be very high, but the marginal cost of producing additional copies of the same good is typically negligible. Fixed‐costs do not vary with the quantity of output produced. For example, the fixed‐cost of

159 establishing positioning infrastructure includes the cost of GNSS equipment, network processing software, quality control software, ICT infrastructure, Data Centres (DCs), Human Resources (HR), property purchases and rent (i.e., for each CORS site), site upgrades, and wages, amongst other costs (see Section 3.2.1.1). The production of spatial data also exhibits a high fixed‐cost structure (PwC, 2010a).

Marginal cost is the change in total cost (or change in total variable cost) that results from a change in the quantity of output produced. Marginal costs increase if the variable costs of production increase with more output. For example, producing more GNSS receivers requires more inputs to construct each receiver. However, information goods, such as a digital music file can effectively be copied at zero marginal cost after the initial fixed‐cost investment. Hence, the marginal cost of producing one more subscription from a positioning service is very low; close to zero.

Whilst it can be argued that administrative and data bandwidth requirements for positioning services may reach capacity, therefore increasing marginal cost at some point in time, these costs are typically considered fixed in the short‐term given a set number of staff are paid a fixed wage, and a set quota of bandwidth can be purchased from an Internet Service Provider (ISP). Note that the cost of deploying CORS, or licensing access to additional GNSS receivers to expand service coverage, is still considered fixed in the short‐term in order to produce at least one data correction. In the longer‐term however, the division between fixed and variable costs becomes less clear as distribution and administrative costs are less certain. Staffing, energy, telecommunications, internet access and marketing are all examples of costs that can vary in the longer‐term depending on factors that are internal and external to the business. For example, the market price of energy may change requiring the SP to renegotiate their fixed‐term contract for a given period of time. Similarly, the SP may need to hire more staff to manage a larger network of users if market demand increases.

In light of previous discussions on utility and opportunity costs, this cost structure implies that information goods should be priced according to consumer value rather than production costs (Shapiro and Varian, 1999). For example, if the cost of producing (or reproducing) a piece of information is zero, pricing the good at a 20‐30% premium to this cost seems illogical. Industrial goods on the other hand are typically priced according to production costs, meaning companies that are more efficient (e.g., fewer inputs needed to produce the same level of output) tend to have lower production costs and can therefore price their products lower, or extract higher margins from each unit sold. The quality of the production process influences the quality of these industrial goods. Consumer value is therefore a demand‐side consideration and cost is a supply‐side consideration. Price is a function of both. If there is high demand for a good, price will be well above production costs.

Information is therefore classified as an experience good (Shapiro and Varian, 1999) meaning the value of information arises from its use (Arrow, 1959 cited in, Bates, 1990); consumers must experience the good in order to value it. Recent work by Jones and Mendelson (2011) compares quality and price

160 competition for industrial and information goods, highlighting that suppliers who produce the highest quality information are likely to capture a larger share of the market. This finding reinforces the notion that higher quality information is more valuable to consumers as it delivers higher utility.

The concept of Service Level Management (SLM) introduced in Section 4.2.2.5 identified key performance criteria (e.g., service uptime, data completeness, service availability and position accuracy) that influence the quality of a positioning service. It is important to note that different levels of SLM can impact a consumer’s decision on which positioning service to subscribe to. Service performance, which is guided by SLM procedures, can be optimised for different applications to increase value for consumers that are willing to pay a higher cost. GNSS positioning techniques, data formats, ICT systems, datum management strategies, multi‐GNSS compatibility, network size, network redundancy and customer support can all be used to differentiate service performance within a broader SLM framework. Hence, SPs differentiate their products by value‐adding to the raw GNSS data streams observed and processed from each CORS, in a similar way that PwC (2010a) describes how and why governments and industry value‐add to raw spatial data to produce fundamental spatial datasets. Competition within a market drives companies to differentiate their products, and different markets exhibit different levels of competition which characterises their market structure.

6.2.2 MARKET STRUCTURE

Market structures reflect the number of companies competing within a market, which shapes the pricing and production decisions of each business, and therefore the extent to which each business can influence market prices. Perfectly competitive markets are those in which many companies offer similar products meaning buyers and sellers have negligible impact on market prices; they are both price takers (Frank et al., 2008). As a simplified example, the market for milk is highly competitive given any dairy farmer can freely enter or leave the market to sell what is essentially the same product. Farmers must accept the market price for selling their milk or buyers will choose a competing supplier.

At the opposite end of the spectrum are businesses that are said to have a monopoly as the sole provider of a product for which there is no direct substitute. Monopolies are price makers as they have increased market power for controlling the price and quantity of the product that is sold. Monopolies create high barriers to entry that prevent other businesses from entering and competing within the same market given one business has sole access to the key resource that is produced and sold. No other business can compete with the monopoly’s scale of production.

Pharmaceutical companies often have a temporary monopoly on any new drugs they produce by applying for a government patent that assigns exclusive rights to manufacture the drug for a set period of time, after which the market becomes more competitive as new firms enter. Patent and copyright laws are said to offer higher incentive for research and innovation, such as the development of new

161 pharmaceutical drugs (Mankiw, 2007). However, the key problem with monopolies in the absence of price regulation is their ability to price above marginal cost in order to maximise profit without the need to increase production. The quantity produced and sold by the monopoly will be less than the socially optimum level of output demanded by society, which leads to deadweight loss.

Deadweight loss occurs due to an inefficient allocation of resources which delivers the monopoly higher profits, whilst reducing the supply made available to consumers who would otherwise have purchased the product at marginal cost (Mankiw, 2007). Markets with deadweight loss are not pareto efficient given one individual (the monopoly) has benefited at the expense of another (the consumer).

6.2.2.1 NATURAL MONOPOLIES & ECONOMIES OF SCALE

In some cases natural monopolies are created or encouraged by governments when the existence of multiple producers would be less efficient than if all production was assigned to a single firm. Hence, natural monopolies arise when one business can supply a good or service to an entire market at a lower cost than two or more firms (Mankiw, 2007). For example, to distribute water in a small town, a government or private company must first build a network of pipes and associated infrastructure throughout the town. If two companies were to compete, both would pay the fixed‐cost of building the water distribution network which would duplicate resources and lead to over‐investment. The average total cost (ATC) of supplying water is therefore lowest if a single provider builds the distribution network to serve the entire market as a natural monopoly. ATC92 is the total cost of production divided by the quantity of output (Figure 58). An organisation is said to have economies of scale when their ATC of production continually declines.

FIGURE 58: AVERAGE TOTAL COST CURVE

Economies of scale occur when ATC declines as output increases. A single organisation with economies of scale has a natural monopoly if it can supply a good or service to an entire market at a lower price than two or more organisations (Mankiw, 2007).

92 ATC is the sum of Average Fixed Cost (AFC) and Average Variable Cost (AVC).

162

Natural monopolies are characterised by the high fixed‐cost structure described previously for information goods. In theory, no other organisation can produce the same economies of scale as a natural monopoly without increasing ATC for all quantities of output. RAND Corporation (1995) identified that the marginal cost (leaving aside any effect on military utility) of serving additional users with civil signals from GPS93 is zero; however the economy of scale is not the physical size of the infrastructure, but the range, availability and reliability of its signal. Hence, unlike water and electricity networks, orbital positions in space are not so crowded as to prevent the entry of new satellite navigation systems. This concept has been proven by the entry of new GNSS systems that were described in Chapter 2.

This Chapter identifies and evaluates the economies of scale that a NPI will create by coordinating access to GNSS CORS infrastructure, thereby lowering cost‐barriers to producing and accessing high accuracy position information. Methods of pricing information are key to this discussion.

6.2.2.2 PRICING INFORMATION GOODS

ATC is a key concept for evaluating how the cost of producing each unit of information varies (Shapiro and Varian, 1999). Put simply, economies of scale mean that increasing sales volume decreases ATC (refer to Figure 58). This cost structure has consequences on the price at which information is sold, and the level of competition that exists within markets for information goods.

Firstly, it’s useful to compare the costs of producing information with the costs of producing conventional (industrial) goods such as cars and GNSS receivers. Reducing the ATC of production for conventional goods typically requires supply chain management and improved workflow to reduce per unit costs of parts, assembly and distribution. Cost savings then flow to the consumer and can increase profit from each unit sold. However, if the marginal cost of producing additional units of information is zero, businesses earn no revenue unless they price their information above marginal cost. Hence, information is typically priced at or above ATC to recover the initial fixed‐cost investment and earn profit where possible. Consumers who gain a lot of value (i.e. high opportunity costs) from accessing information are likely to pay a higher price. Hence, value‐based pricing naturally leads to differential pricing strategies (i.e., price discrimination) including personalised pricing (e.g., different prices for each customer), versioning (e.g., offering different product types or ‘lines’), and group pricing (e.g., group discounts) (Shapiro and Varian, 1999).

Positioning SPs often implement versioning and group pricing strategies. For example, GPSnet differentiates group prices for different sectors such as agriculture, surveying and construction, and versions information within these groups by selling different correction and data types (e.g., NRTK,

93 Refer to Section 6.4.3 for a discussion on the public good attributes of GPS.

163

DGNSS and single‐base RTK corrections, and raw RINEX data). Section 6.3.1.3 reviews horizontal and vertical differentiation strategies.

It follows that producers of information goods typically charge higher prices for higher quality information, such as data corrections that offer better accuracy and are delivered with greater reliability. The fact that information goods can be differentiated on price means that markets for information goods cannot function in the same way as highly competitive markets (e.g., the market for milk) in which all buyers and sellers are price takers (Shapiro and Varian, 1999). Hence, any market where producers can influence market prices cannot be perfectly competitive.

If information markets were perfectly competitive, price competition would drive prices toward the marginal cost of producing an additional copy (i.e., zero). For example, selling a data subscription for $100 is less viable than a competitor who can sell the same subscription for $99 and still earn profit. This concept underpins the Australian Government’s open data policy on Spatial Data Access and Pricing, which states that:

“As datasets become accessible over the internet, the marginal cost of transfer approaches zero. Therefore, all fundamental spatial data will eventually be made available free of charge” (Australian Government, 2001)

In the absence of perfect competition, providers of information goods differentiate price and quality to differentiate their products from competitors. However, the initial high‐fixed cost of producing information goods deters some organisations from entering the market in the first place given a large portion of fixed‐cost is not recoverable; it is a sunk cost (Shapiro and Varian, 1999). Natural monopolies are often subject to high sunk costs given few organisations have incentive to enter a market if an existing provider has already incurred sunk costs to achieve economies of scale. Hence, one organisation may be best placed to serve the entire market with the lowest ATC of production to avoid two businesses duplicating fixed‐cost investment. Indeed, many industries have cost structures that share these characteristics, including telecommunications organisations that spend considerable money laying cables, deploying cell towers and switchboards, and ensuring the system has sufficient capacity and redundancy to manage demand once operational. However, once the first signal is sent on the network, additional signals can be distributed at almost zero marginal cost.

The following Sections review the market structure and cost structure for supplying GNSS positioning services in Australia using comparisons with Australia’s NBN. These comparisons help to illustrate why markets for information goods exhibit monopolistic and competitive behaviour.

164

6.2.3 PRODUCING HIGH ACCURACY POSITIONING SERVICES

High fixed‐cost investment in CORS infrastructure is required regardless of the number of subscriptions that are produced within a positioning service. Purchasing a subscription effectively gives the user access to a copy of the data correction that is processed within the positioning service, although each correction is optimised (or ‘individualised’) for a user’s specific geographic location as a by‐product of the production process. Selling more subscriptions therefore reduces the ATC of producing each data correction. However, the fact that SPs can license access to raw data from CORS sites without having to purchase each CORS helps to lower fixed‐costs, therefore encouraging more SPs to enter the market. A similar theory applies to the Australian Government’s decision to fund the NBN; build the infrastructure and telecommunications providers (amongst others) will compete to deliver services on the NBN by licensing access to the network. Hence, the NBN network provides a single point of access that service providers can leverage to offer different packages and bundles of services such as voice and data.

The NPI concept is premised on the same theme – establish a positioning infrastructure that provides national access to a consistent standard of GNSS infrastructure and raw GNSS data, which positioning SPs and many other users within government, research and industry can access to produce data corrections and a host of other value‐added goods and services.

In fact, networks of CORS already exhibit natural monopoly characteristics in parts of Australia. For example, Table 10 in Section 4.3.2.4 identified that the VIC Government’s GPSnet is the data custodian for over 100 CORS sites across VIC and provides 100% high accuracy positioning coverage across the State. The natural monopoly characteristics of GPSnet are exemplified by the fact that industry SPs license access to data streams from the VIC Government rather than deploying their own CORS, which would otherwise lead to duplication and over‐investment and increase the ATC of producing each correction.

6.2.3.1 DATA LICENSING & MARKET COMPETITION

The market for producing high accuracy positioning services (i.e., information goods) is however competitive in many parts of Australia. For example, third‐party SP’s license data from GPSnet in VIC and differentiate their price and quality of service by value‐adding to this raw GNSS data. In contrast to the NBN, the infrastructure provider (GPSnet) does compete in downstream wholesale and retail markets, but operates on a cost‐neutral business model by pricing at ATC, and receives compensation through data licensing royalties which may compensate for any loss of customers. Data licensing therefore reduces the fixed‐cost of producing data corrections, which translates to cost savings for consumers who benefit from the presence of multiple industry SPs that compete on price and quality to secure market share. Chapter 4 also identified that the VIC, NSW and QLD Governments are shifting their

165 responsibilities away from service delivery to focus on back‐end management of positioning infrastructure that industry SPs pay to access.

To illustrate the benefits of this data licensing model, consider the case where an individual SP has a natural monopoly as the owner and data custodian for the entire supply of CORS infrastructure within a geographic region. The SP would have a natural monopoly that creates cost barriers to entry for other SPs who have limited incentive to deploy a duplicate network for supplying high accuracy positioning coverage across the service region. If however the data custodian allows third‐party providers to license its raw data streams, multiple SPs can enter the market to produce high accuracy positioning services. Governments can regulate the need for data licensing if the custodian is extracting monopoly profits and controlling supply. Allowing more companies to enter the market stimulates competition for improving service performance and quality, and promotes innovation for new data products and applications, thus increasing value for consumers. The role of government in regulating monopoly markets is further addressed through discussions on public policy in Section 6.4.

Data licensing therefore increases competition for supplying data subscriptions (i.e., information goods) and the ATC of producing each subscription is cheapest when no additional CORS are deployed. In other words, an SP’s ATC of producing data corrections within a positioning service would be lowest if they do not need to deploy additional CORS beyond those supplied by the licenser. The same theory applies to minimising the ATC of producing fundamental spatial data by assigning one firm responsibility for capturing raw data, given one dataset can be copied at marginal cost rather than duplicating data capture (PwC, 2010a). Similarly, two organisations would duplicate fixed‐costs if they deploy CORS infrastructure within the same region.

If however a SP chose to deploy and control its own duplicate CORS network, the same SP has greater flexibility in varying the physical location of each CORS compared with owners of other types of natural monopoly infrastructure. For example, the unnecessary waste of duplicating a power utility network to provide two independent power connections at each individual house is self‐evident; the consumer only requires access to one network. The flexibility to vary the location of CORS may therefore allow a SP to provide some level of product differentiation in terms of service performance which ultimately attracts more customers. A similar example was provided in Section 6.2.2.1 to identify why satellite providers are less affected by traditional easement issues regarding the location of their physical assets in space. However, so long as the cost of licensing access to CORS data is cheaper than deploying new infrastructure, the fixed‐cost of operating a network containing duplicate infrastructure must be higher. It is unlikely data licensing costs will exceed the high fixed‐cost of establishing a CORS site.

SPs that do deploy additional (duplicate) CORS would need to absorb or offset the costs of deployment from another part of their business, or identify users that are willing to pay a higher cost to access the network. The price‐driven nature of consumers in the GNSS market described in Section 6.3.1 suggests that users will substitute to the cheapest product unless there is a vast difference in Quality of Service

166

(QoS). In some cases, Australian users are unaware that cheaper services exist due to a lack of knowledge about the broader GNSS market beyond their affiliation with local DSPs who sell subscriptions on behalf of a SP.

6.2.3.2 PERFORMANCE STANDARDS

It follows that performance standards can influence pricing decisions for supplying position information in a similar way that pricing and access models for fundamental spatial data allow end users to signal the quality of data that they value most (PwC, 2010a). Performance standards primarily relate to SLM criteria for position accuracy, data availability and overall quality assurance procedures (see Section 4.2.2.5). For example, a full cost‐recovery model for spatial data (i.e., data priced at ATC) would allow land information agencies to direct their efforts and resources towards producing and optimising product lines that are most valued by consumers based on their consumption patterns (PwC, 2010a). Similarly, a positioning SP who differentiates prices for accuracy, availability (e.g., percentage of uptime) and quality assurance (e.g., quality control software and fault detection systems) can determine which performance standard users value most. VARs therefore have incentive to innovate processing strategies that maximise service performance in the most efficient and cost‐effective way.

If a SP develops a new processing technique (e.g., RT‐PPP) that requires fewer CORS to produce the same or better levels of service performance, they could simply license fewer data streams from a third‐ party data custodian and decrease their ATC of production. If the data custodian does not upgrade and maintain the quality (e.g., Tier) of CORS infrastructure needed to support this new multi‐GNSS technology (e.g., new signals and data formats) the SP may deploy a duplicate network or part thereof to maximise competitiveness. The modernised network may ultimately supersede the data custodian’s original network, which again raises issues of duplication that could potentially have been avoided if CORS infrastructure had been operated and maintained to a consistent national (i.e., NPI) performance standard. Australia’s NBN provides a useful comparison given the new fibre‐optic network will be established as a natural monopoly, but will inevitability be contested by new wireless technologies that offer comparable speeds at lower ATC. Furthermore, some customers may not require the coverage and speed provided by the NBN and will settle for substitute wireless technologies. However, the network effect described in Section 6.2.4 implies that the value of the NBN to one user will increase as other people begin to develop and access services on the NBN. Hence, as interconnection via the NBN backbone becomes ‘the standard’, wireless and fibre technologies will be viewed as complements rather than substitutes. Price competition ‘within the market’ will drive innovative approaches for delivering services on the NBN as opposed to driving competition ‘for the market’ by establishing wireless networks that operate independent of the NBN.

The licensing arrangements implemented by VIC and NSW provide a useful example of why data are priced to account for maintenance and upgrade costs and to cater for the natural life cycle of each

167

CORS, and to provide an authoritative source of CORS data. Applying these State‐based examples and NBN comparisons on a national scale implies that establishing a NPI as a natural monopoly is potentially the cheapest way of standardising infrastructure quality and minimising the ATC of accessing raw data. Commercial innovation and competition in downstream wholesale and retail markets will follow.

Three key points can be summarised from the previous discussion regarding production costs, competition and performance criteria for supplying CORS infrastructure and positioning services:

i. The market for supplying high accuracy positioning services in Australia exhibits natural

monopoly characteristics given that individual data custodians control supply in some geographic regions.

ii. SPs can reduce their ATC of producing data corrections by licensing data, which overcomes the high fixed‐cost of duplicating CORS infrastructure.

iii. SPs differentiate their price, accuracy, service coverage and service performance to market value‐added services and therefore earn higher returns.

These findings inform the market‐based supply discussions evaluated throughout this Chapter, beginning with the following case study that demonstrates why data licensing in VIC effects the price at which subscriptions are sold in downstream retail markets.

6.2.3.3 CASE STUDY 2 – PRICING GOVERNMENT & INDUSTRY POSITIONING SERVICES

The following cost estimates and time periods have been developed for illustrative purposes only and do not represent true values. The relative cost difference in investment between government and industry providers is the key focus.

Total capital investment in the VIC Government’s GPSnet is estimated at $10 million, a significant portion of which was allocated through the Positioning Regional Victoria (PRV) Project in 2008 (DEPI, 2013a). Operational costs are estimated at $650,000 per annum, including wages, electricity, rent, data bandwidth, telecommunications, maintenance contracts and software licensing. Using 2008 as the baseline year from which investment in a State‐wide network commenced, fixed investment over a five‐ year period to 2013 can be calculated at $13.25 million. The marginal cost of producing each additional subscription is considered zero and NRTK subscriptions are the only product offered by GPSnet in this example.

If 500 NRTK subscriptions were sold each year between 2008 and 2013, the ATC of producing each subscription would equal $5300 (Figure 59a). Given GPSnet operates according to competitive neutrality guidelines, subscriptions are priced at ATC in order to recover fixed‐cost investment.

168

FIGURE 59A AND 59B: GOVERNMENT & INDUSTRY ATC CURVES

Figure 59a. Theoretical ATC curve for producing Figure 59b. Industry providers can lower their

subscriptions from the GPSnet service. ATC of producing each subscription by licensing data from GPSnet.

An industry SP also operates a NRTK positioning service in VIC by paying a 30% royalty on all revenue in return for access to raw data from all CORS sites in the GPSnet network. The industry provider also funds 10 additional CORS. The data licensing arrangement with GPSnet significantly reduces fixed‐cost investment to approximately $3 million over a five‐year period for the industry provider. Figure 59b illustrates that the industry provider’s ATC of producing 500 subscriptions per annum for five years would cost $1200. If however $5300 was considered the market price, the industry provider would earn $4100 profit from every subscription sold, which equates to approximately $10.3 million profit (shaded grey in Figure 59b) over five years for 500 subscriptions. However, 30% of all revenue is paid to GPSnet at a total cost of just under $4 million over five years, which reduces total profit to approximately $6.3 million.

However, the industry provider recognises that lowering its subscription cost will attract more customers and potentially lead to higher profit. At a lower subscription price, some users substitute from GPSnet, and the industry provider searches for new customers in different industry sectors including those with users that currently operate using single‐base RTK equipment. The industry provider prices each NRTK subscription at $4000 and attracts 850 users each year, 200 of which have substituted from GPSnet. Total profit (shaded green in Figure 59b) subsequently increases to $8.9 million after paying $5.1 million in royalties to GPSnet. The $5.1 million royalty could be used by GPSnet to recover part of its fixed‐cost investment, meaning GPSnet could potentially lower its subscription price. However, with only 300 subscriptions now sold per annum, its subscription price would increase slightly to approximately $5430 if the remaining $8.2 million fixed‐cost was to be recovered within a five‐year period. GPSnet may therefore need to charge a lower subscription price over a longer period than five years in order to preserve its client base and generate enough revenue to offset its initial investment.

169

It should also be noted that total fixed‐cost investment by GPSnet includes a level of public funding that does not need to be repaid; it is a sunk cost. This investment may be justified on geodetic grounds given GPSnet also supports management of the datum in VIC. Eliminating this ‘public good’ investment from the ATC calculation would help to reduce the subscription price that GPSnet charges to recover fixed‐ cost. The resulting subscription price would also be influenced by the time period for which GPSnet is expected to operate as a commercial positioning service.

It follows that although some users identify value in substituting to the cheaper industry positioning service, GPSnet’s remaining 300 users may not be driven by subscription price alone. For example, GPSnet may offer a more rigorous Service Level Agreement (SLA) that provides a user with more confidence in GPSnet’s service performance and offers warranties and compensation options in the event of any major service disruption. Existing users may also own equipment that is more compatible with the correction information provided by GPSnet. This point highlights why information goods should also be priced according to consumer value. Similarly, the industry provider can price higher than ATC given price signals in the current market suggest that consumers are willing to pay a higher cost. Put simply, SPs identify a price at which the benefits to consumers (e.g., productivity improvements, safety) outweigh the cost of purchasing subscriptions.

To illustrate this point, consider the case where the industry provider charges $2000 per subscription and subsequently attracts a client base of 5000 users per annum, meaning total revenue increases to $50 million. Fixed‐cost investment for this network is estimated at $4 million to cater for the additional staffing and infrastructure resources needed to service more users. The ATC of producing each subscription would decrease significantly to $160 calculated over a five‐year period, meaning profit would increase to $31 million after accounting for GPSnet royalties and repaying initial investment. The $15 million royalty would therefore cover the fixed investment needed to establish GPSnet without the need to sell any subscriptions. GPSnet could therefore focus its resources on operating and maintaining ‘back‐end’ infrastructure whilst leaving the responsibility of service delivery to the industry provider.

If more than one industry provider entered the market in VIC by also licensing data from GPSnet, both providers would differentiate their products to market their value to consumers. Value in this case may result from price competition, but also stems from improvements in SLM and the incentive for each provider to diversify their product range by bundling NRTK subscriptions with other applications such as quality control software to attract more customers. Value‐added features could be customised for specific user groups, such as those from agriculture and construction industries. Ultimately, investment decisions by each provider depend heavily on identifying the accuracy, coverage and service performance that consumers demand at different prices.

170

6.2.3.4 OLIGOPOLISTIC COMPETITION

It has been demonstrated that positioning SPs function in monopolistic and competitive ways. A SP can have a monopoly on the supply of data corrections within a specific geographic region and can also compete directly with SPs in other regions. The same is true of pharmaceutical companies who have a temporary monopoly on a new drug, but compete with other drug companies in the broader pharmaceutical industry. Krugman and Wells (2010) highlight that most industries fall somewhere between the two extremes of perfect competition and monopoly. Suppliers within these industries have competitors, but at the same time do not face so much competition that they are price takers. This type of imperfect competition is known as oligopoly (Mankiw, 2007, Frank et al., 2008, Krugman and Wells, 2010) which characterises the market for supplying positioning services in Australia.

Oligopoly is a market structure in which only a few sellers offer similar or identical products (Else and Curwen, 1990). Importantly, the actions of one seller can have a large impact on the business decisions of all other sellers, meaning oligopolistic firms are interdependent in a way that competitive firms are not. Production and pricing decisions in the market for supplying high accuracy positioning services are oligopolistic in nature, including the tension between cooperation and self‐interest, which ultimately influences the level of high accuracy positioning coverage that is supplied. A primary example of this interdependence was provided in the network expansion case study in Section 4.3.3 which explored the trade‐off between deploying a new CORS site and licensing data from existing providers.

Shapiro and Varian (1999) highlight that in the absence of price competition for production efficiency (due to a zero marginal cost structure), product differentiation is crucial for competing with organisations that produce the same ‘kind’ of information. The organisation must find novel ways to value add to the raw information as a means of increasing their market share. Product differentiation therefore helps to lock‐in customers by raising the cost of switching to an alternative product, meaning switching costs and lock‐in are ubiquitous in all information systems (Shapiro and Varian, 1999). For example, Microsoft Corporation has been highly successful at locking users to the Windows Operating System given most consumers have used Windows since purchasing or accessing their first computer. The time and effort needed to learn an alternative software package increases a consumer’s switching costs. The company Apple Inc94. retains an aggressive lock‐in strategy across its entire product range by developing proprietary hardware and software that is ‘closed’ from other systems to limit interoperability and compatibility outside of the Apple brand.

The same is true of GNSS manufacturers who develop proprietary data formats that cannot be decoded by third‐party receivers. Network processing software developed by the manufacturer can be optimised to receive and distribute data using these proprietary formats. For example, data corrections from a positioning service can be output in a specific format designed for specific types of GNSS receivers

94 Incorporated.

171 within an individual brand. Whilst data corrections from the same positioning service may also be distributed in an open and standardised format (e.g., RTCM) for use in any brand of receiver, the proprietary format can be optimised to deliver additional features that are only accessible using a specific brand of receiver. Developing commercial network processing software is therefore an effective way for manufacturers to sell their complementary GNSS receivers. Section 4.2.4 provided evidence of this approach by identifying that local distributors of GNSS equipment often function as, or partner with SPs for the same brand of network processing software.

Irrespective of data format, product differentiation may simply reflect a SP’s ability to network high accuracy data corrections across jurisdictional borders by licensing data from multiple data custodians (see Section 4.3.2.1). Competition within these geographic regions leads to further differentiation by promoting new application modules (e.g., atmospheric modelling programs) for quality control and non‐ positioning applications (i.e., weather prediction). Differentiation can also be achieved by increasing network redundancy and flexibility for data storage and analysis to improve processing capacity and efficiency (e.g., cloud‐based ‘virtual’ servers that can be managed ‘remotely’), and by continuously refining processing techniques and data formats (e.g., RTX, VRS, MAC, FKP). The physical stability of each CORS and their technical capabilities are also differentiating factors that affect service performance and reliability, including the standard (e.g., Tier) to which the infrastructure has been deployed, and the signal tracking capabilities of each GNSS receiver (e.g., number of satellite channels, noise filtering techniques).

At the user level however, most consumers simply want assurance that their positioning service will be available when they need it and that the information they receive can be trusted. These user expectations can be traced through time to the inception of GPS (RAND Corporation, 1995, US Department of Commerce, 1998, The Allen Consulting Group, 2008, European Commission, 2011). Many users aren’t familiar with the complex technical attributes that differentiate positioning services, meaning users simply demand well‐defined service performance metrics that guide them in choosing the service that best suits their application(s). Here lies the importance of SLM for measuring and marketing service performance (and therefore value to consumers) using quantitative and qualitative criteria.

SPs can formally document their responsibilities to users by specifying performance targets within a Service Level Agreement (SLA). SLAs specify all the characteristics of the service including responsibilities, guarantees, warranties, locations, costs and times which can be measured against Key Performance Indicators (KPIs) (Wustenhoff, 2002a). SLAs are therefore useful for communicating in plain language the features of a positioning service that differentiate it from competitors. Hence, the provision of SLAs, and the extent to which they differ from competitors in response to user expectations, are both forms of product differentiation that can influence the subscription price charged by SPs. In an oligopoly market, such as that described for Australia’s positioning market, there is strong

172 incentive to differentiate service performance using SLAs. SPs who can certify their CORS infrastructure (e.g., Regulation 13 Certificates) and QoS according to national standards (e.g., APREF and future NPI criteria) can promote additional value to consumers.

If consumers favour the information produced by one positioning service over the performance of another, the value to each user of accessing the most popular service is likely to increase as more users subscribe. For example if increased market demand for one service leads a SP to extend service coverage, the value to every user is enhanced by having greater access to a broader service coverage region. This is known as the network effect.

6.2.4 NETWORK EFFECTS

When the value one user places on a product is influenced by how many other people are using that product, the product exhibits network effects or network externalities (Shapiro and Varian, 1999, Krugman and Wells, 2010). As a simple example, people use Microsoft Windows because other people use Microsoft Windows. Externalities arise when one market participant engages in some form of activity that effects the well‐being of others, but neither party pays or receives compensation for that action (Mankiw, 2007). Hence, the size of an externality is influenced by the size of the network affected by the externality.

Fax machines are often used to conceptualise network effects. A fax machine derives its value from the fact that a user can directly send and receive information with other people who own fax machines. Adoption rates for fax machines soared throughout the mid‐1980s meaning the direct value to each user increased as the network of users increased. However, indirect connections also create important externalities. For example, Krugman and Wells (2010) highlight that the dominance of Microsoft Windows is self‐reinforcing: Windows users get help and support and can share files with friends and colleagues who also use Windows. The Operating System is so widely used that software developers are encouraged to develop programs that run on Windows.

The same theory applies to a SP who seeks to increase the network of users connected to their positioning service. Firstly, increasing the customer base may lead to increased service coverage, which can benefit all users. Secondly, switching costs increase as more users become familiar with one service, meaning they are less likely to substitute and more likely to recommend their chosen service to colleagues. Thirdly, the data formats and processing methodologies associated with the dominant service become more widespread, which encourages users to purchase complementary GNSS equipment and software products, and encourages the market to adopt this service as ‘the’ standard.

Shapiro and Varian (1999) and Krugman and Wells (2010) highlight that technologies which are subject to strong network effects tend to exhibit long lead times followed by explosive growth where more people suddenly find adoption worthwhile; a pattern known as positive feedback. After a period of slow

173 growth, the network eventually reaches critical mass and takes over the market. Consumer expectations are therefore critical given the network that is expected to become the standard often will become the standard. Tipping occurs when positive feedback due to network externalities causes consumers to adopt one of two or more competing technologies as the standard (Krugman and Wells, 2010).

The change in quantity of the product that is demanded over time can be mapped to illustrate the slow growth that occurs until critical mass is reached, after which the rate of adoption grows quickly. Adoption curves for new technology are often referred to as ‘S‐curve adoption paths’ (Rogers, 2003). Of key relevance to this study is the conceptual S‐curve applied by The Allen Consulting Group (2008) to model adoption rates (Figure 60) for high accuracy GNSS technology in the agriculture sector over a 20‐ year period up to 2030.

FIGURE 60: S‐CURVE ADOPTION PATHS

Adoption profiles for uptake rates of CTF and Inter‐Row Sowing (IRS) in cropping regions across Australia with and without a standardised national high accuracy positioning network (The Allen Consulting Group, 2008).

The lower adoption curve shown in Figure 60 presents a ‘base case’ in which future growth in high accuracy GNSS positioning services occurs according to today’s ‘organic’ market structure comprising independently owned and operated positioning services. The upper adoption curve is an assessment of the productivity gains that would potentially result if a standardised national network of CORS was established through a coordinated approach similar to that proposed through the NPI concept in Chapter 5. Both curves represent total uptake of high accuracy GNSS technology in the agriculture (CTF) sector, meaning each curve can be interpreted as the entire market for positioning services within this sector as opposed to adoption rates for a specific government or industry SP within this sector.

174

Section 6.3.1.6 summarises the macroeconomic productivity gains associated with these uptake curves as a percentage of GDP, but the key message from Figure 60 is that the Australian market for high accuracy positioning services exhibits network effects. The lower curve exhibits positive feedback given adoption rates grow regardless of how compatible and interoperable each ‘organic’ positioning service is in the absence of any national approach to coordinating access (e.g., through data licensing) and service standards (e.g., SLAs). Organic growth will however increase switching costs when networks are operated independently and users must choose the service that best fits their application and existing product range. If multiple SPs are successful at locking‐in users, which embodies the current approach by SPs in the Australian market summarised in Section 4.2, Figure 60 implies that it is unlikely one industry provider will tip the market to deliver the economies of scale needed to establish a national network as the standard.

The upper curve therefore reflects the natural monopoly characteristics described previously where a standardised network such as GPSnet could be rolled out across the whole of Australia. Regardless of whether the standardised network is owned by one or multiple stakeholders, and whether downstream markets for delivering positioning services are made competitive through data licensing, the upper curve implies that industry users see greater benefit from connecting to a larger network than a smaller one. As the network becomes more standardised in terms of infrastructure quality, data formats, SLM, price and access conditions, the network of complementary value‐added hardware and software that is compatible with the standardised network will grow, therefore increasing value for all users who access ‘the’ national network. In this case, economies of scale are not just driven by how cheap each subscription can be supplied (given marginal cost is negligible), but by the extent to which positive feedback increases the value of, and therefore demand for a standardised national network. Network effects are often referred to as demand‐side economies of scale for this purpose. Demand‐side economies of scale continue to increase as more users join the network.

In light of ANZLIC’s NPI Policy (2010), standardisation and compatibility are key to building demand‐side economies of scale by inter‐connecting existing and future infrastructure. However, generating positive feedback through interconnection depends on the level of open or controlled access that is enabled by each SP.

6.2.4.1 DATA STANDARDS: OPEN VERSUS CONTROLLED ACCESS

For positioning services, access typically depends on whether data corrections are distributed in an open standard or proprietary (i.e., closed) format, and whether users can be excluded from accessing the service altogether. Excludability is a key concept explored in Section 6.4 regarding free‐ridership problems related to public goods. Openness and control are key concepts in the face of high network effects given the value of a network is highly dependent on how many people can access the network.

175

RTCM‐3.1 for example is an open data standard that most brands of GNSS receiver are compatible with. However, most manufacturers also develop proprietary data formats that are used to optimise correction information for a specific brand of receiver. Whilst most GNSS receivers are capable of processing different NRTK positioning techniques such as VRS and MAC using RTCM‐3.1, proprietary formats can still be used to enhance each positioning technique. Regardless of data format, commercial SPs exclude users who have not purchased a subscription by assigning registered users the necessary credentials for accessing data via an NTRIP caster.

Public SPs in Australia such as AMSA provide free access to their data by broadcasting radio signals without the need for registration. GA also provides free access to its raw RTCM‐3.1 data streams via NTRIP but requires user subscriptions to monitor usage.

It follows that a SP’s network of users is significantly diminished if they limit access to one brand of receiver. Open data standards such as RTCM build demand‐side economies of scale that maximise value for consumers and therefore grow the network of users. Furthermore, SPs and data custodians require a common data format to share data that they have licensed to one another, which reflects the interdependent nature of businesses that operate in oligopoly markets. For example, if one SP dominated the entire market for positioning services, proprietary control through data formats and exclusion strategies would be extremely valuable to the SP that has complete control over who connects to their network. In oligopoly markets however, data licensing and competition encourages the use of non‐proprietary formats, meaning a SP who exerts too much proprietary control over data access will suffer in the presence of strong network effects for open data, particularly if users fear vendor lock‐in to one brand of receiver.

SPs should choose the strategy that maximises value rather than the strategy that maximises control, which often means sharing some level of value with competitors (Shapiro and Varian, 1999). Data sharing helps to generate demand‐side economies of scale for accessing high accuracy positioning services by exposing a range of users to data offered by different SPs. Furthermore, a company that adopts an open data strategy can still control changes to the technology (e.g., by integrating new multi‐ GNSS features into their network processing software) after securing a broad user base, which increases switching costs (therefore benefiting the network operator). There is no individual SP that controls the data standard, and therefore the market for supplying high accuracy data corrections in Australia.

A useful formula for understanding the rewards from building awareness and support for an information good through sharing arrangements, whilst also retaining some level of competitive advantage through controlled product differentiation is given by Shapiro and Varian (1999):

FORMULA 1: BALANCING REWARDS IN INFORMATION MARKETS

176

Formula 1 implies that in the presence of strong network effects, the inherent value of information will depend on how widely it is adopted by industry (i.e., the value added to industry), which in turn influences the size of a company’s market share (i.e., share of industry value) . Put simply, a provider can have a large share of a small market (through proprietary control), or a small share of a large market (through open access) (Shapiro and Varian, 1999). Unless a new technology truly dominates a market, maximising value requires some degree of sharing with competitors to fuel positive feedback. Formula 1 can therefore be used to map the trade‐off between openness and control as shown in Figure 61. The optimum balance in Figure 61 can be considered a pareto efficient outcome when rewards are maximised for buyers and sellers.

FIGURE 61: OPEN & CONTROLLED ACCESS

The trade‐off between openness and proprietary control impacts the size of an organisation’s market share (adapted from Shapiro and Varian, 1999).

From the evidence presented in this thesis so far, Australia’s high accuracy positioning market most likely sits below the optimum curve towards the left hand side of the graph in Figure 61. Whilst most SPs stream data in open RTCM format, no single provider enables access to the full 8.4% service coverage region. This lowers value for users (value added to industry) given multiple subscriptions must be purchased in different locations across Australia, and therefore decreases each SPs share of industry value. Furthermore, the fact that the market for positioning services only covers 8.4% of Australia means that greater rewards could be achieved if service coverage is extended to a level that is ‘optimum’ (e.g., national).

One developing technology that has the potential to deliver greater compatibility and access across Australia with the same level of high accuracy performance is the RT‐PPP technique introduced in Section 3.4.3.1 and further explored in Section 6.3.3.1. Firstly, the implications of using RT‐PPP as a method of increasing access and therefore value to producers and consumers of high accuracy positioning services is analysed in relation to the new IGS RTCM‐SSR data standard.

177

6.2.4.2 IGS DATA STANDARDS: IMPLICATIONS FOR AUSTRALIA’S NPI

The IGS motive for providing free access to non‐proprietary RTCM‐SSR data was briefly introduced in Section 4.4.6.2 and is made clearer by previous discussions on network effects. Encouraging manufacturers, governments, researchers and other businesses to integrate authoritative RTCM‐SSR orbit and clock data into their goods and services will increase the network of users who access these GNSS data products, thus entrenching IGS real‐time PPP products as a global standard.

The IGS is already recognised as an authoritative source of orbit and clock products, which establish global standards for post‐processing GNSS data. These products are derived from the IGS global tracking network of CORS infrastructure, which is built according to best practice guidelines as a global standard for infrastructure quality. Free access to post‐processed IGS data is justified on the grounds that substantial public benefits derive from the scientific, educational and commercial applications that these products enable. Public benefits increase as the network of users increases. The IGS has now responded to increased demand for real‐time orbit and clock products by developing its real‐time service (IGS, 2013d). Encouraging all manufacturers, governments and research communities to integrate these products at the beginning of their supply chains provides a method of controlling the quality that is expected in downstream user markets for GNSS information. Hence, open access provides a means of becoming ‘the’ standard for data formats and infrastructure quality.

Critically, IGS real‐time data products are designed to complement, not compete with goods and services produced by commercial manufacturers and SPs. Rather than having multiple government and industry providers duplicate investment in the global data infrastructure and processing resources needed to produce real‐time orbit and clock data, the IGS provides an institutional mechanism for pooling these resources in a multi‐layered, highly redundant system architecture. Hence, the IGS is one of few organisations that can deliver the economies of scale needed to meet the future positioning demands of a global user community, including the need to quality assess multi‐GNSS constellations. In fact, the IGS provides access to these products at a marginal cost of zero. In other words, industry can substantially reduce fixed‐cost investment by accessing IGS products free of charge and therefore focus attention on differentiating the value they add to downstream users.

Current efforts by companies such as Trimble to develop an independent RT‐PPP service by developing their own orbit and clock products will provide an interesting case study in the future for identifying which approach (i.e., open or controlled standards) ultimately builds the largest network of users. The author’s experience suggests that open data standards will prevail.

The same concept of developing uniform standards to produce fundamental orbit and clock datasets is a key argument for developing a NPI. The NPI would deliver the economies of scale needed to create a single point of access to authoritative (i.e., fundamental) open‐source data that stimulates competition for developing innovative value‐added services in downstream user markets. The question remains as to

178 whether or not the Australian Government should play an active role in delivering positioning services from the NPI. Prior to addressing this question through discussions on public policy, the economic efficiency of Australia’s current high accuracy positioning market must be evaluated. The following Section applies the market‐based production and pricing concepts developed in Section 6.2, to interpret the geographic, scientific and commercial supply and demand evidence provided in Chapter 4.

6.3 SUPPLY AND DEMAND FOR POSITIONING SERVICES IN AUSTRALIA

Chapter 4 identified geographic locations where high accuracy service coverage has been enabled, and evaluated the scientific and commercial business drivers that were used to justify these investments. Table 8 and Figure 32 provided numerical and spatial evidence, respectively, that some State and Territory governments have been more successful at justifying investment in CORS than others. Table 9 and Figure 36 demonstrated the market‐driven investment response from industry.

The supply evidence identified above implies that the benefits and costs of deploying CORS infrastructure are not evenly distributed across Australia. This Section establishes economic context around the cost‐benefit decisions that governments and industry use to evaluate investment opportunities. The cost structure and market structure for producing high accuracy data corrections are used to evaluate how economically efficient investment in positioning infrastructure has been across Australia in response to user demand. Issues of deadweight loss resulting from duplication and overinvestment are subsequently identified to explore the role that a NPI can play towards minimising these economic inefficiencies. The role of public policy in facilitating greater coordination is explored in Section 6.4.

6.3.1 DEMAND

Economics theory on the law of demand is firstly reviewed and then applied in the context of high accuracy positioning services in the following Sections.

6.3.1.1 BACKGROUND THEORY

The law of demand (Else and Curwen, 1990, Mankiw, 2007, Frank et al., 2008) states that, all other things being equal (‘ceteris paribus’), the quantity of a good that is demanded by consumers will increase as its price decreases. Demand for a product depends on the quantity of a good that consumers are willing and able to purchase, which is dictated by their opportunity costs. The demand curve is used to map the relationship between price and quantity, ceteris paribus, as demonstrated in Figure 62a.

179

FIGURES 62A AND 62B: DEMAND CURVES

Figure 62a. The law of demand states that, Figure 62b. Any change other than price ceteris paribus, the quantity demanded that raises or lowers the quantity that increases as the price of a good decreases. buyers wish to purchase at a given price

shifts the demand curve.

A movement along the demand curve in Figure 62a is the direct result of a change in price, while any factor other than price will shift the position of the entire demand curve as demonstrated in Figure 62b. Factors other than price include consumer tastes and preferences, income rates, buyer expectations (e.g., predicting future prices), product quality and the price of other goods, such as substitute products that consumers may switch to, or complementary products whose prices can influence demand for other products (e.g., cheaper GNSS receivers can increase demand for positioning services).

For example, without any change in price, demand for GNSS‐enabled smart phones may increase as the quality of these devices and the applications they enable (e.g., social networking, banking, navigation) become more valuable to consumers, thus shifting the demand curve right. Further value is generated as the network of smart phone users increases. Over time however, each phone manufacturer will compete for more customers, leading to price‐competition, which also increases the elasticity of the market demand curve. Elasticity is the change in quantity that is demanded as a result of changes in price. Demand for a product is highly elastic if a small change in price significantly changes the quantity demanded, which is likely to occur in a highly competitive market. If demand for smart phones is highly elastic, manufactures that offer cheaper prices will sell the most phones.

If a market was perfectively elastic (i.e., perfectly competitive), the demand curve would be flat at a constant price given all firms would be price takers regardless of how much value they add to their products. Hence, any market in which a provider can differentiate on price cannot be perfectly competitive. Indeed, the ability to sell products at different prices is why the demand curve slopes downwards, and this oligopolistic structure is typical of most markets in the modern global economy. This implies that all consumers exhibit some degree of price‐sensitivity regardless of whether the product is an information good or an industrial good. Hence, movements along the demand curve and shifts in the entire demand curve for information goods are influenced by the same ‘non‐price’ factors described for traditional (industrial) goods.

180

The difference between information goods and conventional goods is the cost structure for supplying information goods. Developing supply‐side economies of scale can help to generate demand‐side economies of scale, depending on how cheap and accessible (i.e., open versus controlled access) the information product is within a market. However, the supply of high accuracy positioning services is currently limited to less than 9% of Australia’s geographic land mass, meaning price and other factors that drive demand for positioning services outside of these regions must also be examined to guide future investment decisions.

6.3.1.2 QUANTIFYING DEMAND

A simple measure of demand for high accuracy positioning services is the quantity of NRTK subscriptions that are purchased at different prices. The fact that information goods are priced on value rather than production costs means a SP has the flexibility to vary subscription prices for high accuracy data corrections (e.g., NRTK) above marginal cost, but not so high that consumers will substitute to a competing positioning service. Cheaper prices deliver smaller profit margins but increase sales volume. Higher subscription prices deliver higher profit margins, but sales volume is likely to decrease as more customers substitute in markets where competing positioning services are available at lower prices.

The demand curve in Figure 62a illustrates a linear relationship between price and quantity that can be used to conceptualise the market for high accuracy positioning subscriptions in Australia. Non‐linear demand curves are beyond the scope of this thesis. The basic assumption in Figure 62a is that more subscriptions are sold when price decreases towards zero (i.e., marginal cost) and the same theory applies when analysing demand for fundamental spatial data (PwC, 2010a). However, several other assumptions need to be clarified before attempting to model ‘true’ market demand for high accuracy subscriptions in Australia.

Firstly, Figure 62a is a conceptual model that demonstrates consumer behaviour in response to price changes. Absolute data on price and quantity is highly dynamic and highly valuable to businesses (e.g., supermarkets, GNSS manufacturers, positioning SPs) as it guides price discrimination strategies that are used to maximise profit. Hence, sales information is often kept private. Government and industry SPs in Australia do not openly publish subscription prices unless requested by users, and details on the number of subscriptions sold to different user groups are kept internal as they provide a competitive edge in determining which products are most valuable to each user group. Hence, this Chapter does not provide a detailed analysis of individual demand curves for each SP; its purpose is to analyse competition and growth trends in the overall market. This introduces a second complexity associated with pricing information goods, which raises further challenges in trying to quantify demand.

In light of the versioning and group pricing strategies introduced in Section 6.2.2.2, most SPs offer multiple types of high accuracy subscriptions that are differentiated on price and coverage. Charging

181 different prices for different levels of geographic coverage is a common price discrimination strategy, and subscription products can be further differentiated within each geographic region by customising service performance and bundling additional products (e.g., RINEX data). For example, an industry SP may offer multiple subscription products that include a pseudo‐national NRTK subscription across VIC and NSW, and a subscription that allows access in VIC alone. The VIC‐NSW subscription would typically be priced higher than the ‘VIC‐only’ product, but priced lower than users would otherwise pay if purchasing two individual subscriptions for GPSnet and CORSnet‐NSW.

A user that only requires coverage in VIC would therefore choose between a GPSnet subscription or the VIC‐only product marketed by the industry SP. Case Study 2 in Section 6.2.3.3 identified that the industry SP is capable of discounting its VIC‐only subscription whilst still earning profit, meaning price‐ sensitive consumers are likely to choose the cheaper industry subscription in VIC, and in any other State for that matter. Hence, the demand curve for the VIC‐only product will differ from that of the combined VIC and NSW coverage product given they are essentially independent products which are priced differently. Put simply, analysing market demand depends on which products are being compared.

In some regions of Australia, individual SPs (e.g., RTKnetwest) have a monopoly on service coverage, meaning their demand curves also represent market demand for these products. In other geographic regions where SPs face competition, prices can be aggregated if the products being compared are more or less equivalent (e.g., products that offer the same coverage). However, even in regions of overlapping coverage, product lines can be differentiated in such a way that one SP offers a unique positioning capability (e.g., accuracy, coverage, service performance) meaning demand for that product is effectively independent from other correction products in the market. Product and price differentiation strategies can therefore be classified and evaluated in terms of horizontal differentiation and vertical differentiation.

6.3.1.3 HORIZONTAL & VERTICAL DIFFERENTIATION

Horizontal differentiation describes the case where two products are sold at the same price but have different attributes, meaning consumer demand exists for both products (Dos Santos Ferreira and Thisse, 1996). Two products are said to be vertically differentiated if one product captures all demand from consumers if both products are priced the same. The dominant, vertically differentiated product therefore offers superior quality, which ultimately leads the producer to price the higher quality product at a higher price.

According to Jones and Mendelson (2011), all consumers prefer more of a characteristic called ‘quality’, but vary in their willingness to pay for it, meaning vertical differentiation is particularly appropriate for many types of information goods. Ease of use, speed and functionality are all ‘quality’ characteristics that, ceteris paribus, all consumers prefer more of. Quality can be interpreted in a number of ways for

182 positioning services including position accuracy, data latency, service availability, service coverage and overall system performance.

In the broader market for positioning services, the fact that SPs offer low accuracy (e.g., DGNSS) and high accuracy (e.g., NRTK) corrections is a prime example of vertical differentiation. If NRTK services were offered at the cheaper price charged for DGNSS‐only services then everyone would choose NRTK corrections, and the market demand curve for NRTK would shift right at this price. However, vertical differentiation leads SPs to charge a higher price for better accuracy (i.e., quality), and to further differentiate performance criteria, for example, via SLM procedures. Note however that service level is not just related to technical metrics, but also the value that consumers place on features such as customer warranties, certified positions, failure detection warnings and backup procedures, which can be managed and marketed using SLAs. SPs also bundle multiple types of data corrections (e.g., DGNSS, single‐base RTK, NRTK) into one subscription to market increased redundancy and flexibility for users.

The simplest example of horizontal differentiation is two different types of GPS receivers that offer the same positioning accuracy but have distinct features such as different user interfaces, which are optimised for different users groups (e.g., agriculture users versus surveying users). The receivers are horizontally differentiated given each user group prefers one type of receiver and has no incentive to substitute when they are priced the same. In the context of positioning services, two subscription products might be priced the same but offer different features such as additional service coverage or customised information. Whilst some users may benefit from additional service coverage, the alternative subscription offering less coverage for the same price may offer additional features that users prefer, such as access to RINEX data for post‐processing. It is however likely that additional coverage would only be provided up until a certain geographic extent before the SP increases price as means of differentiating products vertically.

Returning to the VIC‐NSW example above, the middle demand curve in Figure 62b can be interpreted as market demand for high accuracy data subscriptions in VIC. If a SP offered a correction product that provides additional geographic coverage across NSW at the same price as the original VIC‐only product, without limiting access to other features such as RINEX data, it makes little sense for a user to purchase the alternative VIC‐only product that effectively offers less quality (i.e., coverage). Market demand for VIC‐only subscriptions would shift to the left in Figure 62b, whilst market demand for the VIC‐NSW product would shift well to the right given users choose the higher ‘quality’ product that is offered at the same price. Some users may continue using a VIC‐only product if they have some preference for the features offered by that SP (e.g., warranties).

Rather than offering coverage in VIC and NSW at the same price, SPs typically adopt vertical differentiation strategies by recognising that consumers who value service coverage are likely to pay a higher price. Hence, the VIC‐NSW product is a separate subscription product sold at a higher price, and therefore has its own demand curve. These examples highlight that different users have different

183 sensitivities to price, accuracy, coverage and service performance. The effect of these sensitivities on market demand for high accuracy positioning services can be introduced by reviewing two early scenarios provided by RAND Corporation (1995) on market growth trends for GPS products.

6.3.1.4 PRICE VERSUS ACCURACY

RAND Corporation (1995) explored two scenarios to evaluate the influence of Selective Availability on growth trends in the early GPS market. Scenario one (Figure 63a) was based on the assumption that after Selective Availability was removed, market demand for GPS products would shift well to the right because increased accuracy would entice more users to enter the market. Regardless of any change in the price of a receiver, Scenario one implied that demand would increase as more users found value in applying higher accuracy position information, as depicted in Figure 63a.

Scenario two (Figure 63b) on the other hand assumed that the GPS market would become more price competitive if Selective Availability remained on, given users would become increasingly price‐sensitive and increasingly dependent on GPS for everyday applications, regardless of any change in accuracy.

Price‐sensitivity was expected as GPS devices became integrated with other devices such as communications hardware (e.g., smart phones), leading to more competitive consumer markets. Increased dependence was expected as GPS devices became increasingly embedded in a nation’s infrastructure (e.g., GPS receivers being used in telecommunications networks, highways, ports and construction projects) (RAND Corporation, 1995).

FIGURE 63A AND 63B: SELECTIVE AVAILABILITY & MARKET DEMAND FOR GPS

Scenario 1 Scenario 2

Figure 63a. Projected change in market Figure 63b. Projected change in market demand for GPS devices from 1995 (‘today’) demand for GPS devices from 1995 (‘today’) if Selective Availability was switched off if Selective Availability remained on (RAND Corporation, 1995). (RAND Corporation, 1995).

184

The shallow demand curve in Figure 63b exhibits higher elasticity because consumers are less focussed on accuracy in the presence of Selective Availability, and are therefore more sensitive to price as the market expands. Hence, the market demand curve shown in Figure 63b would shift to the right as more users entered the market and became dependent on GPS, and the curve would become more elastic as consumers became increasingly price‐sensitive. Horizontal differentiation would be important in a price‐ sensitive market, particularly to sell single‐frequency devices which dominated the market at this time, and continue to dominate the GNSS market today based on findings from GSA (2013).

At the time of this study in 1995, no operational alternative to GPS existed that could threaten the accuracy provided by GPS. Scenario one therefore implied that a costless95 change (switching off Selective Availability), which dramatically improved accuracy, would increase acceptance of GPS and lead to greater sales over time as the market expanded. Each company would attempt to maximise their market share in different segments without necessarily competing on price as more accuracy introduced new opportunities to value‐add. Scenario two on the other hand led many manufacturers to assume that, ceteris paribus (e.g., stable government policy, no substitute to GPS), lower prices would be more important to consumers as the market continued to expand without any change in accuracy. Put simply, users would have incentive to purchase GPS devices for reasons other than accuracy in Scenario two.

RAND Corporation (1995) concluded that:

“The key uncertainty in the economic value of turning Selective Availability to zero is whether the elasticity of demand for GPS is of greater or lesser significance than the position of the demand curve. To put it bluntly, does the future of commercial GPS depend more on low prices or on greater accuracy?” (RAND Corporation, 1995)

Comparisons can be made with the modern GNSS market (GSA, 2013) noting that Selective Availability has been switched off and competing satellite positioning systems are emerging to join the incumbent GPS. In light of market growth evidence presented in Section 6.3.1.6, this research suggests that the consumer‐driven demand curve in Scenario two most closely resembles the modern GNSS market96. Significant improvements in accuracy have shifted the demand curve right, but this shift is also largely driven by increased acceptance and adoption of GNSS technology across multiple sectors of the economy (including an increasing level of dependence). Global adoption rates in industries for LBS, road, maritime, rail, surveying and agriculture services are evaluated by GSA (2013) to estimate sales revenue and future growth trends in Section 6.3.1.6.

95 ‘Costless’ in a financial context, but not including the costs to public safety that Selective Availability was initially designed to protect (in a national security context). 96 Note that Selective Availability has been switched off today in contrast to the assumption made for the future demand curve in Figure 63b for Scenario two.

185

It follows that increased adoption within each of these sectors has led to greater price‐competition both vertically and horizontally as GNSS technology has become more accessible, powerful and functional over time. Price elasticity has also increased as more manufacturers and positioning SPs compete in consumer‐driven (e.g., smart phones) and infrastructure‐driven (e.g., engineering) markets. Whilst prices for GPS devices are still vertically differentiated in the sense that a dual‐frequency geodetic receiver is still priced higher than a smart phone, price‐competition has also increased relatively within each vertical price category.

A remaining question is whether accuracy may one day become so affordable (i.e., consumer‐driven) and so necessary (i.e., infrastructure‐driven) that all users demand high accuracy products?

This question provides the link between the previous scenarios and the need to evaluate market demand for high accuracy positioning subscriptions in Australia. Put simply, this research attempts to identify how a NPI can contribute to increasing market demand for positioning services across Australia. The research is limited to evaluating demand for high accuracy data, but recognises that a NPI will support the development of many GNSS products that are differentiated horizontally and vertically. The same concept for evaluating market sensitivities to price and accuracy can be applied to factors such as price versus coverage, and price versus service performance. In other words, identifying the price at which users demand more coverage and service performance, and identifying which user groups are likely to pay a higher price for these features are key questions addressed in the following Sections.

A two‐step approach was used to evaluate these questions to determine how a NPI will influence demand for high accuracy GNSS data corrections in Australia:

1. Estimate the total number of users who purchase high accuracy data subscriptions, and the average cost of these subscriptions (Section 6.3.1.5).

2. Investigate price trends and other factors that influence the position and shape of the demand curve identified in step one in response to growth trends in the broader GNSS market (Section 6.3.1.6).

6.3.1.5 ESTIMATING DEMAND FOR HIGH ACCURACY SUBSCRIPTIONS IN AUSTRALIA

Having detailed pricing strategies for data subscriptions and compared the modern GNSS market with early projections made by RAND Corporation (1995), it has been demonstrated that all users of GNSS technology exhibit some degree of price‐sensitivity. This Section estimates the price and quantity of high accuracy data subscriptions that are demanded in Australia, but also highlights the challenge of quantifying demand without a standardised framework for comparing local and national pricing models.

To begin this analysis, it assumed that NRTK corrections in the current market are more or less interchangeable, meaning users have incentive to substitute to a competing service at a lower price. A

186 key challenge however in estimating market demand for NRTK subscriptions was introduced previously when noting the absence of any public data on price schedules and usage statistics. To address this challenge, prices and user numbers have been estimated indirectly from a range of economic‐related literature (Position One Consulting, 2008, The Allen Consulting Group, 2008, ACIL ALLEN Consulting, 2013, GSA, 2013), and by drawing on feedback97 from government and industry SPs in Australia.

The total number of NRTK subscriptions demanded by users in Australia is therefore estimated to be below 5,000. Feedback from the DEPI98 suggests that GPSnet has approximately 500 users subscribed to its NRTK service. Given the Australian market for high accuracy NRTK subscriptions is comprised of three government SPs and three industry SPs, if each government provider has the same number of users as GPSnet, and each industry provider has 75% more than GPSnet99, the high accuracy market would contain almost 4000 users. Despite the absence of empirical data, the author’s upper estimate of 5,000 users is less than 0.03% of Australia’s population which is, theoretically, the potential market for high accuracy positioning services. The total number of users would therefore need to reach over 23,000 before market demand totalled 1% of Australia’s population, which demonstrates the small amount of market penetration in Australia. Even if 3,000 additional single‐base CORS have been deployed independent of any networked service (see Section 4.2.4), and there are (for example) five users for every single‐base CORS site, total user numbers would still be below 1% of the population.

The average cost of accessing an annual NRTK subscription to GPSnet is estimated to be $3,000. It was also identified in Case Study 2 (Section 6.2.3.3) that industry SPs who license raw data streams can discount their prices from government providers and still earn profit, thereby attracting a larger user base. The average cost of a VIC‐only subscription provided by industry is estimated to be $2,500. A similar discount rate applies when pricing pseudo‐national correction products that are networked across jurisdictional borders. For example, if GPSnet and CORSnet‐NSW both charge $3000 for State‐ wide coverage (i.e., $6000 total), a discount rate of roughly 25% (from the previous VIC example) would mean an industry SP charges $4,500 for VIC and NSW coverage, which is roughly consistent with industry feedback.

Given Table 10 (Section 4.3.2.4) identified NRTK coverage in VIC and NSW accounts for approximately 72% of total NRTK coverage across Australia, applying a linear projection to these previous cost estimates suggests that a pseudo‐national SP would charge approximately $6,250 to access the entire 8.4% service coverage region. It is however likely that SPs would cap subscription prices beyond a certain level of coverage given price competition will increase where two or more SPs deliver access to the same coverage region.

97 Feedback from conference presentations was particularly beneficial for this purpose. 98 International GNSS Conference 2013 ‐ Surfers Paradise, Australia. 99 Consistent with industry feedback and previous findings that data licensing can lead to a larger user base through discounted pricing.

187

A key implication of these price estimates is that regardless of differences in service performance, SPs who differentiate their coverage are selling independent products that have different demand curves. Put simply, market demand for a VIC‐only subscription is different to that for a combined VIC and NSW subscription. The NPI concept can therefore be analysed as a more structured and equitable pricing approach.

Consider the case where a NPI is established that allows any SP to license data streams from all CORS sites within the existing 8.4% service coverage region. This baseline coverage of 8.4% has various implications on how data can be priced. Firstly, users that require the maximum level of high accuracy coverage are likely to purchase one single subscription rather than multiple subscriptions from independent providers. Without the NPI, Figure 36 demonstrated that industry SPs can only provide access to approximately 85% of the total coverage once data from CORSnet‐NSW is also licensed (only 50% without CORSnet‐NSW). Hence, the NPI would encourage greater competition across the entire service coverage region by enabling more SPs to access existing CORS infrastructure which is primarily funded by government at present.

The same concept was presented in Case Study 2 to demonstrate why greater competition drives SPs to increase value for consumers through price and product differentiation, which introduces the second key point: each SP can offer horizontally and vertically differentiated products within the 8.4% pseudo‐ national coverage region. The natural strategy would be to differentiate coverage by State, meaning those regions where SPs have small monopolies on coverage would potentially become more competitive. The NPI would therefore reduce cost barriers for SPs who wish to enter the market, which in turn leads to greater value for consumers given the price and quality of horizontally and vertically differentiated products becomes more competitive. SPs would have greater incentive to develop innovative pricing strategies by bundling products, and to develop new hardware and software features for different applications to support diverse user groups.

Australia’s NBNCo has adopted a similar pricing structure. Uniform wholesale prices are enforced by NBNCo to ensure each wholesale provider has equitable access to the network. Wholesalers then compete on price and quality by differentiating their products horizontally and vertically to attract retail clients such as ISPs. ISPs search for the most cost‐effective and innovative product bundles that value‐ add to their business (e.g., backwards compatibility, network redundancy, service guarantees). Customers benefit from any cost‐savings that can be passed on from retail providers who aim to build their own demand‐side economies of scale (see Section 6.2.4). Wholesale and retail providers therefore focus their resources on value‐adding at each point of the information supply chain as opposed to the infrastructure supply chain. Linking each service to the same underlying infrastructure promotes investment in downstream research and development for commercialising broadband services, nationally. The NPI is comparable to the single point of access provided by NBN infrastructure in this example.

188

Having analysed pricing strategies and demand for high accuracy data subscriptions in Australia, Step two provides insight on future growth trends in the multi‐GNSS market by exploring opportunity costs for price, accuracy, coverage and service performance.

6.3.1.6 IDENTIFYING CURRENT & FUTURE DEMAND IN THE GNSS MARKET

The question of what drives demand for PNT information in the broader GNSS market has been introduced in terms of the trade‐off between price and accuracy in previous Sections. The notion that accuracy is addictive is a common mindset; but accuracy is expensive.

A single‐base RTK setup can cost between $5,000 and $20,000, whilst subscriptions to NRTK services range between $2,000 to $5,000 on average in Australia, depending on service coverage and the type of data corrections that are delivered (i.e., higher accuracy equals higher cost). In order to take full advantage of NRTK corrections, users must also purchase a high quality dual‐frequency receiver which can range from $5,000 to $15,000 in Australia. On the other hand, a dedicated handheld GNSS receiver or mobile device with integrated GNSS capabilities may cost as little as $100 to $500, but only deliver accuracy in the 5‐10 m range (95% confidence).

Whilst the absolute price of GPS and GNSS devices has decreased over time, recent sales figures provided by GSA (2013) demonstrate that the relative (vertical) price gap (RAND Corporation, 1995) between high accuracy and low accuracy devices has remained through time.

In reviewing price and accuracy trade‐offs in the early GPS market, RAND Corporation (1995) summarise that:

“As prices for GPS equipment drop, more commercial users adopt GPS or explore its use – even with no change in the GPS policy environment. ...Civil and commercial buyers are price elastic, and thus price is a greater influence per se on overall demand levels than accuracy. Whilst users would like perfect accuracy if it were costless, the vast majority of markets not using DGPS100 seem satisfied with the accuracy of SPS” (RAND Corporation, 1995)

Market growth studies by the European GNSS Agency (GSA) (2013) also support this statement. GSA reports that global shipments of GNSS‐enabled devices in 2012 for the LBS industry, representing the cheaper and lower accuracy end of the GNSS market (including smart phones, tablets and tracking instruments), grew to over 800 million units worldwide from 150 million in 2005. This growth translates to a global penetration of 22% for LBS devices that are GNSS enabled, which contributes over €12 billion in sales and services revenue globally. Furthermore, cumulative revenues for LBS are expected to

100 DGPS accuracy as defined by RAND Corporation is equivalent to the high accuracy market considered within this thesis.

189 account for approximately 47% of global GNSS revenue (over €240 billion) by 2022 in contrast to 4.1% and 1.4% contributed by the surveying101 and agriculture102 industries respectively (both of which are key user groups of high accuracy positioning services in Australia).

The remaining global revenues evaluated by GSA up to 2022 are divided between road (46.2%), aviation (1.0%), maritime (0.3%) and rail (0.1%), each of which are expected to grow in Australia based on current estimates up to 2020 (ACIL ALLEN Consulting, 2013). Whilst road applications are a large segment of the market, and higher accuracy GNSS technology will become more critical for road infrastructure and transport vehicles in Australia (Austroads, 2011, Standing Council of Transport and Infrastructure, 2012, ACIL ALLEN Consulting, 2013), many road applications reviewed by GSA aren’t dependent on high accuracy position information yet, including pay‐per‐use‐insurance, road traffic monitoring and road user charging applications.

Whilst the lower sales volume of high accuracy devices reflects their higher cost, it is important to consider the downstream economic value that higher accuracy devices and services create compared with lower accuracy devices. For example, The Allen Consulting Group (2008) estimate that the cumulative benefits to Gross Domestic Product (GDP) provided by high accuracy positioning services (which require high accuracy GNSS devices) within the mining, agriculture and construction sectors alone could reach between $73 and $134 billion net present value by 2030. Additional benefits of between $32 billion and $58 billion could be achieved through a national rollout of a standardised NPI. The quoted benefits are reliant upon high accuracy (± 2cm) CORS networks that offer NRTK positioning coverage. In the agriculture sector for example, high accuracy CORS networks improve farming practices by reducing production inputs, soil compaction, water run‐off, soil erosion, fuel usage and stress to farmers; whilst increasing yield, lowering carbon dioxide emissions and preserving water quality (Bowman, 2008).

Recent work by ACIL ALLEN Consulting (2013) also suggests that by 2012 Australia’s real GDP was between $2.3 billion and 3.7 billion higher than it would have been without the accumulated productivity improvements arising from sub‐metre, decimetre and centimetre GNSS positioning services. The same report projects that real GDP could be between $7.8 billion and $13.7 billion higher by 2020. These findings imply that although the low accuracy LBS segment delivers the highest sales revenue (GSA, 2013), the economic value created by these devices is not the same as the time‐savings, labour‐savings, safety improvements and equipment savings that derive from high accuracy positioning services and equipment. The price that users are willing to pay for higher accuracy, coverage and service performance varies across different industry sectors.

In light of these growth estimates, demand for GNSS technology is continuing to grow and is adding value across many sectors of the global economy. As more users enter each segment, the demand curve

101 100% penetration for GNSS enabled devices. 102 40% penetration for GNSS enabled devices.

190 shifts outwards and more businesses compete to deliver value‐added services. Users that value improved accuracy, coverage and service performance will naturally search for products that offer these capabilities at competitive prices, thus increasing demand elasticity where higher competition occurs. As GNSS technology becomes more prevalent in physical and information‐based infrastructures, such as communication networks and transport systems, society’s dependence on accessing PNT information anytime and anywhere will increase. For example, the European Commission (2011) estimated that 6‐ 7% of the European Union’s (EU) economy is already dependent on GPS, with further growth expected. The ASC (2012) note that Australia’s economy is similarly dependent on GPS.

As new applications and PNT capabilities are introduced to consumers, GNSS technology will further penetrate user markets in different industry sectors, therefore expanding the broader market for GNSS goods and services along with markets for complementary non‐GNSS technologies. Whilst high accuracy applications for agriculture and surveying are currently a small portion of the market in terms of annual device sales over time, growth forecasts by GSA (2013), The Allen Consulting Group (2008) and ACIL ALLEN Consulting (2013) suggest there is still a significant level of uptake that will occur in the these industries over the coming decade. However, the total number of users currently subscribed to positioning services is lower than predicted in these studies based on estimates made within this thesis103, suggesting that adoption rates for high accuracy positioning services have not yet reached critical mass (i.e., have not reached uptake levels comparable to that of low accuracy code‐based devices).

One possible explanation for a lack of uptake is that many users continue to invest in single‐base RTK technology as a substitute for NRTK services, particularly where NRTK coverage is not available. There is also a general lack of awareness that NRTK can improve service performance and coverage and enhance multi‐GNSS compatibility, meaning price‐driven users may find the cost of adopting any form of high accuracy GNSS technology too high at present. Put simply, if users cannot identify value in using high accuracy position information, they will not pay a higher price to access this information. Given the cost of supplying CORS infrastructure and positioning services influences the price that SPs charge to recoup fixed‐cost investment and earn profit, supply costs are a key consideration for identifying the extent to which lower subscriptions costs can increase demand. Section 6.3.2 explores these supply costs.

6.3.2 SUPPLY

It is self‐evident but nonetheless important to note at the beginning of this Section that public and privately owned CORS infrastructure and positioning services have been deployed because government and industry providers have identified demand for these services. The geographic location of CORS infrastructure and service coverage illustrated in Figures 32 and 36 respectively identified where

103 Adoption rates for 2013 were not compared by ACIL ALLEN Consulting (2013) with earlier projections from The Allen Consulting Group (2008).

191 demand for high accuracy products has been strongest. Public investment in VIC, NSW and QLD has built awareness and encouraged uptake of GNSS technology where market forces alone may not have led to State‐wide coverage. Industry providers have invested in CORS infrastructure and positioning services where a suitable Return on Investment (RoI) has been identified to offset fixed‐costs and earn profit. This Section begins by introducing the cost‐benefit relationship for supplying CORS infrastructure, followed by discussions on how a NPI can minimise fixed‐costs as a means of maximising social utility.

6.3.2.1 EXTERNALITIES & THE COST‐BENEFIT RELATIONSHIP

Section 6.2.1.1 identified that the benefits of pursuing any opportunity must be weighed against its costs. The first half of this Chapter was dedicated to understanding the high fixed‐cost structure needed to produce the first GNSS data correction from a positioning service. Section 6.3.1 identified economic benefits in terms of sales figures and contributions to GDP that reflect growing demand for GNSS technology. The majority of these costs and benefits are directly attributable to a specific good or service. For example, the cost of each input needed to establish CORS infrastructure can be approximated as a dollar value. These costs include GNSS hardware and software, communications, power, data usage and storage (e.g., cloud‐based services), heritage clearances, wages, labour, maintenance and property rent (Hausler and Collier, 2013b). Significant investment in Information Technology (IT) infrastructure is also needed to build data and processing redundancy and capacity through the use of Data Centres, Analysis Centres and Control Centres. It was also identified in Chapter 3 that costs vary for different Tiers of CORS. High quality geodetic Tier 1 CORS are more expensive than commercial Tier 3 CORS which are primarily used for network densification (Hausler and Collier, 2013a).

Whether buying or selling positioning services, or any product for that matter, direct benefits can be measured against the direct costs of investing in the product. The direct benefits of establishing a positioning service can be analysed in terms of the financial RoI that SPs receive from selling data subscriptions. Returning to Figure 36, the fact that commercial positioning services exist in these geographic regions suggests that the longer‐term benefits of supplying this infrastructure equal or exceed the direct costs of investment (see GPSnet example in Case Study 2 – Section 6.2.3.3).

Furthermore, Section 6.2.4 introduced the concept of externalities, when the well‐being of a third‐party is influenced by an activity without the third‐party having paid or received compensation for that activity. In other words, the indirect costs and benefits experienced by people external to the business are not typically considered in private investment decisions made by businesses and individuals. Pollution is the most common negative externality cited in the economic literature (Mankiw, 2007, Frank et al., 2008, Krugman and Wells, 2010). Indirect costs to those harmed by pollution are viewed as external to the direct costs and benefits (revenue) of supplying the product that causes the pollution. In the case that pollution decreases quality‐of‐life, increases health‐care costs, and lowers tourism, social costs are said to be higher than the private costs faced by the polluter. Public investment therefore aims

192 to minimise social costs and maximise public benefits that are not typically included in private cost‐ benefit calculations (Mankiw, 2007, Lateral Economics, 2009, Helbling, 2010).

It follows that positive externalities occur when the benefits to society of investment in a specific product are greater than the direct RoI received by the producer. For example, research and development activities often lead to positive externalities beyond the direct benefits enjoyed by those who fund the research. New research generates new knowledge which contributes to other discoveries and innovations, such as new positioning techniques in the case of positioning services. PwC (2010a) identified positive spill‐overs (i.e., externalities) from producing fundamental spatial datasets, including a more informed community which facilitates better decision‐making. Section 6.4 explains how government policy can be used to minimise social costs and maximise social returns to reduce deadweight loss and improve social well‐being.

A Cost‐Benefit Analysis (CBA) measures costs and benefits in terms of social utility gains, meaning positive and negative externalities are key inputs for analysis (OECD, 2006). For example, to determine the net effect of proposed policy changes and infrastructure investment on social well‐being, a CBA is often used to evaluate all potential gains and losses from a proposal in monetary terms. Australia’s Department of Finance and Deregulation (Dobes, 2008) notes that:

“Just as individuals maximise their income from investments in shares by choosing those with the highest expected net yield, governments can maintain social returns on expenditure (and hence the standard of living of the community) at the highest level possible by choosing projects and policies with the highest levels of net present value104.” (Dobes, 2008)

In the context of positioning infrastructure, Section 3.5 has already detailed why public funds are used to establish, monitor and maintain the GRS as a means of generating positive externalities (i.e., governments, businesses and users can connect to the GRS). The clearest benefits relate to measuring the size and shape of the Australian landmass to detect and monitor natural hazards such as crustal motion, which improves safety and allows greater planning for preventing damage to critical assets such as power and transport networks. Furthermore, as the network of users who connect to the GRS increases, the value of the GRS increases given more users can communicate and apply authoritative position information in a standardised reference system. Critically, modern positioning services can deliver all of these capabilities in real‐time, which leads to new research and development opportunities for applications that bring benefits to Australia and neighbouring countries, along with global GNSS user communities. These benefits include improvements in conventional and space weather forecasting;

104 By comparing the value of a dollar in the future to the value of that dollar today, Net Present Value (NPV) allows the current value of a future project to be estimated. Positive NPV implies that the project is viable given future cash flows from the project will be positive.

193 rapid detection of hazardous events such as earthquakes and tsunamis; assisting neighbouring countries to exploit GNSS technology and benefit from regional hazard monitoring applications; and improving performance monitoring of GNSS constellations to mitigate against vulnerabilities such as signal jamming and interference, particularly for the protection of critical infrastructure (ASC, 2012).

The key point is that private investment decisions for establishing positioning infrastructure and positioning services do not typically account for broader social benefits, meaning private investment does not always occur where public benefits have been identified. In other words, the supply of CORS infrastructure and positioning services may never be optimised if funding decisions are left to the private sector alone. This concept is known as market failure (Randall, 1983); a situation where the social costs of producing a good or service are not minimised which leads to deadweight loss due to an inefficient allocation of resources. Put simply, the quantity demanded by consumers does not equate to the quantity supplied. Whilst the previous Section detailed growth trends in the GNSS market, the concept of externalities highlights that direct benefits are not the only reason that users demand access to PNT information. External benefits are a key consideration that should be identified and evaluated within a CBA.

Dobes (2008) evaluates a past example of how a rigorous CBA would have assisted decision‐making on unifying railroad gauges in Australia early in the 20th Century, which has implications for current decision‐making towards establishing a NPI. Rather than focussing solely on the costs of unification, Dobes (2008) highlights that greater emphasis should have been placed on the social utility and downstream economic benefits that interconnection of the rail network between each jurisdiction would enable. However, private interests diverged from social interests in choosing which rail standard to adopt, or whether there should be a standard at all given the switching costs of coordination were high for each party (Shapiro and Varian, 1999, Dobes, 2008). However, adopting a single standard, in this case the 4‐foot‐8½‐inch gauge width ensured that all goods and services (e.g., rail freight) that required access to the network were made compatible, therefore generating greater value for those who continue to produce, distribute and consume each product that was transported. Section 6.2.4.2 identified why the IGS RTCM‐SSR data format has been developed to facilitate ‘interconnection’ of positioning services for this purpose.

Section 6.3.2.2 will demonstrate why issues of duplication and over‐investment in the Australian market for high accuracy positioning services has led to market failure, which leads to discussions in Section 6.3.2.3 and 6.3.3 on how a NPI can minimise social costs. However, readers are reminded from Section 6.1.2 that the aim of this research is not to provide a CBA, but to evaluate technical, institutional and economic decisions by governments and industry for supplying positioning infrastructure on a national scale.

194

6.3.2.2 DUPLICATION, OVER‐INVESTMENT & MARKET FAILURE

The evolution of CORS infrastructure and positioning services in Australia described in Chapter 4 suggests that duplication and overinvestment has occurred where data licensing could have minimised fixed‐costs. The following analysis provides geographic, statistical and economic examples of why duplication and over‐investment can be interpreted as market failure.

In relation to Figure 36, at least 49 privately‐owned CORS were identified in VIC, NSW, ACT and QLD alone that overlap with existing government services but do not contribute GNSS data to these networks. This equates to over 19% of total CORS that could have been used to extend service coverage and increase service performance, using existing government infrastructure through a more coordinated and strategic development approach. This conservative estimate of duplication overlooks a number of privately owned CORS that remain unidentified in these regions.

On a national scale, a simple area‐per‐station ratio was used by Hausler and Collier (2013a) to approximate the total service coverage that a NPI would enable if raw data from all CORS identified in this research (see Section 4.2) was coordinated through a single point of access. The analysis did not include CORS sites in the FBA network, although no duplication has been identified within this network meaning relative changes in coverage identified by Hausler and Collier (2013a) remain valid. Potential coverage was projected based on the area‐per‐station NRTK coverage (sq km) for stations in the GPSnet network. Potential coverage was estimated at 14.8% across mainland Australia (including Tasmania) suggesting that current service coverage could have been increased by approximately 43% through greater coordination of existing CORS assets. This difference can be interpreted as ‘lost’ coverage due to infrastructure duplication, and therefore market failure, which stems from the technical, institutional and commercial barriers discussed throughout this thesis.

Lost coverage equates to $13.5 million in capital and operational costs105, which could have been saved or reallocated through a coordinated national network to generate greater economic value in line with the estimates provided in Section 6.3.1.6. This conservative cost estimate does not account for duplicated software and control centres, or maintenance and upgrade costs, which are estimated at $2m for GPSnet alone. This analysis is also purely conceptual given existing infrastructure is fixed in location, and the projected coverage is linear and not optimised for a specific geographic region. The purpose is to estimate numerically the potential coverage that could have been enabled through coordinated deployment of a single, uniform service. It’s also recognised that ARGN (Tier 1) and AuScope (predominantly Tier 2) CORS infrastructure is strategically positioned to optimise management

105 Capital and operational costs for each CORS were estimated at $60,000 which is based on the assumption that 90% of duplicated CORS were deployed to Tier 2 and 3 standards at an average cost of $50,000 per CORS, with the remaining 10% deployed to Tier 1 standards with an average cost of $150,000 per site. ICSM standards and guidelines recommend that 10% of infrastructure should be installed to a higher standard to provide a traceable link to the national reference frame (Burns & Sarib, 2010). Tier 1 sites require more stringent specifications for physical site selection, site stability, GNSS hardware and software, and ancillary equipment.

195 of the geodetic reference frame. Eliminating all AuScope and ARGN sites yields total national coverage of 11.5% using the projection above, which translates to 27% of lost coverage. This equates to $8.4 million of over‐investment using the same cost profile.

The point remains that duplicated infrastructure would have contributed additional coverage and redundancy if deployment of, and access to all existing CORS had been coordinated through a NPI to improve service coverage and performance. Social costs must therefore be higher where additional coverage and performance could have been provided, meaning lost coverage can be interpreted as a deadweight loss to society. Put simply, the cost of funding duplicated infrastructure could have been saved or better spent elsewhere.

Viewed in aggregate, $13.5 million would have been a small price to pay to enable the broader social and commercial value (The Allen Consulting Group, 2008) that a standardised national network would enable. However, in the current market, $13.5 million can be interpreted as an inefficient allocation of resources that leads to deadweight loss and suggests that some level of market failure is restricting supply. Indeed, the very point of this research is to identify, relate and communicate these technical, institutional and economic barriers, and therefore evaluate the direct and external benefits that coordinated access will enable. Two implications of market failure are subsequently explored below:

i. The costs and benefits of supplying CORS infrastructure and establishing positioning services are not evenly distributed spatially (Sections 6.3.2.3 and 6.3.2.4).

ii. Duplication and over‐investment increases social costs, which in turn limits external benefits to producers and consumers who could have benefited from accessing a larger positioning network (Section 6.3.3).

6.3.2.3 LOCATING COSTS AND BENEFITS IN AUSTRALIA

The clearest example of why the costs of supplying CORS infrastructure and positioning services are not evenly distributed across Australia was demonstrated in Sections 4.2 and 4.3 by identifying that more investment (including network densification and duplication) has occurred in regions where demand is higher. Increased demand suggests that the direct and external benefits of producing and accessing these services must also be higher in these regions. However, limited spatial evidence has been compiled on where these benefits generate most value to users in Australia. The following analysis therefore maps key economic factors such as population density, remoteness indices and user applications that have influenced past investment in CORS, to identify regions where future investment is likely to be prioritised (i.e., where benefits outweigh fixed‐costs).

In compiling Figure 64, Hausler and Collier (2013a) identified that approximately 82% of Australia’s population lives within 50 km of the coastline, and demonstrated that most investment in CORS infrastructure has occurred towards these higher density regions (i.e., Major Cities and Inner and Outer

196

Regional Australia). It was also estimated that up to 83% of Australia’s population can access a positioning service within the estimated total NRTK coverage region.

FIGURE 64: AUSTRALIAN POPULATION DENSITY & NRTK COVERAGE

Statistical Area Level 1106 Census regions overlaid with 50 km coastline buffer and the combined high accuracy service coverage provided by governments and industry (Hausler and Collier, 2013a).

It was previously demonstrated in Figure 36 however that no single service provider enables access to this total coverage region in Australia. For example, Table 2 identified SmartNet Aus as the largest pseudo‐national service with 4.2% coverage across Australia, which equates to only 50% of the total NRTK coverage displayed in Figure 36. SmartNet Aus coverage will extend to approximately 85% once data streams from CORSnet‐NSW have been integrated.

One reason densification occurs around capital cities such as Melbourne (VIC) and Sydney (NSW) is to improve accuracy and service reliability particularly for engineering and construction applications (Rubinov et al., 2011). It is therefore reasonable to assume that future investment in CORS infrastructure will be focussed in and around Greater Capital City Statistical Areas (ABS, 2012a). Although population growth in urban regions is a driver for engineering and construction, Section 6.3.1.6 highlighted that population is only a small part of the picture when considering the productivity gains from high accuracy position information to industries for agriculture, engineering and mining (The Allen Consulting Group, 2008). For example, the new FBA network in Central Queensland is a leading

106 Statistical Area Level 1 (SA1) is the smallest base region and therefore the largest dataset for which 2011 Census data was collected by the ABS (2013), which includes approximately 55,000 mesh blocks covering the whole of Australia. SA1 is a classification within the ABS Australian Statistical Geography Standard (ASGS).

197 example of how land and water resource management activities in regional areas can benefit from high accuracy positioning services. The network will assist broad acre cropping enterprises and horticulturalists to improve their efficiency, and reduce the amount of pesticides and fertilisers reaching the Great Barrier Reef.

Figure 65 adopts a national approach to evaluating costs and benefits in the agriculture sector by approximating the location of key wheat growing regions, which are proven to benefit from high accuracy positioning practices such as CTF (Bowman, 2008). Figure 65 compares georeferenced data from ABARES (2012) with aggregate high accuracy positioning coverage to conceptualise where current and future service coverage is needed. As described throughout Chapters 4 and 6, a number of agriculture dealers and consumers are likely to operate privately‐owned CORS of unknown quality in these regions. Figure 65 therefore helps to identify where this infrastructure may be located, and where market demand107 will drive future investment in the near‐term, with or without the NPI.

FIGURE 65: AUSTRALIAN WHEAT GROWING REGIONS & NRTK COVERAGE

Australian wheat growing regions (ABARES, 2012) overlaid with existing high accuracy coverage (Hausler and Collier, 2013a).

107 The ABS estimates total wheat production in Australia for 2011‐12 at 29,923,000 tonnes, with a gross value of $7.5 billion. The gross value of all Australian crops increased by 6% to $20.0 billion in 2011‐12 (ABS, 2012a).

198

Another useful measure of where future infrastructure may be supplied by governments and industry in response to future demand is the Accessibility/Remoteness Index of Australia (ARIA108) shown in Figure 66. Comparisons between Figures 65 and 66 demonstrate that regions of higher population density and regions of higher agricultural activity are correlated with Major Cities, Inner and Outer Regional Australia and Remote regions of Australia as defined by the ARIA. Figure 66 implies that Regional and Remote Australia are likely to be the first regions that require further expansion of positioning services in response to future demand. Based on current trends in QLD, SA and WA (see Figure 32), uncoordinated private investment is likely to continue in these regions in the absence of a NPI. The ARIA classification also helps to determine the approximate locations in which independently owned assets may reside.

FIGURE 66: AUSTRALIAN REMOTENESS INDEX & NRTK COVERAGE

Accessibility/Remoteness Index of Australia (ARIA) overlaid with existing total high accuracy service coverage (Hausler and Collier, 2013a).

Road transport is another sector expected to undergo substantial market growth in its use of GNSS technology as summarised in Section 6.3.1.6. Real‐time, high accuracy position information can be used to locate a vehicle relative to a road centreline to support driverless technology and enable safety warnings for crash avoidance. In the same way that aviation applications require a high percentage of

108 The ARIA is based on a geographical methodology in which remoteness is defined on the basis of road distance from any point to the nearest town (service centre). The most recent ARIA compiled in 2011 uses five population classes to map remoteness across Australia (refer to map legend in Figure 66). As a purely geographical concept, the ARIA does not attempt to define the broader concept of accessibility which is influenced by many factors such as the socioeconomic status and population mobility.

199 service availability for safety‐of‐life purposes (US Government, 2012, CRCSI, 2011), accuracy, availability and integrity are key performance criteria required in the road transport sector.

Road, rail, aviation and maritime transport sectors are all leading examples of why truly national positioning services deliver social benefits through improved safety and network interconnection, which reinforces the notion that duplicated infrastructure leads to higher social costs. Figure 67 demonstrates this visually by overlaying existing NRTK coverage with Dual Carriageways, Principal Roads, Secondary Roads and Minor Roads in Australia109. Hence, Figure 67 not only demonstrates a lack of national coverage, but the need to enable a single point of access to coverage in existing service regions where higher demand has justified previous investment. Similarly, the rail gauge example in Section 6.3.2.1 highlighted the inefficiency of purchasing separate subscriptions in different geographic regions given positioning services with non‐uniform service levels and infrastructure standards dramatically limits the social utility that real‐time position information generates.

FIGURE 67: AUSTRALIAN TRANSPORT NETWORKS & NRTK COVERAGE

Dual Carriageways, Principal Roads, Secondary Roads and Minor Roads (GA, 2006) overlaid with existing total high accuracy GNSS service coverage (Hausler and Collier, 2013a).

109 Road classifications are defined by GA (2006) within the GEODATA 250K Series 3 dataset.

200

6.3.2.4 MARGINAL UTILITY

Following the previous cost‐benefit examples, it is evident that increased access to existing CORS infrastructure within and outside of existing service coverage regions can dramatically improve the marginal utility of high accuracy position information, as described below.

It has been demonstrated throughout this Chapter that different users have different opportunity costs for accuracy, coverage and service performance. The previous Section provided a visual representation of how these costs and benefits vary spatially. Each user places different value on the utility they receive from positioning services which reflects the price they are willing to pay for access. However, total utility is also influenced by external benefits such as how compatible their existing equipment is with a positioning network, and how many other people access and share data on the same network. Maximising external benefits helps to minimise social costs from duplication and over‐investment, thus increasing the marginal utility from accessing data within a positioning service.

Marginal utility was defined in Section 6.2.1.2 as the marginal benefit (or loss) that a consumer gains from consuming one additional unit of a good or service; a high accuracy data subscription in this case. However, the quantity of data corrections that can be supplied from any positioning service subscription theoretically approaches infinity depending on the network’s capacity to handle congestion from too many users. Hence, there is no natural limit on how many units can be produced. Methods of artificial scarcity are however used to restrict supply by controlling pricing and access to the network (Krugman and Wells, 2010).

SPs attempt to maximise returns by recognising that consumers have different opportunity costs when presented with a range of differentiated correction products. At one level, measuring the number of individual data packets (i.e., bytes of data) that a user consumes when subscribed to a specific correction product is a method of quantifying utility and depends on the length of time a user is connected to the service. However, the concept of utility extends well beyond usage statistics for individual correction products. SPs seek quantitative and qualitative feedback across their entire product range to direct investment towards product features that consumers value most. Service coverage and service performance are primary ways in which SPs differentiate value to attract different consumer groups and grow their market share. Hence, service coverage and service performance are also key criteria for evaluating marginal utility.

A key question in the context of a NPI is how much coverage and performance should be supplied before the marginal utility gained from producing ‘additional’ coverage is not worth the investment. Section 6.3.2.1 demonstrated the importance of identifying direct benefits and external benefits to answer this question. Whilst a CBA is typically used to identify and quantify all costs and benefits resulting from public funding, private investment decisions tend to exclude external costs and benefits such as knowledge spill‐overs and the benefits of standardisation. Identifying direct benefits allows

201 industry providers to interpret demand signals from consumers at various price points, which reflects their willingness to pay for additional coverage and service performance. If however the majority of value to consumers stems from external benefits such as public safety, as opposed to direct benefits that SPs use to guide pricing decisions, coverage and service performance may be supplied at a level that is less than socially optimal. The same concept applies to providers of fundamental spatial data who use price signals to determine the quality of data demanded by consumers (PwC, 2010a). Price signals for spatial data quality are weaker if information goods are provided for free (via public funding for example), but free data delivers larger external benefits such as knowledge spill‐overs to enhance decision‐making.

The finding in this research that almost 75% of NRTK CORS infrastructure has been funded by governments in Australia suggests that external benefits have been identified in addition to direct returns from operating commercial services. For example, governments in VIC, NSW and QLD have identified value in developing CORS networks where private investment may not have been justified to begin with. Government leadership has created external benefits by accelerating the adoption of NRTK technology in Australia; by providing research organisations with free access to positioning services to enhance research and development; by increasing consumer awareness about GNSS technology; and by enhancing and streamlining internal business services within government (e.g., asset mapping, surveying, meteorology, education, and geodesy). Public investment has created opportunities for private investment in downstream commercial positioning services through data licensing.

It is therefore likely that public funding will continue to be a key requirement for establishing a NPI. Regardless of the chosen funding model, the Australian Government also has a role to play in developing public policies (see Section 6.4) that minimise social costs by facilitating greater coordination between government and industry services. A formal CBA is a first step towards understanding the costs and benefits that a NPI will enable. However, the following Section also suggests that advancements in multi‐GNSS technology and processing techniques such as RT‐PPP present a unique opportunity to develop a NPI that delivers substantial economic and social benefits at negligible cost, particularly compared with other nation‐building projects such as the NBN.

It is therefore feasible that the marginal utility of existing CORS infrastructure is already close to enabling national high accuracy service coverage if a coordinated, single point of access is made possible through the NPI. Hence, the NPI will enhance Australia’s opportunity to provide leadership in developing new GNSS technology such as RT‐PPP to benefit national, regional and global users.

202

6.3.3 NPI: MAXIMISING BENEFITS AT MINIMUM COST

The importance of minimising fixed‐costs has been demonstrated throughout this Chapter by analysing cost structures, market structures, economies of scale, network externalities and the need to increase compatibility through standardisation. The argument that a NPI will address issues of market failure can first be explored by considering a simple example of whether aggregate investment by governments and industry over the past two decades could have been reduced, or used more efficiently if a uniform distribution and access model had been enabled through a NPI. A number of pricing and access decisions can be interpreted from this question to inform future policy and investment decisions for deploying CORS infrastructure and establishing positioning services nationally through the NPI.

Figure 68 maps two conceptual ATC curves for producing an arbitrary number of subscriptions in the existing 8.4% coverage region within Australia. Curve X represents the aggregate cost of funding all existing networks including those containing duplicated infrastructure. Curve Y removes all duplication costs to represent the minimum cost of enabling access to the 8.4% coverage region by only purchasing infrastructure spaced optimally at 70 km.

FIGURE 68: CONCEPTUAL NPI ATC CURVE

Curve X represents the ATC of producing subscriptions in a network containing duplication, whilst curve Y represents a network without duplication that provides the same level of coverage as curve X.

Applying cost estimates from Section 6.3.2.2 to Figure 68 demonstrates that the ATC of producing every data subscription would have been cheaper if 27% of coverage had not been duplicated at an extra fixed‐cost of $8.4m. The fixed‐cost of enabling 8.4% coverage would have been lowest if a NPI (curve Y) had been used to optimise the spatial distribution of CORS infrastructure within the network.

Note that Figure 68 is scalable to any level of service coverage where duplication has occurred; the implication being that data licensing would have minimised ATC, instead of deploying additional infrastructure. The relative shift between the curves in Figure 68 therefore reflects the level of

203 duplication in a given network that is not optimally designed. Note also that ATC continually decreases towards marginal cost given the variable cost of producing each additional correction is negligible and does not change as more subscriptions are produced. Short‐term marginal costs are considered zero in the remaining examples.

Figure 69a overlays a market demand curve whose shape resembles that of the current market for high accuracy positioning services described in Section 6.3.1.4. The assumption in Figure 69a is that at least one SP (curve X) provides access to the entire service coverage region but has deployed more infrastructure than was needed to achieve this coverage.

FIGURE 69A AND 69B: ATC & DEMAND FOR A NPI

Figure 69a. Price, quantity and deadweight loss Figure 69b. The cost of accessing

(shaded red) are influenced by supply costs and positioning goods and services will consumer demand. Curve Y represents an optimised influence current and future demand.

NPI design that lowers the ATC of producing all

subscriptions compared with a network (curve X) containing duplication.

A provider would price at ATC (represented by point A in Figure 69a) to recover fixed‐cost investment. At a (demand) price higher than ATC (above point A along the demand curve110), SPs would sell fewer subscriptions but earn higher returns per subscription. At a price below ATC (below point A along the demand curve), more consumers are willing to purchase subscriptions however the SP will make a loss given the ATC of producing each subscription is higher than the (demand) price they receive from consumers. The NPI design provides the lowest ATC (point B) of production meaning more subscriptions can be sold at a lower price without any financial loss.

When subscriptions are priced at ATC, the deadweight loss to society (shaded red) is the ‘lost’ value resulting from the additional quantity of subscriptions that would have been sold if subscriptions were

110 The demand curve represents the range of quantities that users are willing to purchase at different prices, meaning any section of the demand curve that is above the ATC of supplying a specific quantity of subscriptions corresponds to a profit in this example (vice versa for any losses incurred from a price below ATC).

204 priced at marginal cost (zero in this case). A useful interpretation of deadweight loss is provided by PwC (2010b) to describe why some users are willing to consume data at ATC whilst others are willing to purchase data at a price between marginal cost and ATC. Put simply, if subscriptions were sold to both user groups at these two different costs (ATC and

However, Section 6.3.2.1 also suggested that the justification (CBA) for public finances to fund a NPI would require evidence that substantial external benefits can be generated in downstream user markets. For example, in light of Sections 6.3.1.5 and 6.3.1.6, the demand curve in Figure 69a does not yet resemble a highly elastic market given market penetration across multiple sectors of the economy is low. The demand curve remains relatively inelastic even at a marginal cost of zero given expensive high quality dual‐frequency receivers are needed to access data corrections, which limits the market to a smaller group of specialised users. In other words, public funding is difficult to justify without a rigorous CBA to forecast the long‐term external benefits that multi‐GNSS technology will enable for governments, industry and the research community of Australia. In light of Section 6.3.1.6 however, market growth forecasts suggest that ‘future demand’ in Figure 69b is on the horizon, which will shift the demand curve outwards, and increase demand elasticity as society’s dependence on GNSS technology increases and users become more price‐sensitive. As the market continues to grow, Figure 69b illustrates a potential increase in the quantity of subscriptions demanded over time, which can be sold cheaper as ATC continues to decline. The level of coverage and service performance needed to maximise demand is therefore key to this discussion and raises the question of whether the future demand curve in Figure 69b is at all possible without a NPI that lowers, or distributes more efficiently, fixed‐cost investment to encourage greater access to position information?

To explore this question, consider that any expansion of coverage beyond 8.4% currently requires additional investment in CORS infrastructure, which can raise the ATC of producing each subscription. Drawing on findings by Hausler and Collier (2013a), the remaining number of CORS needed to extend NRTK coverage nationally can be calculated111 at approximately 3000 if a similar station distribution to GPSnet was adopted. Whilst it is reasonable to assume that triple‐frequency multi‐GNSS positioning

111 Based on the area‐per‐station ratio computed for GPSnet.

205 techniques will help to extend current inter‐station spacing requirements (Feng and Li, 2008), and less densification will be needed outside of capital cities (Section 6.3.2.3), 2500‐3000 additional CORS is still a reasonable estimate based on spatial evidence presented within this thesis (but would represent a very inefficient use of resources).

The trade‐offs between price and accuracy, and price and coverage identified in Section 6.3.1.4 are therefore key to this discussion. If consumers are price‐driven, current demand suggests that users who are happy with 5‐10 m accuracy from their standard GNSS device are unlikely to outlay substantial investment in a surveying‐grade GNSS receiver, in addition to purchasing a high accuracy subscription, in order to receive high accuracy position information. The marginal utility of extending service coverage is unlikely to justify the increase in ATC if limited growth is expected in this case. This applies to both ATC curves in Figure 69a given fixed‐cost must increase to extend service coverage. In the case that increased demand is identified outside of the existing coverage region, which is highly likely in Australia based on findings in Section 6.3.1.6 and 6.3.2.3, SPs are still limited in the amount they can charge for additional coverage in a consumer‐driven (price sensitive) market. Hence, the marginal utility of accessing more service coverage is heavily influenced by the price a SP charges users to offset increases in ATC.

Given costs and benefits are not evenly distributed spatially (Section 6.3.2.3), initial shifts in the demand curve are likely to be greater where existing positioning services are available, implying that any additional revenue earned within these regions in the short‐term can potentially be used to extend service coverage. A similar concept was described previously to explain why State governments in Australia identified value in facilitating the adoption of NRTK technology in Australia by leveraging public funds in the short‐term. In the longer‐term, technological advancements are likely to decrease the cost of extending service coverage as high accuracy positioning infrastructure and devices become cheaper (GSA, 2013), which encourages more SPs and users to enter the market. However, lower device costs also encourage some users to substitute to single‐base RTK technology, particularly those who are not familiar with the benefits of network positioning services. A key objective of the NPI will therefore be to increase consumer awareness of the multi‐GNSS benefits that users gain from joining an expanding network of users who derive authoritative and standardised position information from a NPI.

The key point is that until the high accuracy positioning market has reached critical mass, where high accuracy positioning services become ‘the standard’, there are cost‐barriers that prevent consumers from entering the market, which in turn limit the extent of service coverage that SPs are willing to supply. Whilst there are various methods other than those described previously of how organisations can structure capital and operational expenses to finance network expansions and improvements in service performance, the underlying technical condition to distribute CORS sites at approximately 70 km remains a barrier to achieving national high accuracy positioning coverage. If however there was a GNSS technology that enabled the same level of high accuracy performance to be provided nationally, without

206 substantially increasing the density of existing CORS infrastructure in Australia, the benefits to governments, businesses and society would be profound. RT‐PPP is a developing technology that current research suggests will enable this capability within the next 5‐10 years.

6.3.3.1 THE VALUE OF RT‐PPP TO AUSTRALIA

Section 3.4.3 identified that PPP techniques do not require a dense network of CORS sites nearby the user’s location. In theory, if traditional PPP methods were available in real‐time without the need for augmentation, no additional CORS would be needed to deliver high accuracy positioning services. Additional investment would only be needed to upgrade existing hardware for PPP compatibility, and to develop software and other ICT infrastructure. Based on current research however (Wübbena et al., 2005, Bisnath and Gao, 2009, Chassagne, 2012, Rizos et al., 2012, CRCSI, 2013b, Murfin, 2013) there is a level of densification that will be needed if high accuracy PPP corrections are to be delivered instantaneously using a hybrid RT‐PPP approach. A remaining research challenge is to identify the optimum density of CORS that will minimise fixed‐costs without jeopardising accuracy and service performance.

For example, doubling the NRTK inter‐station spacing requirement to 140 km would lower the total number of CORS needed to ‘fit‐out’ Australia by close to one quarter (around 625‐750 CORS112). Using the same ratio, tripling the inter‐station spacing requirement to 210 km would require between 415‐500 CORS based on the same area‐per‐station projection used in Section 6.3.2.2. However, these rudimentary estimates overlook the fact that NRTK station spacing already extends to over 100 km in parts of Australia, and multi‐GNSS capabilities are likely to extend this minimum distance requirement further. Assuming an average baseline length of 300 km is possible reduces this estimate to between 290‐350 CORS, and further reductions are likely as RT‐PPP technology matures in a multi‐GNSS future.

Broadly speaking, any technology that minimises the ATC of supplying and therefore pricing high accuracy positioning services nationally, will facilitate higher uptake by price‐driven users in consumer‐ driven and infrastructure‐driven markets. For example, if the demand curve in Figure 69a remained fixed, but both ATC curves continued to increase linearly as a result of increased investment to fit‐out the nation with NRTK infrastructure, SPs would find it difficult to recover these higher fixed‐costs without increasing subscription prices. SPs will only invest in regions where direct benefits outweigh the additional cost. Hence, if the external benefits of network expansion were not fully captured by this demand curve, but were seen as critical to enabling downstream multi‐GNSS value, then public funding may be the only option for supplying additional infrastructure, but would be difficult to justify without rigorous CBA.

112 Calculated as one‐third of the 2500‐3000 CORS identified previously.

207

Section 6.3.1.6 identified that the market demand curve in Australia is expected to shift right as more users enter the current market, which will also drive price‐competition amongst SPs seeking to increase their market share. SPs have incentive to develop and invest in technology that does not dramatically increase the price they charge for subscriptions. For example, if an individual SP dramatically increased subscription prices in order to cover the fixed‐cost of deploying 3000 CORS for national NRTK coverage, it is likely that alternative positioning techniques such as RT‐PPP would reach maturity before the SP attracted enough users for their high accuracy NRTK product to reach critical mass. If RT‐PPP and other multi‐GNSS innovations ultimately offer comparable performance to NRTK, short‐term investment decisions by industry may be delayed until these technologies reach maturity. Hence, public and private investment in the short‐term will help to fund the development of RT‐PPP and other technology. In the long‐term, this investment is likely to be recovered as consumers gain more access to positioning services at a lower cost, which generates greater demand in downstream commercial markets.

To conceptualise this balance, consider a SP that offers national high accuracy RT‐PPP coverage at the same, or a slightly higher price than NRTK subscriptions for the existing 8.4% coverage region. Although additional investment would be required to deploy the RT‐PPP network, the future demand curve would resemble that of Figure 69b given more users can now access a standardised, multi‐GNSS enabled positioning service. Regardless of a minor shift in the ATC curve, the changing demand curve would intersect the ATC at a higher quantity meaning subscription prices remain relatively constant, particularly in the presence of high economies of scale (represented by the decreasing ATC curve). A large increase in the position and elasticity of the demand curve may ultimately allow SPs to lower subscription costs further toward marginal cost. Even if the demand curve remained constant, subscription prices would increase but by a far lower amount than a national network built solely on NRTK technology.

It follows that additional CORS may only be required where the highest possible accuracy and service performance is demanded by consumers, which is where most investment in Australia has occurred to date (Section 6.3.2.3). Indeed, the minimum standard of accuracy, coverage and performance demanded by, and deemed critical for society (i.e., by government) may not be as rigorous as the current ±2cm NRTK standard. Commercial providers could provide NRTK or equivalent augmentations where higher accuracy is required using data from a NPI. The Australian Government’s decision to fund a national backbone of NBN infrastructure provides a useful comparison on the need to encourage downstream competition in wholesale and retail markets by connecting to a centralised NPI backbone.

The NPI should therefore be viewed as a mechanism that enables access to augmented positioning coverage anytime and anywhere across Australia, regardless of whether high accuracy NRTK coverage is available. The same concept underpins WAAS in the US which does not provide the same accuracy as ground‐based NRTK services but provides a minimum standard of coverage, availability and integrity deemed critical for aviation services. In other words, the social costs to governments, businesses and

208 society of not having WAAS are higher than the cost of funding WAAS. To inform future decision‐making on where and how to prioritise future government and commercial investment, the NPI will therefore require a governance framework in which all governments, businesses and user groups can communicate their positioning performance requirements and expectations.

Several conclusions can be drawn on how RT‐PPP and multi‐GNSS advancements will help to minimise the cost of supplying national positioning coverage through a NPI:

i. RT‐PPP will significantly reduce fixed‐cost investment in CORS infrastructure, thus lowering the ATC of network expansion compared with traditional NRTK approaches.

ii. Regardless of total network coverage, increasing the number of CORS that contribute data to a RT‐PPP solution will improve positioning coverage and service performance (e.g., accuracy, reliability, integrity, availability) through better atmospheric sampling. RT‐PPP therefore encourages data licensing in ways that maximise the number of CORS accessible through a NPI.

iii. RT‐PPP presents the opportunity to deliver data corrections via communications satellites such as Japan’s QZSS constellation. Satellite delivery significantly decreases the need for ground‐ based mobile telecommunications infrastructure in remote regions of Australia, and provides an additional layer of redundancy where existing communications are available. Satellite delivery can also reduce the cost of GNSS receivers if correction information can be delivered on existing L‐Band signals such as QZSS‐LEX, thus eliminating the need to purchase additional mobile telecommunications hardware. Furthermore, RT‐PPP corrections have the potential to deliver higher accuracy performance on L1‐only devices which are cheaper than high quality dual‐frequency receivers that are used for NRTK.

iv. RT‐PPP corrections can be delivered in the required GRS for immediate application, thus reducing the time and cost needed to perform additional datum transformations, which can introduce additional measurement error.

Having demonstrated the technical and economic value that RT‐PPP offers towards optimising the supply of CORS infrastructure, it is reasonable to conclude that the success of this technology in Australia is heavily dependent on the amount of raw data that can be accessed from existing CORS. Public policy is an institutional mechanism that is needed to facilitate and improve access to infrastructure and data to influence production and investment behaviour by government and industry providers.

209

6.4 PUBLIC POLICY

The concept of market failure was introduced in Section 6.3.2.1 by identifying that externalities can lead to an inefficient allocation of resources. Governments respond to market failure by developing public policies that protect the interests of those affected by externalities (Mankiw, 2007). Regulations, taxes and subsidies are primary policy tools used to minimise market failure. For example, governments aim to limit pollution by setting quality standards for products that produce carbon emissions and by taxing producers of these emissions. Alternatively, governments subsidise research organisations that generate positive externalities through knowledge spill‐overs, which provides incentive to generate new research. Antitrust laws113 and information standards (e.g., data standards) often govern production decisions for supplying information goods (Shapiro and Varian, 1999, Krugman and Wells, 2010).

The purpose of this Section is to identify why public policy is needed to overcome issues of duplication and over‐investment, and to facilitate greater access to existing and future positioning infrastructure and information. The percentage of public and private funding that is needed to optimise the supply of positioning services in order to maximise direct and external benefits is a key consideration. In other words, should the private market be solely responsible for responding to society’s demand for positioning goods and services, or should the Australian Government provide a level of investment and regulation that helps to standardise coverage and performance on a more equitable basis? This question builds on discussions regarding the level of dependence that society has on maintaining access to positioning services as a public good, which influences the level of government funding and oversight that is needed to manage positioning resources.

6.4.1 RULES AND REGULATIONS

Rules and regulations governing Australia’s use of positioning services are not well defined. Comparisons are made below with the telecommunications and electricity industries to introduce the need for greater standardisation and oversight at a national level of government.

6.4.1.1 TELECOMMUNICATIONS

The Australian Communications and Media Authority (ACMA) is the regulatory body responsible for defining the rules and guidelines that govern telecommunications carriers and service providers. The regulatory framework includes codes developed by industry in cooperation with the ACMA, and overarching technical standards for customer equipment. These regulations are legislated under the Telecommunications Act 1997 and Broadcasting Services Act 1992, and Section 51(v) of the Australian Constitution, which assigns legislative power to the parliament for postal, telegraphic, telephonic, and other like services.

113 E.g., Australia’s Competition and Consumer Act 2010.

210

6.4.1.2 ELECTRICITY

In contrast to the national regulatory framework for telecommunications services, legislative powers for electricity services are assigned to States and Territories. To ensure synchronicity in electricity transmission between interconnected jurisdictions, an overarching National Electricity Law (NEL) provides the legislative and institutional framework for Australia’s National Energy Market (NEM). The power grids of Western Australia and the Northern Territory operate independently.

The NEL is a schedule to the National Electricity (South Australia) Act 1996 and establishes the functions of the Australian Energy Market Commission (AEMC), the Australian Energy Regulator (AER), and the Australia Energy Market Operator (AEMO). The AEMC develops the National Electricity Rules (NER) under the NEL, which govern the arrangements for registration, market operation, market settlement, system security, network connection, metering, dispute resolution and jurisdictional feedback. The NER are enforced by the AER. Each participating State and Territory jurisdiction applies the NEL and associated NER to their legislation, for example the National Electricity (Victoria) Act 2005.

Whilst the administrative titles and functions of each body listed above are not pertinent to this discussion, the fact that public oversight is required to optimise the delivery of these services is critical. Government regulation for these industries is justified based on the welfare expectations that society places on governments for maintaining reliable access to critical power and telecommunications infrastructure. This does not preclude changes in technology and business models for these services, but refers to the general notion that uniform access, service standards, policy and pricing mechanisms are agreed upon and enforced within these industries. These electricity assets are also classed as critical infrastructure.

6.4.1.3 POSITIONING SERVICES

In contrast to the power and telecommunications examples described above, positioning services within Australia are not subject to the same level of institutional oversight and regulation at any level of government in Australia. Whilst nominal comparisons can be made between the spatial industry and the electricity market in terms of a federal distribution of powers for developing legislation, there is no overarching regulatory framework for coordinating GNSS positioning activities within the Australian Government (see Section 4.2.1.1). At present, ANZLIC is the peak inter‐governmental organisation for matters related to positioning within the spatial sector. ANZLIC develops policies and strategies to promote accessibility to, and the usability of spatial information, and has representation from leading Federal, State and Territory spatial agencies. ANZLIC does not however report directly through a secretariat to the Australian Government (at the time of writing), and its mandate primarily relates to governing information produced from positioning infrastructure as opposed to governing the provision of the infrastructure itself. GA is the Federal agency responsible for positioning infrastructure owned by

211 the Australian Government, whilst State and Territory governments manage their positioning infrastructure and policies independently.

With the exception of NSW and VIC, limited institutional consideration has been given to coordinating the technical and institutional deployment and delivery of positioning services. There is no regulatory framework that defines the institutional roles, responsibilities, contributions, entitlements, industry codes and practices, service standards, technical guidelines, risk factors, and liability arrangements that would be necessary to facilitate information sharing and development of the broader positioning market. As a consequence, there is no central department recognised as the single point of contact for national positioning within the Australian Government. In light of the evidence presented in Chapters 1 to 6 so far, the following Section explores why the Australian Government has a key role to play in establishing a NPI to inform policy and investment decisions through a whole‐of‐government policy framework.

6.4.2 THE ROLE OF GOVERNMENT

To understand the role of government in facilitating access to position information on a national scale, to promote fair trading and competition between wholesalers, retailers and consumers, it is useful to first revisit the concept of market power introduced in Section 6.2.2.

6.4.2.1 ADDRESSING MARKET FAILURE

Organisations that exhibit monopoly behaviour have increased market power to control the supply of a product and therefore the price at which it is sold to the market. Public policy is implemented by government to limit the growth of monopolies and therefore limit economic inefficiency (e.g., deadweight loss). For example, antitrust policy aims to prevent monopolisation that can result from predatory pricing schemes and collusive behaviour. However some level of monopoly power is a natural outcome in industries with high fixed‐costs and low marginal costs (Krugman and Wells, 2010), such as industries that produce position information. In many cases, the incentive to dominate a market is what leads potential providers to incur high fixed‐costs in the first place.

On one hand, governments encourage producers to invest in new technology that enables them to supply the highest quality products at the lowest cost. On the other hand, governments discourage anti‐ competitive behaviour that drives out all competition from a market. Hence, price and product differentiation strategies that create lock‐in and push a product towards critical mass are subject to

212 antitrust policy114 (Shapiro and Varian, 1999, Krugman and Wells, 2010). A delicate balance is needed to develop government regulations that maximise value within an economy.

The underlying principle of using public policy to encourage ‘fair’ competition applies to markets for industrial and information goods that exhibit market failure. For example, the level of cooperation that occurs between providers in oligopoly markets may influence policymakers to regulate production and pricing behaviour to avoid collusion. However, self‐interest also drives oligopolies towards competitive behaviour given privately owned businesses attempt to maximise their market share by controlling access to their products. Self‐interest has led to duplication and over‐investment in Australia’s high accuracy positioning market, given private investment decisions do not adequately account for the external benefits of positioning services to society. The role of government is to overcome this market failure by implementing policies that guide future investment decisions by governments and industry, and promote increased user access to these networks. One policy example is the NSW Government’s recent decision to licence raw data (for a fee) to promote innovation and competition in downstream commercial markets. GPSnet applies a similar data licensing policy, and Case Study 2 identified why this policy can attract new users from different industries and lead to business models that lower subscription costs for end users.

A key policy challenge for establishing a NPI is to therefore maximise access to data from all existing CORS infrastructure owned by government and industry providers across Australia. In light of Chapter 4, the finding that public funding in CORS infrastructure already accounts for approximately 75% of existing investment highlight that access to this infrastructure is governed by a combination of Federal, State and Territory data access policies (e.g., competitive neutrality or free access). In the context of a NPI however, the Australian Government is the only entity with the institutional scope to mandate national access to some or all of these existing networks.

In light of Australia’s Satellite Utilisation Policy, it is reasonable to conclude that the Australian Government views existing State and Territory CORS assets as a critical resource for supporting society’s growing dependence on GNSS technology, particularly as the high accuracy positioning market continues to evolve. The Australian Government therefore has a key role to play in centralising and regulating access to data from these existing networks in order to maximise economic value. The policy and funding arrangements needed to achieve this consolidation are beyond the scope of this thesis and depend heavily on existing data access policies, particularly given State and Territory governments have incentive to retain ownership in some cases for internal business purposes (e.g., geodetic activities).

114 One of the most prominent antitrust cases in history was brought forward by the US Department of Justice in 2000 who accused Microsoft Corporation of engaging in monopoly behaviour that contravened the Sherman Antitrust Act 1890. The US Government did not challenge the fact that network externalities are a natural feature of information industries, but claimed that Microsoft unfairly used its monopoly position in the market for operating systems to give its other products an unfair advantage over competitors. The initial ruling against Microsoft was overturned in November 2001 meaning the company was no longer required to split in two, but the resulting settlement required Microsoft to share its application programming interfaces with third‐party companies.

213

However, the finding that most government providers are shifting their responsibilities away from providing commercial positioning services suggests that ‘privatisation’ of these networks is already an option being considered in the longer‐term. Public ownership by the Australian Government may provide a more socially optimal alternative to privatisation in this case, and Section 6.4.3 explores public ownership concepts through discussions on public goods. Commercial drivers for a NPI are firstly discussed.

6.4.2.2 COMMERCIAL DRIVERS

From a commercial perspective, industry providers that fund their own infrastructure would have no obligation to share data with the Australian Government. However this research has identified that industry SPs have a commercial interest in maintaining access to government‐owned infrastructure (i.e., to lower fixed‐costs by licensing data). Government policies can therefore be developed that provide incentive to share data in return for gaining access to a much larger government‐funded NPI network. Government subsidies are one type of incentive, however the opportunity to access a standardised, multi‐GNSS enabled NPI network may be incentive enough for industry providers to contribute their data without the need for compensation. The ability to market positioning services that are certified against a national standard is likely to be a crucial business driver as critical infrastructure applications such as those for transport systems become increasingly dependent on high accuracy GNSS technology. Indeed, the Australian Government may be the only institution with the property right115 (i.e., legal authority) to provide and certify the underlying infrastructure within a NPI.

However, the fact that high accuracy positioning services are delivered by government and private companies in Australia raises questions as to how far the Australian Government’s role should extend in providing positioning services. On one hand, there is a clear role for the Australian Government to provide a level of enhanced accuracy and performance to maximise public benefit, much like the argument for WAAS. On the other hand, governments do not typically compete in markets where there is a clear role for industry to develop and sell value‐added services (RAND Corporation, 1995). One example is the Australian Government’s decision not to compete in downstream wholesale and retail markets for delivering broadband services on the NBN. However, the critical point to note in relation to a NPI is that the underlying NBN infrastructure is funded entirely by the Australian Government. Public funding was justified on the grounds that in the absence of government involvement, private investment decisions were unlikely to deliver a level of national coverage and infrastructure quality deemed socially optimal for maximising value in the Australian economy. In other words, government policy was implemented to fund a standardised NBN and to regulate access to this network to address technical, institutional and economic issues of market failure that would otherwise limit the delivery of broadband services. NBNCo enforces the Australian Government’s NBN pricing model to ensure uniform

115 Refer to Section 6.4.3.1.

214 pricing and access to the network is achieved to stimulate downstream wholesale and retail competition (NBN Co, 2011).

Applying the NBN concept in a NPI context suggests that government funding is needed to deploy the underlying positioning infrastructure that will stimulate commercial enterprise. However, the following discussion on public goods also suggests that the Australian Government may have some responsibility for delivering positioning services from a NPI network.

6.4.3 PUBLIC GOODS

The public good concept helps to analyse the roles and responsibilities of governments in the provision of high accuracy positioning services.

6.4.3.1 BACKGROUND

Chapter 1 introduced public goods as those which meet two conditions: they are non‐rival meaning one person’s consumption does not diminish another person’s ability to consume the good, and they are non‐excludable meaning society cannot be prevented from using the public good. National defence is the classic public good quoted in economics literature to demonstrate why no other organisation except government has the property right and resources to fund and control national defence (Mankiw, 2007). On one hand, the need for public funding recognises how critical and therefore valuable national defence is to protecting the welfare of society. However government ownership also highlights the concept of free‐ridership.

A free‐rider is a person who receives the benefit of a good but does not pay for it (Mankiw, 2007). For example, if left to the private market alone, national defence would not be supplied in the most efficient way possible given no private organisation has the property right to charge people for the defence benefit they receive. National defence may ultimately benefit the interests of some users more than others at no additional cost, meaning free‐ridership would lead to market failure in the absence of public funding. Conversely, free‐ridership can also create market failure if producers and consumers become too dependent on public funding.

A key challenge for government is to determine what level of regulation, ownership, taxes and subsidies can be used to minimise market failure in order to raise economic well‐being. Rigorous CBA helps to determine if the external benefits of public funding are worth the cost. Naturally, government must also take care not to create additional barriers to entry by implementing regulations (e.g., safety standards, licensing procedures, wages), taxes and legislative restrictions that prohibit private investment and therefore market competition (Rose, 2002).

215

6.4.3.2 POSITIONING INFRASTRUCTURE & SERVICES: A PUBLIC RESOURCE?

For the purpose of this research, GPS is considered a public good. The SPS signals are freely available without any restriction (e.g., encryption), and these signals can be consumed in whatever quantity a user requires without affecting another person’s ability to access the signals (i.e., non‐rival). The only barrier to using the SPS is the cost of purchasing a GPS receiver, which is a private good that is excludable and rival. Put simply, if one person buys a GPS receiver the product is no longer available for another consumer to purchase.

High accuracy positioning services in Australia are not public goods. SPs exclude users by charging access fees and encrypt data using proprietary data standards that prevent unauthorised access. The technical capacity of some positioning services may also reach a point of congestion, for example by exceeding data bandwidth limits which would also make the service non‐rival in consumption. Note here that whilst the marginal cost of producing additional corrections is typically considered zero in this Chapter, network congestion could potentially increase marginal cost in the short‐term if the cost of providing additional bandwidth increases for each additional correction.

In reviewing the role of government for providing access to positioning services, it is useful to consider that Australia and many other countries are free riders of GPS. Australia’s reaps significant economic benefit by leveraging free and unrestricted access to GPS signals. It could be argued that free‐ridership has subsequently limited investment in space and ground infrastructure by the Australian Government. However, it is also recognised from Chapters 2 and 4 that ground infrastructure investment may not have occurred without the invention of GPS in the first place, meaning GPS has actually stimulated investment according to this latter interpretation. Furthermore, the Australian Government provides free access to data from the infrastructure it owns to support international efforts aimed at monitoring and improving GPS and GNSS capabilities, such as collaborative work undertaken through the IGS. The Australian Government also contributes to bilateral discussions and activities with the US Government through its Joint Delegation Statement on Cooperation in the Civil Use of GPS and Space‐Based Positioning Navigation and Timing (PNT) Systems and Applications (GPS.gov, 2010).

The free‐ridership concept does however highlight that current investment in PNT infrastructure by the Australian Government is marginal compared with the billions of dollars (see Chapter 2) spent by foreign nations in developing their GNSS capabilities. Australia’s Satellite Utilisation Policy (Australian Government, 2013a) and the Australian Strategic Plan for GNSS (ASC, 2012) identify that Australian governments and industry now have a unique opportunity to develop policies that inform future investment in multi‐GNSS technology. In fact, the Australian Government has a responsibility to ensure Australia is technically, institutionally and economically equipped with the positioning resources needed to maximise value in a multi‐GNSS economy. In light of Section 6.3.2.1, part of this responsibility extends to the delivery of positioning services such as those supporting weather forecasting, hazard monitoring applications, GNSS performance monitoring and risk mitigation technology for the protection of critical

216 infrastructure (ASC, 2012). Each of these applications generates substantial positive externalities that government aims to maximise.

Indeed, maximising external benefits using positioning services is not a new concept. In reviewing the early market for high accuracy positioning services, RAND Corporation (1995) notes that if a private company can charge for a service, then government should not provide the same service for free. However, important exceptions include national security, foreign policy and public safety (RAND Corporation, 1995). These external beneficiaries reinforce the US Government’s mandate described previously to fund and manage the provision of GPS and WAAS as a public good.

In this context, the Australian Government also has a role in funding positioning infrastructure and providing a level of enhanced service performance that will generate external benefits that are critical to protecting and enhancing economic value for Australian governments and industry. Identifying the minimum service coverage and service performance requirements needed to maximise these benefits is a key recommendation of this research, and requires a national governance structure that incorporates the views of all stakeholders of a NPI.

6.5 CONCLUSION

Chapter 6 has consolidated a range of technical, institutional and economic concepts to identify two interrelated drivers for developing a NPI that will enhance access to high accuracy multi‐GNSS position information:

i. In light of the direct and external benefits that high accuracy positioning services will create in a multi‐GNSS enabled economy, there is an identified need to address issues of market failure that currently limit the supply of CORS infrastructure to a level that is less than socially optimal.

ii. A coordinated, whole‐of‐government and industry approach to establishing a NPI will guide future investment decisions and promote data access policies that account for technical, institutional and economic user needs across multiple sectors of the Australian economy.

In the same way that the Australian Government encourages downstream competition for developing commercial goods and services that enhance access to broadband services on the NBN, commercial providers of positioning services have incentive to develop products that enhance accuracy, integrity and quality assurance for a growing range of positioning applications. The NBN analogy suggests that establishing a NPI as a natural monopoly would offer the lowest ATC of supplying CORS infrastructure and other positioning infrastructure nationally. Indeed, the NPI is essentially a national model of the individual approaches undertaken by the VIC, NSW and QLD Governments to license data through a

217 single point of access. The NPI is a natural progression in the technical, institutional and economic evolution of multi‐GNSS technology.

A NPI would mean that SPs no longer negotiate VAR Agreements and prices with multiple data custodians whose infrastructure and SLM procedures are likely to vary; national agreements would be developed. Furthermore, the NPI would bring uniform national standards for multi‐GNSS compatibility that not only minimise ATC but ensure all position information is referenced to a national and globally compatible datum. SPs could function as certified wholesale providers of GNSS data derived from the NPI. Certification would ensure each SP meets a minimum standard of infrastructure and service quality to provide user confidence that position information is consistent, nationally (i.e., has a traceable link to the NGRS), and to enforce minimum service level standards. Pricing and access to the NPI could be standardised in much the same way that NBNCo certifies wholesale access through its WBA.

Consistent NPI data standards and transfer protocols will allow broader and more equitable access to position information and spatial data. The 4‐foot‐8½‐inch rail gauge is a useful geographic comparison for understanding why national coordination and standardisation is critical for broadening access to positioning services to create additional value from existing resources. Indeed, the market may fail to converge on a common standard in the absence of government regulation. Inefficiencies can arise where proprietary standards dominate a positioning market across a specific country or region. This leads to increased market power resulting in barriers to entry for other providers wishing to enter a network economy.

Additional CORS sites should still be funded publicly and privately for establishing a NPI, but the value of connecting each site to the NPI should be clearly articulated. Validating the quality of data observed from a new CORS connected to the NPI is a key role the Australian Government should continue to play, but in a real‐time capacity. In return, raw GNSS data observed from the new CORS site could feed back into the NPI to assist quality monitoring of the entire network, which builds additional rigour in the system whilst allowing other users to access new data subject to agreed licensing arrangements between site owners and the NPI custodian. This is a natural extension of the cooperative site hosting models already used in Australia and the US (Chapter 4), meaning the NPI concept would extend custodial responsibilities to managing real‐time data streams in addition to archived datasets (e.g., RINEX).

As PPP and multi‐GNSS processing techniques continue to evolve, the NPI should be used to deliver an authoritative source of regional orbit, clock and atmospheric products that align with and contribute to those computed by the IGS. In the absence of any immediate investment space infrastructure such as an SBAS, maintaining some level of sovereign control over the computation and quality standards for producing PPP products is likely to be crucial as multi‐GNSS signals and positioning services increasingly support critical infrastructure assets including banking and transport systems. Australia’s Satellite Utilisation Policy suggests the Australian Government will play a leading role in funding and establishing

218 the necessary governance structures and technology to guide policy and technical progress towards the NPI.

Establishing the NPI to minimise fixed‐cost investment ultimately decreases access costs for producers and consumers, which encourages downstream competition for developing positioning services that ensure high accuracy multi‐GNSS position information becomes ‘the standard’.

219

220

CHAPTER 7 NPI PLANNING FRAMEWORK: TECHNICAL, INSTITUTIONAL &

ECONOMIC CRITERIA FOR COORDINATING ACCESS TO AUSTRALIA’S GNSS CORS INFRASTRUCTURE

NPI PLANNING FRAMEWORK:

TECHNICAL, INSTITUTIONAL & ECONOMIC CRITERIA FOR COORDINATING ACCESS TO AUSTRALIA’S GNSS CORS INFRASTRUCTURE

7.1 INTRODUCTION

The major contribution of Chapter 7 is to propose a new NPI Planning Framework (the Framework) that will inform the business case for establishing a NPI by defining criteria for planning, operating and managing Australia’s positioning infrastructure on a national scale, thereby enhancing the direct and external benefits of accessing multi‐GNSS technology. Existing providers will use the Framework to optimise their supply chains in ways that contribute to, and benefit from establishing a NPI with a single point of access.

7.1.1 RESEARCH RATIONALE

By addressing public and commercial business drivers for supplying ground (and space) infrastructure across Australia, Figure 70 illustrates that the design of a NPI will respond to the technical, institutional and economic limitations that result from deploying and operating ground infrastructure independently, as detailed throughout this thesis. Greater coordination is needed across all levels of government and in cooperation with industry to overcome issues of duplication and over‐investment.

FIGURE 70: CHAPTER 7 RATIONALE

Chapter 7 develops the NPI Planning Framework to provide technical, institutional and economic recommendations for establishing a NPI as a single point of access to positioning infrastructure in Australia. Chapter 7 consolidates findings from throughout the thesis (as highlighted by the yellow bounding box) to develop these recommendations in line with policy and planning at a national level of government in Australia.

222

The Framework will guide future policy and investment decisions to coordinate and increase the supply of CORS infrastructure made available through a single point of access. The Framework will support development and implementation of the NPI Plan and the PNT governance framework outlined within Australia’s Satellite Utilisation Policy (Australian Government, 2013a), as illustrated in Figure 70.

7.2 NPI: A CONCEPTUAL FRAMEWORK

7.2.1 INTRODUCTION

Evidence of duplication and over‐investment in Australia’s CORS infrastructure has been identified for the first time through this research, and a unique economic context has been developed to examine how and why a NPI will address these supply challenges. The Framework developed below consolidates these findings to establish a new model for informing NPI policy and investment in positioning infrastructure. In light of Chapters 1 to 6, the Framework identifies four key objectives for achieving coordination: policy; investment; positioning infrastructure and services; and access. These objectives relate the supply chain and value chain for establishing a NPI, as defined in the following Sections.

For the purpose of this research, the Framework primarily addresses coordination issues for accessing CORS infrastructure; however the Framework is scalable and adaptable to plan for the multitude of GNSS and non‐GNSS positioning infrastructures that a NPI will facilitate access to. The findings in Section 7.3 are therefore relevant to planning, deploying, networking and delivering all positioning infrastructure in Australia, as depicted in Figure 71.

FIGURE 71: CONCEPTUAL NPI PLANNING FRAMEWORK

Conceptual flow diagram for the NPI Planning Framework.

223

The conceptual relationship between each objective in Figure 71 can be described in two different ways, both of which capture the fact that technical, institutional and economic criteria influence decisions for supplying positioning infrastructure in Australia, and therefore the value created by this infrastructure:

i. Policy will influence planning for a NPI and will guide public and private investment decisions for funding infrastructure and services. Government and industry providers can network this infrastructure in order to maximise access to the positioning services they deliver to users.

ii. Delivering Access to a NPI requires a network of positioning infrastructure and services that have been deployed where public and private investment has been justified in accordance with national planning and policy.

The four objectives (policy, investment, infrastructure and services, access) primarily represent the value chain for establishing a NPI. Economic value is firstly created through direct public and private infrastructure investment in line with national policy, and this value grows as the network of users and products/services that access the network expands, therefore generating direct and external benefits across the entire economy.

To achieve these objectives, the need to plan, deploy, network and deliver positioning infrastructure in a way that minimises fixed‐costs, without jeopardising service quality, broadly represents the supply chain for CORS infrastructure within the Framework. Note however that supply criteria are not identified explicitly within the Framework. Each research finding and recommendation in the Framework combines technical, institutional and economic CORS requirements from throughout this thesis with supply criteria identified by Higgins (2008), to demonstrate the multi‐faceted (i.e., non‐linear) supply chain for establishing a NPI. Figure 72 maps the organisational roles identified by Higgins (2008) in Section 5.3.1.2, to the supply considerations and objectives identified in the Framework in Figure 71.

224

FIGURE 72: NPI PLANNING FRAMEWORK & HIGGINS MODEL

Institutional

Technical Economic

Policy Investment Infrastructure & Services Access

PLAN DEPLOY NETWORK DELIVER

Specify Stations Network Process Deliver

Specify System Own Stations Network the Data Process Network Deliver Service • Target Density, • Site Selection •Data Comms •Copy of • Retail Sale of Coverage •Site from Network Network Data Products Reliability and Construction Stations •Data •Marketing Availability •Equipment • Control Centre Processing • Rover • Site Quality Purchasing •Data Archive •Production of Equipment •Equipment • Station Data Data Streams support Quality Comms • Distribution of •End User • Geodetic •Site Data Streams Support Reference Maintenance •Data • Liaison with Frame •Equipment Wholesaling User Comms • Data Services Replacement •Retailer Providers Produced Cycle Support • Data Access Policy

Governance

Relationship between the Framework and the Higgins Model. The Framework addresses the value proposition for establishing a NPI by examining technical, institutional and economic criteria that influence decisions for supplying CORS infrastructure, nationally.

This relationship between the Higgins Model and the Framework can be summarised as follows:

• System requirements are planned116 and specified117 in accordance with national policy118;

• Specifications for deploying each station influence the level of investment that is required;

• Networking and processing data from CORS stations will enhance the value of infrastructure and services within a NPI, and infrastructure and services that are connected to a NPI;

• The NPI enhances economic value by delivering access to an expanding network of users.

116 Italicised text represents supply considerations addressed in the Framework. 117 Bold text represents organisational supply criteria identified in the Higgins Model. 118 Underlined text represents the NPI objectives set out in the Framework.

225

Whilst the Higgins Model has informed development of independent networks in Australia, it has not established a ‘unified’ single point of access. Figure 72 therefore illustrates how the Framework links the roles and responsibilities (Higgins, 2008) for supplying CORS to the broader value chain for investing in CORS (the main focus of the Framework). Put simply, it is difficult to examine organisational roles and responsibilities for supplying positioning infrastructure without first articulating the value proposition(s) that guides public and private investment decisions. Public and commercial business models can then be developed to supply access to a NPI in downstream wholesale and retail markets.

7.3 NPI PLANNING FRAMEWORK

Institutional, technical and economic criteria addressing policy, investment, infrastructure and access objectives for establishing a NPI are identified below. The order in which these criteria are presented is not sequential given different objectives will be addressed at different stages of development. For example, the development of open data standards is well underway, however the NPI policy framework needed to endorse and implement these standards (nationally) does not exist. Each recommendation therefore strengthens the business case for a NPI, but the technical, institutional and economic design of a NPI is not contingent upon implementing each recommendation.

A useful example for interpreting the Framework is to consider that different funding options (e.g., public versus private) will influence the (technical) design of a NPI and associated (economic) cost‐ recovery models. The Framework therefore specifies the technical and economic criteria for evaluating each funding option, which in turn affects the type and level of (institutional) regulatory oversight (e.g., data licensing, data standards) needed to govern a NPI. Different funding options therefore lead to different institutional, technical and economic requirements for establishing a NPI which are summarised in the Framework and referenced to content presented throughout this thesis.

Table 23 (first presented in Section 1.6.1) lists all recommendations from the Framework to outline key themes that have been addressed in this thesis. Each recommendation is backed by a summary of associated research findings, and is referenced to content within this thesis that contributes evidence supporting the recommendation. Each ‘cell’ within Table 23 is therefore a component of the Framework, and each component is addressed individually in the remaining Sections of this Chapter. Combining each component establishes a framework for planning a NPI, thereby guiding technical, institutional and economic decision‐making by governments and industry.

226

TABLE 11: NPI PLANNING FRAMEWORK RECOMMENDATIONS

Policy Investment Infrastructure & Services Access

227

7.3.1 POLICY

Developing national policies for designing and implementing a NPI is the first step towards recognising the direct and external benefits that public and commercial investment in CORS infrastructure enables. National policy guides future investment decisions, promotes infrastructure and service standards and guides data access arrangements (e.g., open versus controlled access).

7.3.1.1 INSTITUTIONAL CRITERIA

TABLE 12: POLICY – INSTITUTIONAL FINDINGS & RECOMMENDATIONS

Summary of Research Findings

Infrastructure investment and operations have been duplicated as a result of independent policy and management across government, which has limited data sharing between governments for public and commercial positioning applications. There is ambiguity in the roles and responsibilities of infrastructure managers and partner organisations within government, and reporting mechanisms for some bodies are undefined. A central governing body to act as a single point of contact and access for positioning programs has not been identified formally in Australia.

Whole‐of‐government collaboration and coordination is essential to ensuring Australia captures the full benefits of multi‐GNSS to enhance the utility of existing and future positioning infrastructure investment. Authoritative policy for implementing a NPI will encourage government agencies to exercise leadership and responsibility in developing and managing a NPI, and will ensure the NGRS provides the underlying framework for delivering fit‐for‐purpose location information, thereby increasing compatibility with international reference frames and spatial datasets (ANZLIC, 2011). The following institutional criteria are recommended to facilitate national policy development and funding in response to supply challenges.

Chapters Response to Research Findings Recommendations 1.4.1 • A NPI advisory committee with stakeholder representation 2.2.7 from governments, industry and the research community 4.2*119 5.2* should be established as a single point of access for

5.3* addressing national positioning requirements, and for 6.3.2.1 reporting to the Australian Government (e.g., through the 6.3.3.1 SCC PNT Working Group identified in Figure 4). 6.4*

119 The symbol * denotes the case where all sub‐sections are relevant to the specified findings and recommendations.

228

• The advisory committee should:

1.4.1 o Inform national positioning policy in line with the NPI 2.2.7 Plan and Australia’s Satellite Utilisation Policy, and 4.2* establish implementation teams and technical working 5.2* groups as needed (e.g., by drawing on existing 5.3* 6.3.2.1 government and industry expertise). 6.4* Encourage and facilitate alignment between existing o Federal, State and Territory spatial policies and national

policy (e.g., rigorous alignment with the NGRS). Establish a national o Engage with existing cross‐sectoral committees, governance structure 3.5* 120 councils (e.g., ANZLIC, ICSM, ARRB ) and working with representation from 4.2.1* groups to align NPI investment with existing cross‐ 5.2* Australian governments, 5.3* sectoral government and industry programs, to industry and research 6.3.1.6 establish a broader funding base, to minimise stakeholders, to set 6.3.3* duplication and to address the positioning 6.4.3.2 directions and seek requirements of all stakeholders. government 2.2* o Facilitate international engagement to ensure ongoing endorsement on 2.5 access to foreign space systems, and to promote positioning related 3.5.2.5 ongoing collaboration with international programs such matters 4.4.7 5.3.2* as those of IGS and GGOS.

2.2.7 o Provide a single point of contact (access) within the 4.2* Australia Government for addressing issues related to 5.3* infrastructure investment, data access, and service 6.2.3* 6.3.3* performance.

2.2.7 o Clarify the roles, responsibilities, contributions, 4.2* entitlements, liabilities, privacy, codes and practices 5.3.2* 6.4* and risk factors for all stakeholders.

120 Australian Roads Research Board (ARRB).

229

7.3.1.2 TECHNICAL CRITERIA

TABLE 13: POLICY – TECHNICAL FINDINGS & RECOMMENDATIONS

Summary of Research Findings NPI policy should address the need for authoritative infrastructure, data and service standards for accessing and improving the utility of high accuracy positioning infrastructure and services. National standards and guidelines will facilitate data sharing across government and industry to maximise the cross‐sectoral benefits of accessing certified and legally traceable data connected to the NGRS. Open data standards increase interoperability, redundancy, network integrity, service coverage and availability.

Chapters Response to Research Findings Recommendations

3.2* • The stability and quality of CORS infrastructure should be 3.5* certifiable against national and international standards Endorse national 4.2* (e.g., ICSM standards and guidelines) for legal traceability infrastructure standards 4.3.3 5.3* with respect to the NGRS.

3.4* • Uniform service level standards (e.g., SLAs) should be 4.2.2.5 endorsed by government to specify minimum service level 4.3.2* Endorse national service criteria supporting the functions of government and 5.3* level standards 6.2.3* business services, particularly those which have a critical 6.4* dependence on GNSS infrastructure.

3.4.4 • Open data standards for recording and distributing GNSS Endorse open data 5.2* data should be endorsed by government to facilitate standards for recording 4.4.7 centralised access for producers and consumers of and distributing GNSS 5.3.2* 6.2.4* positioning services. data within a NPI

• Providers of NPI services should be certified (e.g., licensing agreements, Regulation 13) under relevant legislation to 2.2.7 3.2.1.2 ensure custodial responsibilities are well‐defined for 3.5.2.1 producers and consumers connecting to the NPI. Endorse measures and 4.2.1.1 Certification will ensure uniform infrastructure and data 4.3.1* responsibilities for 4.3.3 standards are enforced to promote equitable access in certifying access to NPI 4.4.7 downstream wholesale and retail markets. services 5.3* 6.3.2* • The NPI data custodian should coordinate compliance and 6.4* certification procedures with responsible authorities121 within government and industry.

121 E.g., ICSM, Civil Aviation Safety Authority (CASA), Australian Communications & Media Authority (ACMA).

230

7.3.1.3 ECONOMIC CRITERIA

TABLE 14: POLICY – ECONOMIC FINDINGS & RECOMMENDATIONS

Summary of Research Findings

Multi‐GNSS technology will generate substantial long‐term benefits for governments, industry and the research community. Rigorous CBA will evaluate the direct and external costs and benefits of improving access to multi‐GNSS technology, with emphasis on the social utility gains that are typically overlooked in private cost‐benefit investment decisions. CBA will determine the extent to which government policy is needed to fund and regulate access to existing and future infrastructure and positioning services within a broader NPI.

Chapters Response to Research Findings Recommendations • Undertake rigorous CBA to evaluate the marginal utility

3.5* (across Australia and the Asia‐Pacific) of accessing high Undertake rigorous Cost‐ 4.2* accuracy positioning services to guide policy and Benefit Analysis to 4.3* investment decisions by government and industry. 4.4* evaluate the direct and 5.3.2* • Ensure CBA captures the future cross‐sectoral benefits of external value of 6.2.4* certifying infrastructure quality and endorsing open data creating a single point of 6.3* access to a NPI 6.4* standards through a centralised governance structure with a single point of access.

4.2.3 4.2.5* • Ensure pricing policies for accessing the NPI align with Develop a whole‐of‐ 4.3.2.2 5.3.2* broader information access policies of Federal, State and government data pricing 6.2.2.2 Territory governments. policy 6.2.3* 6.4*

231

7.3.2 INVESTMENT

Public and private investment is needed to deploy, operate and maintain CORS infrastructure and positioning services across Australia. Commercial investment is typically justified on the grounds that consumer demand will provide a suitable RoI to recover fixed‐costs and earn profit where possible. Public funding has also been justified on the grounds that commercial positioning services managed by governments can function on a competitive neutral basis. However, the public good benefit of investing in geodetic infrastructure to support positioning activities across the entire economy remains a primary justification for Australian Government investment. A NPI should therefore coordinate access to public and privately funded infrastructure through a sustainable business model.

Providing a single point of access to infrastructure owned by public and private stakeholders will require a revenue stream to compensate ongoing deployment, operational and maintenance costs (i.e., based on NPV of current investment). The type of funding used to generate this revenue will depend on who manages and operates the NPI. Public funding could be based purely on tax dollars, or include some form of cost‐recovery mechanism by enforcing access fees on producers and consumers. Depending on the adopted positioning technique and level of existing private ownership, full privatisation of the NPI would potentially require a level of compensation for purchasing existing government infrastructure (up to 75% of which is owned by governments in Australia), or paying a licensing fee if existing governments are to retain ownership. Duplication of existing infrastructure is the worst case scenario where public and private investment continues independently.

A hybrid public‐private partnership model (Australian Government, 2008) is also possible whereby a combination of funding is used to finance, build and maintain physical infrastructure and to operate selected positioning services. Whilst details of the policy, financial structure and guidelines pertaining to each of these funding options are beyond the scope of this thesis, technical, institutional and economic criteria for choosing the appropriate funding model are identified in the following Sections.

232

7.3.2.1 INSTITUTIONAL CRITERIA

TABLE 15: INVESTMENT – INSTITUTIONAL FINDINGS & RECOMMENDATIONS

Summary of Research Findings

Institutional requirements for managing and operating a NPI vary depending on who funds the NPI. Existing sources of funding should be leveraged where possible from across government to support arguments for new investment, in light of the cross‐sectoral benefits positioning infrastructure creates (i.e., evidenced by the value that existing cross‐sector funding initiatives create). Regardless of the chosen funding model, government has a role in developing policy and regulations that protect critical positioning infrastructure, and promote equitable access to this infrastructure in order to generate positive externalities and maximise benefits from existing investment.

Chapters Response to Research Findings Recommendations • Identify funding sources from existing spatial programs (e.g., geodetic contributions) and cross‐sectoral programs 3.5.2* within government (e.g., regional innovation, transport, 4.2.1* Identify existing and new 4.2.4 meteorology), particularly from departments that already sources of public funding 4.2.5.1 benefit from accessing positioning infrastructure and 4.4.7 from Federal, State and information. 5.3.2* Territory governments 6.1.2.2 • Identify new funding initiatives (e.g., new policy proposals) 6.4.3* within government that can be leveraged to support development of the hard and soft infrastructures for a NPI.

2.2.7 4.2.5* • Investigate national policies (e.g., data access and pricing 4.3.2* 4.4.6* policies) and business models relevant to procuring public‐ Investigate public‐ 6.1.2.2 private partnerships to fund infrastructure projects in the private partnerships 6.2.1.3 national interest. 6.2.3* 6.4* 2.5 • Identify relevant policy, legislation and regulations (e.g., Investigate policy, 3.2* national security, spectrum licenses, royalties/taxes, anti‐ legislative and 4.2* trust policy) that would apply to a public and/or privately regulatory conditions for 6.2* 6.4* funded NPI. privatisation

233

7.3.2.2 TECHNICAL CRITERIA

TABLE 16: INVESTMENT – TECHNICAL FINDINGS & RECOMMENDATIONS

Summary of Research Findings

Capital and operational costs for supplying CORS infrastructure and positioning services must be accurately identified to model current and future investment profiles for a NPI. Exploring the trade‐off between deploying and licensing data will inform future investment decisions and help differentiate the roles of government and industry towards funding a NPI.

Chapters Response to Research Findings Recommendations 3.2* 3.4* • Identify the fixed and variable costs of establishing and 4.2* operating positioning infrastructure and positioning Quantify the direct and 4.3* 4.3.1* services on a national scale. external costs and 6.2* benefits of establishing a 3.5* NPI with a single point of • Ensure all external costs (negative externalities) and 4.4.7 access 6.2.4* benefits (positive externalities) of establishing a NPI are 6.3* identified and modelled as part of a CBA. 6.4.3*

234

7.3.2.3 ECONOMIC CRITERIA

TABLE 17: INVESTMENT – ECONOMIC FINDINGS & RECOMMENDATIONS

Summary of Research Findings

Cost‐recovery models for infrastructure investment vary depending on the type of public and/or private funding model that is adopted. A sustainable funding model will be critical to ensuring ongoing access to the NPI, and maintaining infrastructure and service standards to align with multi‐GNSS developments and international best‐practice standards. Cost‐recovery models can limit economic value if access costs for producers and consumers of positioning services are too high, which limits direct and external benefits in downstream user markets.

Chapters Response to research findings Recommendations • Investigate funding mechanisms for recovering public and 4.2.3 private investment, including government taxes, 4.2.5* subscription fees and data licensing. CBA will help to Develop sustainable 4.3.2* 6.2.2* determine which funding model maximises access to a NPI cost‐recovery models to 6.2.3* for public good and commercial purposes. The chosen ensure ongoing funding 6.3.2* funding model will influence pricing models in downstream 6.4* wholesale and retail markets.

235

7.3.3 INFRASTRUCTURE & SERVICES

A future NPI will likely integrate a multitude of GNSS and non‐GNSS PNT technologies with a focus on coordinating and optimising the nation’s supply of positioning infrastructure, thereby creating a single point of access to real‐time high accuracy position information referenced to the NGRS. NPI policies and investment strategies will guide technical, institutional and economic planning for coordinating and optimising access to CORS infrastructure on a national scale. CORS infrastructure and associated positioning services must therefore be designed for multi‐GNSS compatibility and to deliver the minimum service level needed to satisfy current and future demand from a growing network of users.

7.3.3.1 INSTITUTIONAL CRITERIA

TABLE 18: INFRASTRUCTURE & SERVICES – INSTITUIONAL FINDINGS & RECOMMENDATIONS

Summary of Research Findings

The roles, responsibilities and rights of all stakeholders who contribute infrastructure and manage services connected to the NPI should be clearly defined in accordance with national policy, standards and legislation.

Chapters Response to Research Findings Recommendations • CORS infrastructure and positioning services should be certifiable and legally traceable in accordance with national policy and standards. Develop procedures for • CORS infrastructure and positioning services should comply certifying CORS 2.2.7 with legislative requirements at State, Territory, Federal infrastructure and 3.2* and international levels of government (e.g., planning and 3.5* associated positioning privacy laws, ICAO122 specifications). 4.3.3 services in accordance 5.3.2* • Certification procedures should be clearly documented to 6.2.4* with national policy, define the roles, responsibilities and rights of each 6.4* legislation and stakeholder. regulations • Certification should be undertaken directly by the responsible authority (e.g., the NPI custodian) or by an accredited third‐party organisation.

122 International Civil Aviation Organization.

236

7.3.3.2 TECHNICAL CRITERIA

TABLE 19: INFRASTRUCTURE & SERVICES – TECHNICAL FINDINGS & RECOMMENDATIONS

Summary of Research Findings

CORS infrastructure should be designed for multi‐GNSS compatibility, with multiple layers of redundancy for power, communications, data storage and security. Raw and corrected data should be distributed and archived in a secure, highly redundant ICT infrastructure with data processing centres distributed across different geographic regions. Standardised performance procedures and metrics are needed to monitor system performance against minimum service level standards.

Chapters Response to Research Findings Recommendations • Identify and document hardware, software & data formats that are needed to establish, operate, integrate, maintain and access positioning infrastructure in accordance with Develop and formally national standards (e.g., ICSM standards and guidelines). document positioning Positioning infrastructure includes, but is not limited to: 3.2* infrastructure o Multi‐GNSS technology 3.4* specifications in 3.5* o CORS infrastructure components (see Table 5) 4.3.3 accordance with national o Network infrastructure (e.g., Data, Analysis and Control policy, standards and Centres; Virtual Private Networks) legislation o Positioning techniques o Data standards (e.g., RTCM) o SLM criteria

3.2* • Service performance should be measurable against 3.4* national service level standards (e.g., SLAs) by defining Key Define Key Performance 4.2.2.5 Performance Indicators (e.g., for accuracy, availability, and Indicators for measuring 4.2.5* 6.2.3.2 quality assurance) that specify the minimum performance service level standards 6.3.2.4 needs of governments, industry and society.

2.5 Network and process • Data should be networked and processed within a secure 3.2* data within a secure and 4.4.6.2 ICT platform, with multiple layers of redundancy for power, highly redundant ICT 5.3.2* communications and data storage. 6.3.3* platform

237

7.3.3.3 ECONOMIC CRITERIA

TABLE 20: INFRASTRUCTURE & SERVICES – ECONOMIC FINDINGS & RECOMMENDATIONS

Summary of Research findings

Commercial investment in CORS infrastructure has been prioritised in geographic regions where demand for high accuracy position information is greater. Identifying the location and custodian of existing infrastructure is critical to examining how previous investment can be leveraged to increase access within and outside of existing service coverage regions, particularly as new positioning techniques such as RT‐PPP become available. Coordinating the supply of CORS infrastructure therefore minimises duplication and over‐investment to prioritise future investment in regions where coverage has not yet been enabled. Authoritative location and metadata will inform production, distribution and pricing decisions for supplying CORS infrastructure to maximise public good and commercial value.

Chapters Response to research findings Recommendations Identify and map the • Identify geographic regions where duplication and over‐ 3.5.2.5 geographic location of investment has occurred, and is likely to occur in the 4.3* existing and future 5.3.2* absence of coordinated investment by governments and positioning 6.3.2* industry. infrastructure & services

Prioritise future • Future investment in a NPI should be prioritised in regions investment in 3.5* where market growth and public good benefits have been 4.3* geographic regions identified so as to increase social utility and promote 5.3.2* where public good competition in downstream commercial markets, thereby 6.3* benefits and commercial maximising benefits at minimum cost. demand are higher

238

7.3.4 ACCESS

The need to increase access to CORS infrastructure and high accuracy positioning services is the research hypothesis examined throughout this thesis. Technical, institutional and economic barriers must be addressed collectively if producers and consumers of GNSS position information are to benefit from a NPI that enables a single point of access through greater coordination of government and industry positioning activities across Australia. Policy and investment strategies can be implemented that improve and standardise access by enforcing SLAs, VAR Agreements, DALAs and EULAs between providers and users of positioning infrastructure. Collectively, these agreements specify the institutional, technical and economic criteria that are needed to ensure minimum access standards are available to consumers.

The level of access made available to producers and consumers of positioning services ultimately influences the design of pricing strategies used to recover investment costs. Increasing access creates a competitive market in which a range of differentiated products and services are made available at different costs to a larger network of users.

7.3.4.1 INSTITUTIONAL CRITERIA

TABLE 21: ACCESS – INSTITUIONAL FINDINGS & RECOMMENDATIONS

Summary of Research Findings

Rights and responsibilities for accessing positioning data are influenced by national policy (Section 6.4), and are enforceable via well‐defined service level and licensing agreements between data custodians, SPs and users. VAR Agreements, DALAs and EULAs are used to specify liabilities, Intellectual Property rights, sub‐licensing conditions, fees and warranties for accessing data. SLM frameworks are established to specify the people, processes and technology needed to manage network resources and to enforce SLAs that document priorities, responsibilities, guarantees, warranties, locations, costs and times with respect to service performance.

Chapters Response to Research Findings Recommendations • Uniform licensing agreements between data custodians, SPs and users are needed to specify access rights, terms Develop and enforce 4.2.2* and conditions for distributing data through a single point uniform licensing 4.2.5* 4.4* of access. Uniform licensing and access agreements (e.g., agreements for 5.3.2* similar to the NBN WBA) will increase access in distributing data 6.2.3.1 downstream wholesale and retail markets to avoid costly through a single point of 6.4* and time consuming processes for negotiating contracts access with individual providers.

239

• SLAs should be developed to formalise commitments 4.2.2.5 5.3.2* between providers and consumers according to national Develop and enforce 6.2.3* policy and standards that reflect critical infrastructure Service Level Agreements 6.4.1* requirements and consumer expectations.

240

7.3.4.2 TECHNICAL CRITERIA

TABLE 22: ACCESS – TECHNICAL FINDINGS & RECOMMENDATIONS

Summary of Research findings

The product that is delivered to consumers from positioning services is the digital information contained within the data message (e.g., raw or corrected data), which can be distributed via radio, mobile or satellite communications infrastructure. This data is encoded using open and/or proprietary data formats which can influence the type of equipment and software that producers and consumers use to access and apply the data. Open data standards allow anyone to access the same datasets (subject to subscriptions and fees that prevent unauthorised access).

Chapters Response to research findings Recommendations • Data from positioning infrastructure and services should be 3.4.4 distributed in standardised data formats (e.g., RTCM) that 4.4.6* Develop/adopt open align with international best practice (e.g., IGS). Note that 4.4.7 data standards 6.2.4* standardised data correction messages can potentially be optimised for the Australasian region.

2.4.3.7 • Data should be distributed via a secure and highly Distribute data from a 2.5 redundant ICT platform with a single point of access for highly redundant single 3.2* distribution via multiple communication mechanisms (e.g., point of access via 4.4.6.2 5.3.2* radio, satellite and mobile), particularly in regions where multiple communications 6.3.3* mobile telecommunications infrastructure is not available. systems

2.3* 2.4* • A minimum level of service accuracy, coverage, availability 2.5 Deliver a minimum level and quality should be accessible to all users (e.g., similar to 3.3* of service performance 3.4* WAAS) subject to national policy and in accordance with accessible to all users 3.5* public good expectations. 4.2.2.5 6.2.3.2 • Quality assurance procedures (e.g., alert systems and 3.3* Monitor service disaster recovery procedures) and programs (i.e., for 3.4* performance and access 4.2.2.5 independent quality control) should be developed and requirements against 6.2.3.2 implemented to monitor access and service performance 6.3.2.1 KPIs against KPIs specified within SLAs.

241

7.3.4.3 ECONOMIC CRITERIA

TABLE 23: ACCESS – ECONOMIC FINDINGS & RECOMMENDATIONS

Summary of Research findings

The level of positioning data access that is made available to consumers influences the economic value and social utility that is generated from applying position information. The external costs and benefits of producing position information are not typically considered in private investment decisions, meaning access may be less than is socially optimal. Data access and pricing policies can be implemented by government to standardise and improve access for producers and consumers. Uniform data licensing arrangements can increase data access and price competition in downstream wholesale and retail markets. Free access by government may ultimately be justified based on public good arguments for safety, national security and in alignment with foreign policy. A mixture of government and commercial investment has been identified in Australia and is likely to continue as commercial providers identify value from leveraging a larger source of input data through a single point of access (the NPI), which will facilitate innovate product development for an expanding network of users.

Chapters Response to research findings Recommendations • Pricing strategies should be implemented that align with Implement data pricing national data access and pricing policies (e.g., policies that maximise Commonwealth Policy on Spatial Data Access and Pricing) access for public good to maximise direct and external benefits across the and commercial 4.2.3 Australian economy. purposes 4.2.5* 6.2.2* • Subject to government regulations on market competition 6.2.3* (e.g., price regulation, anti‐trust policy), value‐based 6.3.3* Minimise the wholesale pricing strategies should be competitive so as to expand 6.4* and retail cost of the network users, thereby decreasing the ATC of supplying accessing positioning information products. Encouraging market competition will data potentially decrease the wholesale and retails costs of accessing positioning data.

242

7.4 CONCLUSION

Chapter 7 has consolidated findings from this thesis to provide technical, institutional and economic recommendations for establishing a NPI. Collectively, these findings and recommendations establish the NPI Planning Framework, which will guide decision‐making on policy, investment, infrastructure and services, and access criteria for establishing a NPI. The goal of the Framework is to assist governments and industry to increase the utility of existing and future CORS infrastructure across Australia, recognising that increased access generates greater value for producers and consumers of positioning services, which generates public good and commercial value in the Australia economy.

243

CHAPTER 8 THESIS CONCLUSION

THESIS CONCLUSION

Throughout this thesis, relevant information and evidence has been compiled and analysed in a technical, institutional and economic context to identify and evaluate criteria (e.g., costs/benefits) underpinning government and industry decisions to fund, deploy, operate and manage high accuracy positioning infrastructure and services in Australia.

Independent ownership and management of separate CORS networks and product and service offerings was found to increase infrastructure duplication and overinvestment; create inconsistent data and service standards; limit measures of quality control; constrain wholesale and retail competition for expanding service coverage; and create diverging views on the roles and responsibilities of governments and industry for owning, maintaining, expanding and delivering positioning services.

A unique economic context was established to demonstrate how these technical, institutional and commercial barriers can be addressed if raw data streams (an information good) are licensed to enable positioning services from multiple suppliers, instead of duplicating the underlying infrastructure (an industrial good) needed to produce the data streams.

Data licensing facilitates interoperability and market competition by promoting ‘open’ access compared with proprietary approaches (i.e., ‘closed’ access). This was evidenced by existing data licensing arrangements in VIC and NSW which have increased price competition in retail markets, shifting commercial investment towards innovating and customising positioning solutions (rather than duplicating CORS) across multiple sectors of the economy (e.g., agriculture, mining, construction). Market demand for positioning services was found to be strongest in VIC, NSW, ACT and parts of TAS, QLD and SA, predominantly where multiple SPs have licensed access to government‐owned CORS, and deploy infill sites where high fixed‐costs are justified.

In WA, NT and parts of SA and QLD, government and industry investment, and subsequent data licensing was found to be lacking. Small pockets of high accuracy NRTK coverage have been enabled by individual providers within these regions, but data licensing has been limited. Cost barriers are therefore higher for third‐party SPs wishing to enter the market in regions such as these, where the fixed‐cost of duplicating a natural monopoly’s investment is high compared with data licensing costs. Private investment in single‐base RTK (i.e., non‐networked) infrastructure is therefore higher in these ‘underserviced’ regions. Investment in single‐base CORS can lower fixed‐costs in the short term, but significantly limit the longer‐ term productivity benefits (coverage, accuracy, quality control, multi‐GNSS and datum compatibility) that investment in networked infrastructure enables directly and externally to positioning providers and users.

In light of these findings, this research concludes that SPs realise greater technical, institutional and economic benefits from licensing data rather than duplicating infrastructure, which demonstrates that data licensing from a single natural monopoly provider (with one or multiple stakeholders) is the most cost‐effective way to produce and access high accuracy positioning services nationally. Evidence of the

246 direct RoI and positive externalities that a single point of access to positioning infrastructure creates was evidenced by examples in VIC and NSW. The Australian Government’s decision to create a single point of access to national broadband infrastructure provided a useful analogy for comparing why a single point of access to nation‐building infrastructure is considered more equitable to society.

A single point of access reduces duplication by coordinating network planning and design, which lowers the cost of producing high accuracy positioning services, thereby lowering access costs for consumers; all of which minimises deadweight loss to the economy. Data licensing is thus a method of coordinating access to data from existing and future CORS infrastructure nationally through a single point of access: the NPI.

Demand for positioning services is likely to increase as greater access through the NPI creates price competition in retail markets and drives SPs to innovate value‐added services that generate greater revenue. Current demand for high accuracy positioning services is difficult to measure in the absence of a NPI, given service coverage and performance is inconsistent amongst different providers, meaning their individual positioning ‘products’ (e.g., coverage extents) are difficult to compare.

Feedback from governments and industry indicates that total market demand for high accuracy positioning subscriptions is below 5,000 users nationally; less than 0.03% of the population, even though up to 83% of the population can access some form of high accuracy positioning service. This finding implies that the market has not yet reached critical mass, particularly in light of growth expectations across many sectors of the Australian economy. To address this market failure, the question of whether a multi‐GNSS future will create a consumer‐driven and infrastructure‐driven market in which high accuracy positioning becomes ‘the standard’ (i.e., the default available to, and expected by the Australian user community) was addressed by this research. The NPI’s role in facilitating and accelerating this transition was examined.

This research suggests that the innovation and free enterprise that proliferated in the absence of Selective Availability over a decade ago is indicative of the social, economic and environmental value that integrated multi‐GNSS technology will enable in Australia. Just as technical, institutional and economic uncertainties were analysed before the decision to switch off Selective Availability, similar uncertainties have been raised within this thesis to inform discussions on the value that a NPI will generate. Fittingly, the NPI concept is in many ways comparable to the (financial) marginal cost of removing Selective Availability, given investment in a NPI would pale into insignificance compared to the billions of dollars that foreign governments have invested in developing GNSS technology.

But a cost is a cost, and the opportunity (value) of that cost (investment in a NPI) must be identified and communicated well beyond the spatial sector alone. More important perhaps is the cost of not equipping society with a NPI that will maximise public and commercial benefits through enhanced and open access to all new GNSS/RNSS constellations, which Australia continues to access as a free‐rider.

247

In the absence of sovereign investment in a GNSS, RNSS or SBAS capability, the NPI presents a logical, unique and globally significant opportunity to maximise the utility of all existing and future GNSS resources. These resources are not simply the components of infrastructure used to establish the NPI, but any device or infrastructure that receives standardised and certified multi‐GNSS information from the NPI.

Technical, institutional and economic criteria and recommendations for coordinating access to existing and future CORS infrastructure have therefore been proposed through this research, and consolidated in the proposed NPI Planning Framework. By communicating and consolidating the unique spatial and economic evidence presented in this thesis, the Framework will inform future policy and investment decisions for generating downstream public good and commercial value from positioning infrastructure, and the services that are developed and delivered using this infrastructure. To achieve this outcome, the Framework identifies and responds to the complex and multi‐faceted decisions faced by government and industry providers towards optimising the national supply of CORS infrastructure in a multi‐GNSS future, at the lowest cost to society, while maximising the benefits and utility of that infrastructure.

Providing Australia with the positioning resources needed to benefit from, and contribute to a multi‐ GNSS future, in cooperation with local, regional and global partners, is in the technical, institutional and economic interests of all Australians.

248

LEGISLATION

Australian Competition and Consumer Act 2010 Broadcasting Services Act 1992 National Electricity (South Australia) Act 1996 National Electricity (Victoria) Act 2005 National Measurement Act 1960 National Measurement Regulations 1999 Telecommunications Act 1997 Space Activities Act 1998

REFERENCES

AATS (1985), A Space Policy For Australia: A report prepared for the Minister of Science by the Australian Academy of Technological Sciences, Australian Academy of Technological Sciences, Melbourne, Victoria.

ABS (2012a), 1270.0.55.001: Volume 1 ‐ Main Structure and Greater Capital City Statistical Area (GCCSA), Australian Bureau of Statistics (ABS), viewed 20 December 2012, .

ABS (2012b), 7501.0 ‐ Value of Principal Agricultrual Commodities Produced, Preliminary 2011‐12, Australian Bureau of Statistics (ABS), viewed 14 December 2012, . ABS (2012c), Australian Statistical Geography Standard (ASGS), Australian Bureau of Statistics (ABS), viewed 23 November 2012, .

ACIL ALLEN Consulting (2013), The Value of Augmented GNSS in Australia: An overview of the economic and social benefits of the use of augmented GNSS services in Australia, Prepared for the Department of Industry, Innovation, Climate Change, Science, Research, and Tertiary Education.

AdV (2011), SAPOS ‐ Precise positioning in location and height, Arbeitsgemeinschaft der Vermessungsverwaltungen (AdV) der Länder der Bundesrepublik Deutschland. AdV (2013), Satellitenpositionierungsdienst (SAPOS), Arbeitsgemeinschaft der Vermessungsverwaltungen (AdV), viewed 21 January 2014, . Airservices Australia (2012), Ground Based Augementation System, viewed 10 January 2014, . Anderle R (1976), Point positioning concept using precise ephemeris, Proceedings of the International Geodetic Symposium, Las Cruces, New Mexico State University, 1, pp.47‐75. ANZLIC (2010), National Positioning Infrastructure Policy, The Spatial Information Council (ANZLIC), viewed 02 May 2011, .

249

Arrow KJ (1959), Economic Welfare And The Allocation Of Resources For Invention, RAND Corporation. ASC (2012), Australian Strategic Plan for GNSS, Australian Spatial Consortium (ASC). AuScope (2012), Australian Geophysical Observing System, AuScope, viewed 6 October 2013, . AuScope Geospatial Team (2008), New Geodetic Infrastructure for Australia ‐ The University Component of the AuScope Geospatial Team, Journal of Spatial Science, 53 (2): pp.pp.65 ‐ 80. Australian Government (2001), Australian Government Policy on Spatial Data Access and Pricing, Office of Spatial Data Management (OSDM), Canberra, ACT. Australian Government (2008), National Public Private Partnership Policy Framework, Infrastructure Australia, Canberra, Australia. Australian Government (2009a), Australian Space Research Program, Space Policy Unit, viewed 8 July 2013, . Australian Government (2009b), Expense Measures: Innovation, Industry, Science and Research Australian Government, viewed 8 July 2013, . Australian Government (2010), Critical Infrastructure Resilience Strategy, Attorney General's Department, Canberra, Australia.

Australian Government (2011), Satellite Based Augmentation System Review, Department of Infrastructure and Regional Development, Canberra, Australia.

Australian Government (2013a), Australia's Satellite Utilisation Policy, Department of Industry Innovation Climate Change Science Research and Tertiary Education, Canberra, ACT.

Australian Government (2013b), Reef Rescue, viewed 25 Ocotober 2013, . Australian Government (2013c), Statistical Data Integration Involving Commonwealth Data, National Statistical Service, viewed 30 September 2013, .

Austroads (2011), Evaluation of the Potential Safety Benefits of Collision Avoidance Technologies Through Vehicle to Vehicle Dedicated Short Range Communications in Australia, Austraods Research Report, Austoads, Sydney, NSW, pp.33. Austroads (2013), Road Design Guides, viewed 26 August 2013, . BAE (2013), Navigation Via Signals of Opportunity (NAVSOP), BAE Systems Australia, viewed 14 January 2014, . Bates B 1990, Information as an Economic Good: A Re‐Evaluation of Theoretical Approaches, In: Ruben D,Lievrouw L (ed.) Mediation, Information, and Communication: Information and Behavior, New Brunswick, NJ, Transaction Publishers. Bisnath S, Collins P (2012) Recent Developments in Precise Point Positioning, Geomatica 66 (2): 103‐111. Bisnath S, Gao Y (2009), Current State of Precise Point Positioning and Future Prospects and Limitations, International Association of Geodesy Symposia ‐ Observing our Changing Earth, Perugia, Italy, Sideris M (ed.), 133, pp.615‐623.

250

Blick G, Sarib R (2010), The Geodetic Infrastructure in Australia and New Zealand: Differences and Similarities, FIG Congress, Sydney, Australia. BoM (2014), Radio and Space Weather Services, Australian Government Bureau of Meteorology, viewed 29 January 2014, . Boriskin A, Kozlov D, Zyryanov G (2012), The RTCM Multiple Signal Messages: A New Step in GNSS Data Standardization, Proceedings of the International Technical Meeting of The Satellite Division of the Institute of Navigation, Nashville, TN, pp.2947‐2955. Bowman K (2008), Economic and Environmental Analysis of Converting to Controlled Traffic Farming, 6th Australian Controlled Traffic Farming Conference, Dubbo, New South Wales. Brown N (2006), Sequential Phased Estimation of Ionospheric Path Delays for Improved Ambiguity Resolution over Long GPS Baselines Doctor of Philosophy, Department of Geomatics, The University of Melbourne, Melbourne. Brown N, Keenan R, Richter B, Troyer L (2005), Advances in Ambiguity Resolution for RTK Applications Using the New RTCM V3.0 Master‐Auxiliary Messages, ION GNSS 18th International Technical Meeting of the Satellite Division, Long Beach, CA, pp.78‐80. Burns D, Sarib R (2010), Standards and Practices for GNSS CORS Infrastructure, Networks, Techniques and Applications, FIG Congress 2010, Sydney, Australia.

C.R.Kennedy (2013), Survey Solutions, viewed 6 October 2013, . Caissy M, Agrotis L, Weber G, Hernandez‐Pajares M (2012), Innovation: Coming Soon: The International GNSS Real‐Time Service, GPS World, Gibbons Media and Research, LLC.

Can‐Net (2013), Can‐Net, Cansel, viewed 6 October 2013, . Chassagne O (2012), The Future of Satellite Navigation: One‐Centimeter Accuracy with PPP?, InsideGNSS, 7 (2): Gibbons Media and Research, LLC.

Commonwealth of Australia 2004. Australian Government Competitive Neutrality ‐ Guidelines for Managers. Canberra.

Cranenbroek J, Lui V, Keenan R (2006), Making Profitable GNSS RTK Network Infrastructure, Journal of Global Positioning Systems, 5 (1‐2): pp.58‐61. CRCSI (2013a), Next Generation Datum (Project 1.02), viewed 23 September 2013, . CRCSI (2013b), Precise Positioning: Context of Project 1.1, Cooperative Research Centre for Spatial Information (CRCSI), viewed 17 November 2013, . Cruising Heights (2011), Fourth Air Services Negotiation Conference: GAGAN ushers flying leap for aviation, Cruising Heights, Newsline Publications Pvt. Ltd. CSIS (2003), US Japan Space Policy: A Framework for 21st Century Cooperation, Center for Strategic International Studies (CSIS), Washington D.C. CSNO (2012), BeiDou Navigation Satellite System Signal In Space Interface Control Document ‐ Open Service Signal B1I, China Satellite Navigation Office (CSNO), Version 1. Dach R, Hugentobler U, Fridez P, Meindl M (2007), Bernese GPS software version 5.0, Astronomical Institute, University of Bern.

251

Dawson J, Woods A (2010), ITRF to GDA94 Coordinate Transformations, Journal of Applied Geodesy, 4 pp.189‐199. De Smet P (2011), The European GNSS Programmes EGNOS and Galileo, United Nations for Outer Space Affairs (UNOOSA), viewed 10 January 2014, . Dempster AG, Rizos C (2009), Implications of a "System of Systems" receiver, Surveying and Spatial Sciences Biennial International Conference, Adelaide, Australia. DEPI (2013a), Positioning Regional Victoria (PRV) Project, Department of Environment & Primary Industries (DEPI), viewed 3 November 2013, . DEPI (2013b), Vicmap Position ‐ GPSnet, Department of Environment and Primary Industries (DEPI), viewed 30 September 2013, . Dobes L (2008), A Century of Australian Cost‐Benefit Analysis, Office of Best Practice Regulation, Department of Finance and Deregulation, Canberra, ACT. DoD (2008), Global Positioning System: Standard Positioning Service Performance Standard, US Department of Defense (DoD) Position Navigation and Timing Exectuive Committee.

Doppler CJ (1842), Ueber das farbige Licht der Doppelsterne und einiger anderer Gestirne des Himmels, Abhandlunsen der Koniglich Bohmischen Gesselschaft der Wissenschaften, 1 pp.467‐482.

Dos Santos Ferreira R, Thisse JF (1996), Horizontal and vertical differentiation: The Launhardt model, International Journal of Industrial Organization, 14 (4): pp.485‐506.

DPIPWE (2012), Innovative Farming Practices Initiative (IFPI), Department of Primary Industries, Parks, Water and Environment (DPIPWE), viewed 30 September 2013, .

DSE (2009), Data Access Licence Agreement, Department of Sustainability and Environment (DSE), Melbourne, VIC.

Else P, Curwen P (1990), Principles of Microeconomics, Psychology Press.

ESA (2010), Galileo Services, European Space Agency (ESA), viewed 8 January 2014, . ESA (2013), Navipedia, European Space Agency (ESA), viewed 8 January 2014, . ESPI (2012), Space Policies, Issues and Trends in 2011/2012 (ESPI Report 42), European Space Policy Institute (ESPI). Euler HJ, Keenan R, Zebhauser B (2001), Study of a Simplified Approach in Utilizing Information from Permanent Reference Station Arrays, ION GPS 2001, Salt Lake City, Utah. Euroconsult (2012), Profiles of Government Space Programs, Euroconult EC, 2012 Edition. European Commission (2011), Report from the Commission to the European Parliament and the Council: Mid‐term Review of the European Satellite Radio Navigation Programmes, European Commission.

European Commission (2013), Space ‐ European Space Policy, viewed 24 April 2013, .

252

European Union (2010), European GNSS (Open Service) Signal In Space Interface Control Document, European Union, 1.1. FAA (2013), NextGEN ‐ NextGEN Implementation Plan, Federal Aviation Administration. FAA, DOT (2008), Global Positioning System Wide Area Augmentation System (WAAS) Performance Standard, US Federal Aviation Administration (FAA) and US Department of Transport (DoT). FBA (2013), New CORS network to connect CQ growers, Fitzroy Basin Association (FBA), viewed, . Federal Space Agency (2013), On approving the plan to implement the National Space Programme, 2013‐2020, for 2013 and the planning period 2014‐2015, The Russian Government, viewed 8 January 2014, . Feng Y, Li B (2008), A Benefit of Multiple Carrier GNSS Signals: Regional Scale Network‐Based RTK with Doubled Inter‐Station Distances, Journal of Spatial Science, 53 (2). Feng Y, Rizos C (2005), Three carrier approaches for future global, regional and local GNSS positioning services: concepts and performance perspectives, 18th International Technical Meeting of the Satellite Division of the U.S. Institute of Navigation, Long Beach, California, pp.2277‐2287. Fisher K (2005), The Navigation Potential of Signals of Opportunity‐Based Time Difference of Arrival Measurements, Doctor of Philosophy, Department of The Air Force Air University, Air Force Institute of Technology, Ohio.

Floyd R (1978), Geodetic Bench Marks, NOAA Manual NOS NGS 1, National Oceanic and Atmospheric Administration (NOAA) ‐ National Ocean Survey (NOS).

Frank R, Jennings S, Bernanke B (2008), Principles of Microeconomics, Mc Graw‐Hill Higher Education.

Fraser R (2007), A Rigorous Approach to the Technical Implementation of Legally Defined Marine Boundaries, Doctor of Philosophy, Geomatics, The University of Melbourne, Melbourne.

Fraser R, Donnelly N (2010), Progress Towards a Consistent Exchange Mechanism for Geodetic Data in Australia and New Zealand, FIG Congress 2010, Sydney, Australia.

Fujiwara S (2011), QZSS and MSAS, United Nations for Outer Space Affairs (UNOOSA), viewed 10 January 2014, .

GA (2006), Geoscience Australia ‐ GEODATA TOPO 250K Series 3, viewed 14 November 2012, . GA (2013), Australian Fiducial Network, Geoscience Australia, viewed 16 January 2014, . Ganeshan A (2012), GAGAN: Status and Update, Coordinates, September 2012, Centre for Geo‐ Information Technologies (cGIT), Delhi, India. Gauss CF (1809), Theoria Motus Corporum Coelestium in Sectionibus Conicis Solem Ambientium, Hamburg, English Translation (1857) by C.H. Davis, Little, Brown & Co., Boston. Geoscience Australia (2011a), Australian Regional Global Navigation Satellite System Network, viewed 06 August 2011, .

Geoscience Australia (2011b), National Geospatial Reference System, viewed 24 Novemeber 2011, .

253

Geoscience Australia 2012. National Positioning Infrastructure Plan ‐ Terms of Reference. Canberra. Geoscience Australia (2013a), Asia‐Pacific Refernce Frame (APREF), viewed, . Geoscience Australia (2013b), Data Access Policy, Geoscience Australia, viewed 9 October 2013, . Geoscience Australia (2013c), Regulation 13 Certificates, Geoscience Australia, viewed 6 October 2013, . GGOS (2011), Vision, Mission, Goals and Tasks, Global Geodetic Observing System (GGOS). Gibbons G (2007), Speaking with Authority: Galileo's Lead Agency in a Changing World, Gibbons Media and Research, LLC, viewed 5 July 2013, . Gibbons G (2013), BeiDou to Restart Satellite Launches Next Year, Shift B1 Signal Frequency after 2016, Gibbons Media and Research, LLC, viewed 9 January 2014, . Global Positioning Systems Directorate (2011), Navstar GPS Space Segment/Navigation User Segment Interfaces, Global Positioning Systems Directorate Systems Engineering & Integration Interface Specification IS‐GPS‐200

GLONASS Union (2013), Regulatory Control, Non‐Commercial Partnership for the Development and use of Navigation Technologies (GLONASS Union), viewed 8 January 2014, .

Glowacki TJ, Penna NT, Bourke WP (2006), Validation of GPS‐based estimates of integrated water vapour for the Australian region and identification of diurnal variability, Australian Meteorological Magazine, 55 (2): pp.131‐148.

Goad C, Goodman L (1974), A Modified Hopfield Tropospheric Refraction Model, Annual Fall Meeting of the American Geophysical Union, San Francisco. Government of Japan (2009), Basic Plan for Space Policy, Strategic Headquarters for Space Policy.

Government of Japan (2011), Basic policy on the implementation of the operational QZSS project, Cabinet Office, Government of Japan, viewed 5 July 2013, . Government of Japan (2013), Basic Plan for Space Policy, Strategic Headquarters for Space Policy. GPS World (2013a), Experts Meet to Standardize Satellite Augmentation Systems, Gibbons Media and Research, LLC, viewed 10 January 2014, . GPS World (2013b), GAGAN Certified for Aviation in India, Gibbons Media and Research, LLC, viewed 21 January 2014, . GPS World (2013c), Pacific PNT: GNSS, SBAS Updates, Gibbons Media and Research, LLC, viewed 9 January 2014, . GPS.gov (2010), Joint Announcement by the United States of America and Australia on Bilateral Cooperation in the Civil Use of GPS and Civil Space Activities, viewed 22 April 2013, . GPS.gov (2012), Space‐Based Positioning Navigation & Timing ‐ National Executive Committee, viewed 27 August 2012, .

254

GPS.gov (2013), Official US Government information about the GPS and related topics, viewed 10 April 2013, . GPSD (2012), Interface Specification IS‐GPS‐705: Navstar GPS Space Segment/User Segment L5 Interfaces, Interface Specification IS‐GPS‐200, Global Positioning Systems Directorate (GPSD) ‐ Systems Engineering & Integration. Grgich PM (2008), Improved Processing Models for Network Kinematic GPS Positioning in Sparse Networks, Doctor of Philosophy, Department of Geomatics, The University of Melbourne, Melbourne. GSA (2011), What is EDAS?, European GNSS Agency (GSA), viewed 10 January 2014, . GSA (2012), European GNSS Agency ‐ GNSS Market Report, viewed 30 May 2012, . GSA (2013), GNSS Market Report, Issue 3, European GNSS Agency. Gutierrez P (2013), Galileo Coversation: Regulation, Budget, Markets, and International relations, Gibbons Media and Research, LLC, viewed 5 July 2013, . Haasyk J, Janssen V (2011), The many paths to a common ground: A comparison of transformations between GDA94 and ITRF, IGNSS Symposium 2011, Sydney, New South Wales.

Habrich H (1999), Geodetic Applications of the Global Navigation Satellite System (GLONASS) and of GLONASS/GPS Combinations, PhD Dissertaion, University of Berne, Switzerland.

Hains D (2013), Presentation: What Are The Public And Industry Roles In Canada, GNSS Precise Point Positioning Workshop: Reaching Full Potential, Ottawa, Canada.

Hale M (2007), Identifying And Addressing Management Issues For Australian State Sponsored CORS Networks, Masters Thesis, Department of Geomatics, The University of Melbourne, Melbourne.

Hale M, Collier P, Kealy AN, Ramm PJ, Millner JC (2006), Validating a Model for CORS Network Management, International Global Navigation Satellite Systems Society, IGNSS Symposium 2006, Holiday Inn Surfers Paradise, Australia.

Hale M, Ramm P (2007), GPSnet ‐ Current and Future Developments in GNSS CORS Network Management and Service Delivery, Spatial Science Institute Biennial International Conference, Hobart, Tasmania, Australia, pp.141‐151.

Hale M, Ramm P, Wallace J (2007), Legal positions and Victoria’s GPSnet, Proceedings of Spatial Science Institute Biennial International Conference 2007, Hobart, Australia, pp.14‐18. Harding R (2012), Space Policy in Developing Countries ‐ The Search for Security and Development on the Final Frontier, Routledge. Hausler G (2013), Is PPP the Next Flavour of the Month, Professional Surveyor Magazine, 33 (9): Flatdog Media, Inc., Frederick, MD. Hausler G, Collier P (2013a), National Positioning Infrastructure: Identifying and Evaluating High Accuracy GNSS Service Coverage across Australia, Journal of Spatial Science, 58 (2): pp.191‐214. Hausler G, Collier P (2013b), National Positioning Infrastructure: Where are we now?, International Global Navigation Satellite Systems Society (IGNSS) 2013, Outrigger Hotel, Gold Coast, Australia.

Hein G (2006), GNSS Interoperability: Achieving a Global System of Systems or "Does Everything Have to Be the Same?", Gibbons Media and Research, LLC, viewed 10 November 2013, .

255

Helbling T (2010), What Are Externalities?, Finance & Development, International Monetary Fund, 47. Heo Y, Yan T, Lim S, Rizos C (2009), International Standard GNSS Real‐Time Data Formats and Protocols, International Global Navigation Satellite Systems Society, Holiday Inn Surfers Paradise QLD, Australia. Higgins M (2012), Future Trends in Global Navigation Satellite Systems and Precise Positioning Applications, viewed 30 September 2013, . Higgins MB (2008), An Organisational Model for a Unified GNSS Reference Station Network for Australia, Journal of Spatial Science, 53 (2): pp.81‐95. Hofmann‐Wellenhof B, Lichtenegger H, Wasle E (2008), Global Navigation Satellite Systems, SpringerWienNewYork. Huber K, Heuberger F, Abart C, Karabatic A, Weber R, Berglez S (2010), PPP: Precise Point Positioning ‐ Constraints and Opportunities, FIG Congress 2010: Facing the Challenges ‐ Building the Capacity, Sydney, Australia. Hughes L (2013), India's Slow Race to Military Space, FutureDirections International, viewed 5 July 2013, .

Huisman L, Teunissen P, Hu C (2012), GNSS Precise Point Positioning in Regional Reference Frames using Real‐Time Broadcast Corrections, Journal of Applied Geodesy, 6 pp.15‐23.

IAG (2013), International Association of Geodesy (IAG), IAG, viewed 28 January 2014, .

ICAO (2008), Aeronautical Telecommunications, Annex 10 to the Convention on International Civil Aviation, International Standards and Recomended Practices, Radio Navigation Aids, International Civil Aviation Authority (ICAO), 1.

ICSM (2007), Standards and Practices for Control Surveys (SP1), Intergovernmental Committee on Surveying and Mapping (ICSM), 1.7.

ICSM (2013), Standard for the Australian Survey Control Network Special Publication (SP1), Intergovernmental Committee on Surveying and Mapping (ICSM) Permanent Committee on Geodesy (PCG), 2.0.

IERS (2014), International Earth Rotation and Reference Systems Service (IERS), IERS, viewed 28 January 2014, . IGEB (2003), Interagency GPS Executive Board (IGEB) ‐ U.S. Policy Statement Regarding Civil GPS Availability, viewed 16 April 2013, . IGS (2013a), IGS Products, International GNSS Service (IGS), viewed 14 January 2014, . IGS (2013b), International GNSS Service (IGS) Site Guidelines, Infrastructure Committee ‐ IGS Central Bureau, Pasadena, CA. IGS (2013c), International GNSS Service Strategic Plan 2013‐2016, Jet Propulsion Laboratory, California Institue of Technology, Pasadena, CA. IGS (2013d), Why is IGS involved in Real‐Time GNSS?, International GNSS Service (IGS), viewed 2 December 2013, .

256

IGS, RTCM 2013. The Receiver Independent Exchange Format Version 3.02. International GNSS Service (IGS), RINEX Working Group and Radio Technical Commission for Maritime Services Special Committee 104 (RTCM‐SC104). Inmarsat (2013), inmarsat ‐ The Mobile Satellite Company, inmarsat, viewed 6 October 2013, . Inside GNSS (2011), GNSS Receiver Clocks, Gibbons Media and Research, LLC, viewed 14 January 2014, . Inside GNSS (2013a), ESA Adds System Time Offset to Galileo Navigation Message, Gibbons Media and Research, LLC, viewed 14 January 2014, . Inside GNSS (2013b), India Successfully Launches IRNSS‐1A, Gibbons Media and Research, LLC, viewed 8 January 2014, . Inside GNSS (2013c), New Foundation Formed to Pursue eLoran as Backup for GPS, Gibbons Media and Research, LLC, viewed 14 January 2014, . Inside GNSS (2013d), North Korea's GPS Jamming Prompts South Korea to Endorse Nationawide eLoran System, Gibbons Media and Research, LLC, viewed 14 January 2014, . IWG (2012), SBAS International Working Group (IWG) ‐ Global SBAS Status, viewed 9 July 2013, .

Jamtnas L, Sunna J, Emardson R, Jonsson B (2010), Quality Assessment of Network‐RTK in the SWEPOS Network of Permanent GNSS Reference Stations, FIG Congress 2010, Sydney, Australia.

Janssen V (2009), A comparison of the VRS and MAC principles for network RTK, International Global Navigation Satellite System Society, Holiday Inn Surfers Paradise, QLD, Australia. Janssen V, White A, Yan T (2010), CORSnet‐NSW: Towards State‐wide CORS Infrastructure for New South Wales, Australia, FIG Congress 2010, Sydney, Australia.

Japan Civil Aviation Bureau (2009), Overview of MSAS, United Nations for Outer Space Affairs (UNOOSA), viewed 10 January 2014, . Johnston G, Morgan L (2010), The Status of the National Geospatial Reference System and its Contribution to Global Geodetic Initiatives, FIG Congress 2010, Sydney, Australia.

Jones R, Mendelson H (2011), Information goods vs. industrial goods: Cost structure and competition, Management Science, 57 (1): pp.164‐176. Klobuchar J (1987), Ionospheric Time‐Delay Algorithms for Single‐Frequency GPS Users, IEEE Transactions on Aerospace and Electronic Systems, 3 pp.325‐331. Klobuchar J (1996), Ionospheric effects on GPS, 1, Washington, American Institute of Aeronautics and Astronautics, Inc. Kouba J (2009), A Guide To Using International GNSS Services (IGS) Products, viewed 12 August 2013, . Kouba J, Heroux P (2001), GPS Precise Point Positioning Using IGS Orbit Products, GPS Solutions, 5 (2): pp.12‐28.

Krugman P, Wells R (2010), Technology, Information Goods and Network Externalities, Worth Publishers, viewed 28 October 2013,

257

. Landau H, Brandl M, Chen X, Drescher R, Glocker M, Nardo A, Nitschke M, Salazar D, Weinbach U, Zhang F (2013), Towards the Inclusion of Galileo and BeiDou/Compass Satellites in Trimble CenterPoint RTX, Institute of Navigation GNSS+, Nashville Convention Center, Nashville Tennessee. Landau H, Vollath U, Chen X (2002), Virtual Reference Station Systems, Journal of Global Positioning Systems, 1 (2): pp.137‐143. Lateral Economics (2009), Nation Building for the Information Age: the economic case for governments leading the development of a national high accuracy positioning network. Leica Geosystems (2011), Leica GNSS Spider, viewed 29 July 2011, . Locata Corporation (2013), Locata Technology, Locata Corporation Pty Ltd, viewed 26 August 2013, . LPI (2011), Guidelines for CORSnet‐NSW Continuously Operating Reference Stations, Land and Property Information (LPI) ‐ Division of the Department of Finance and Services, Sydney, NSW. LPI (2013), CORSnet‐NSW Network Information, NSW Government Land and Property Information (LPI), viewed 30 September 2013, .

Lyskov D (2013), GLONASS Policy, Status and Evolution, United Nations Offoice for Outer Space Affairs (UNOOSA), viewed 8 January 2014, . Mankiw G (2007), Principles of Microeconomics, 1, Cengage Learning.

McPhee J (2009), The Benefits of Controlled Traffic Farming to assist adaptation and climate change for Australian crop production industries ‐ submission on behalf of the Tasmanian Institute of Agricultural Research, Submission to House Standing Committee on Primary Industries and Resources.

Montenbruck O, Hauschild A, Steigenberger P, Hugentobler U, Teunissen P, Nakamura S (2012), Initial assessment of the COMPASS/BeiDou‐2 regional navigation satellite system, GPS Solutions, pp.1‐12.

Murfin T (2013), Look, No Base‐Station! ‐ Precise Point Positioning (PPP), GPS World.

National Academy of Sciences (2012), Global Navigation Satellite Systems: Report of a Workshop of the National Academy of Engineering and the Chinese Academy of Engineering, Washington, DC, The National Academies Press. Navcom (2014), StarFire Frequently Asked Questions, Navcom, viewed 3 February 2014, . NBN Co (2011), Product and Pricing Overview for Service Providers, NBN Co Wholesale Access Service, NBN Co Limited. NBN Co (2012), Corporate Plan 2012 ‐ 2015, NBNCo Limited. NGS (2013a), Geodesy ‐ CORS, US National Geodetic Survey (NGS), viewed 6 October 2013, . NGS (2013b), Guidelines for New and Existing Continuously Operating Reference Stations (CORS), National Ocean Survey, NOAA, Silver Spring, MD.

258

Niell A (1996), Global mapping functions for atmosphere delay at radio wavelengths, Journal of Geophysical Research, 101 pp.3227‐3246. NIMA (2002), The American Practical Navigator Bicentennial Edition, National Imagery and Mapping Agency (NIMA), 9 Bethesda, Maryland. NOAA (2014), Medium Earth Orbit Search and Rescue (MEOSAR) System, National Oceanic and Atmospheric Administration (NOAA), viewed 9 January 2014, . OECD (2006), Cost‐Benefit Analysis and the Environment, Washington, DC, Organisation for Economic Co‐operation and Development (OECD). OmniSTAR (2013), OmniSTAR, Trimble Navigation Limited, viewed 6 October 2013, . Optus (2013), Optus Wholesale, viewed 6 October 2013, . Ordnance Survey (2012), Ordnance Survey Geodesy and Positioning ‐ The View to 2012, Ordnance Survey, Southampton, United Kingdom. Ordnance Survey (2013), OS Net, Ordnance Survey, viewed 1 May 2013, .

Oxford Dictionaries (2013), Definition of infrastructure in English, viewed 22 August 2013, . People's Republic of China (2011), China Space Activities in 2011, Information Office of the State Council.

Pierce JA, Palmer W, Watt AD, Woodward RH (1966), Omega ‐ A World‐wide Navigational System: System Specification and Implementation, Omega Implementation Committee for the U. S. Navy Department Bureau of Ships (submitted through the Office of Naval Research). Position One Consulting (2008), User Needs Analysis, Project 1.04 ‐ Prepared for the Cooperative Research Centre for Spatial Information.

Position Partners (2011), AllDayRTK, viewed 23 November 2011, . Position Partners (2013), AllDayRTK, viewed 23 September 2013, . PwC (2010a), Stage 1 Report: Prciniples, Issues and Alternative Models, ANZLIC ‐ The Spatial Information Council Economic Assessment of Spatial Data Pricing and Access PriceWaterhouseCoopers (PwC). PwC (2010b), Stage 2 Report: Cost Benefit Analysis of Alternative Models, ANZLIC ‐ The Spatial Information Council Economic Assessment of Spatial Data Pricing and Access PriceWaterhouseCoopers (PwC). RAND Corporation (1995), The Global Positioning System ‐ Assessing National Policies, Critical Technologies Institute. Randall A (1983), The Problem of Market Failure, Natural Resources Journal, 23. Rao V, Lachapelle G (2013), Combining GAGAN with IRNSS, Coordinates, April 2013 Centre for Geo‐ Information Technologies (cGIT), Delhi, India. Rao V, Lachapelle G, Kumar V (2011), Analysis of IRNSS Over Indian Subcontinent, International Technical Meeting of the Institution of Navigation, Catamaran Resort Hotel, San Diego.

259

Rizos C (2007), Alternatives to current GPS‐RTK service and some implications for CORS infrastructure and operations, GPS Solutions, 11 (3): pp.151 ‐ 158. Rizos C (2008), Multi‐Constellation GNSS/RNSS from the Perspective of High Accuracy users in Australia, Journal of Spatial Science, 53 (2): pp.29‐63. Rizos C, Han S (2003), Reference Station Network Based RTK Systems ‐ Concepts and Progress, Wuhan University Journal of Natural Sciences, 8 (2): pp.566‐574. Rizos C, Janssen V, Roberts C, Grinter T (2012), Precise Point Positioning: Is the Era of Differential GNSS Positioning Drawing to an End?, FIG Working Week 2012, Rome, Italy. Rizos C, Roberts C, Barnes J, Gambale N (2010), Locata: A new high accuracy indoor positioning system, International Conference on Indoor Positioning and Infoor Navigation (IPIN), Zurich, Switzerland. Rogers E (2003), Diffusion of Innovations, New York, Free Press. Rose M (2002), Shedding Light on Market Power, Library of Economics and Liberty, viewed 27 November 2013, . RTCA (2013), Minimum Operational Performance Standards for Global Positioning System/Space‐Based Augmentation System Airborne Equipment Radio Technical Commission for Aeronautics (RTCA).

RTCM 2006. RTCM Standard 10403.1 For Differential GNSS Services Version 3. Radio Technical Commission for Maritime Services (RTCM) Special Committee 104.

RTKnetwest (2013), Precise Mobile Satellite Positioning, RTKnetwest, viewed 4 October 2013, . Rubinov E (2013), Stochastic Modelling for Real‐Time GNSS Positioning, Doctor of Philosophy, Department of Infrastructure Engineering, The University of Melbourne, Melbourne.

Rubinov E, Collier P, Fuller S, Seager J (2011a), Review of GNSS Formats for Real‐Time Positioning, AfricaGEO, Cape Town International Convention Centre.

Rubinov E, Hausler G, Collier P, Poyner J, Docherty G, Millner J, Elliot D (2011b), Evaluation of NRTK Heighting in Victoria: Impact of a Temporary Reference Station, International Global Navigation Satellite Systems Society 2011, University of New South Wales, Sydney, NSW.

Saastamoinen J (1973), Contributions to the theory of atmospheric refraction, Bulletin Géodésique, 107 (1): pp.13‐34.

Sagiya T (2004), A decade of GEONET: 1994‐2003‐The continuous GPS observation in Japan and its impact on earthquake studies, Earth Planets and Space, 56 (8): pp.xxix‐xlii. Sayeenathan S (2013), IRNSS & GAGAN, United Nations Office for Outer Space Affairs (UNOOSA), viewed 10 January 2014, . Shapiro C, Varian HR (1999), Information rules: a strategic guide to the network economy, Harvard Business Press. SmartNet Aus (2012), RTK Networks ‐ Different Methods, viewed 12 February 2014, . SmartNet Aus (2013), Join the Network, SmartNet Aus, viewed 7 October 2013, . Space Foundation (2012), The Space Report 2012 ‐ The Authoritative Guide to Global Space Activity, Space Foundation,.

260

SPU (2013), Australia's Satellite Utilisation Policy, Space Policy Unit (SPU), Australian Government, viewed 8 July 2013, . Standing Council of Transport and Infrastructure (2012), Policy Framework for Intelligent Transport Systems, Department of Infrastructure and Regional Development, Canberra, ACT. Steed JB, Luton G (2000), WGS84 and the Geocentric Datum of Australia, 13th International Technical Meeting of the Satellite Division of the Institute Of Navigation GPS, Salt Lake City, Utah, pp.432‐437. Stupak G (2012), SDCM status and plans, United Nations for Outer Space Affairs (UNOOSA), viewed 10 January 2014, . Sudhir C (2013), Indian SBAS System ‐ GAGAN, viewed 10 January 2014, . Telstra Wholesale (2013), Telstra Wholesale, Telstra, viewed 6 October 2013, . The Allen Consulting Group (2008), Economic benefits of high resolution positioning services, Prepared for Victorian Department of Sustainability and Environment and the Cooperative Research Centre for Spatial Information. The Royal Academy of Engineering (2011), Global Navigation Space Systems: reliance and vulnerabilities, The Royal Academy of Engineering, London.

Topcon (2013), Products and Applications, Topcon Positioning Systems Inc., viewed 4 October 2013, . Trimble (2013a), Positioning Services ‐ Trimble VRS Now, Trimble Navigation Ltd., viewed 28 January 2014, . Trimble (2013b), Trimble VRS3NET App, Trimble Navigation Limited, viewed 7 October 2013, . Ultimate Positioning (2013), Infrastructure, viewed 4 October 2013, . UNAVCO (2011), Instrumentation, UNAVCO Inc, viewed 14 January 2013, . United Nations (2004), Report of the Action Team on Global Navigation Satellite Systems (GNSS), Follow‐ up to the Third United Nations Conference on the Exploration and Peaceful Uses of Outer Space (Unispace III). United Nations (2010), Current and Planned Global and Regional Navigation Satellite Systems and Satellite‐based Augmentations Systems, International Committee on Global Navigation Satellite Systems pp.70. UNOOSA (2013), GLONASS Government Policy, Status and Modernisation, Unitated Nations Office for Outer Space Affairs (UNOOSA), Scientific and Technical Subcommittee of COPUOS, viewed 8 January 2014, . UNOOSA (2014), International Committee on GNSS (ICG), United Nations Office for Oute Space Affairs, viewed 8 January 2014, . Urlichich Y, Subbotin V, Stupak G, Dvorkin V, Povalyaev A, Karutin S (2011), Innovation: GLONASS: Developming Strategies for the Future, GPS World, 22 (4): gpsworld.com.

261

US Air Force (2011), 50 SW Completes GPS Constellation Expansion, viewed 15 April 2013, . US Department of Commerce (1998), GPS ‐ Market Projectinos and Trends in the Newest Global Information Utility, The International Trade Administration, Office of Telecommunications. US Government (2004), U.S. Space‐Based Position, Navigation and Timing Policy. US Government 2010. National Space Policy of the United States of America. In: Pnt UNECFS‐B (ed.). Virgin Mobile (2013), Network Coverage, Virgin Mobile, viewed 6 October 2013, . Vollath U, Buecherl A, Landau H, Pagels C, Wagner B (2000a), Long‐Range RTK Positioning Using Virtual Reference Stations, 15th International Technical Meeting of the Satellite Division of the Institute of Navigation, Salt Lake City, Utah, USA, pp.1143‐1147. Vollath U, Buecherl A, Landau H, Pagels C, Wagner B (2000b), Multi‐Base RTK Positioning Using Virtual Reference Stations, 13th International Technical Meeting of the Satellite Division of the Institute of Navigation, Salt Lake City, Utah, USA, pp.123‐131. VSC (2010a), Cutodianship Program, Victorian Spatial Council, viewed 9 October 2013, . VSC (2010b), Data Distribution Channels and Agreements, Victorian Spatial Council, viewed 7 October 2013, .

Wang C, Feng Y, Higgins M, Cowie B (2010), Assessment of Commercial Network RTK User Positioning Performance over Long Inter‐Station Distances, Journal of Global Positioning Systems, 9 (1): pp.78‐ 89.

Wubbena G, Bagge A, Schmitz M (2001), Network−Based Techniques for RTK Applications, GPS JIN, GPS Society, Japan Institute of Navigation, Tokyo, Japan. Wübbena G, Schmitz M, Bagge A (2005), PPP‐RTK: precise point positioning using state‐space representation in RTK networks, International Technical Meeting, ION GNSS, Long Beach, California.

Wustenhoff E 2002a. Service Level Agreement in the Data Center. Santa Clara, CA: Sun Microsystems.

Wustenhoff E 2002b. Service Level Management in the Data Center. Santa Clara, CA: Sun Microsystems. Yan T (2006), GNSS Data Protocols: Choice and Implementation, International Global Navigation Satellite Systems Society, Holiday Inn Surfers Paradise, Australia, 8. Yang J, Varshavsky A, Liu H, Chen Y, Gruteser M (2010), Accuracy characterization of Cell Tower Localization, Proceedings of the 12th Association for Computing Machinery (ACM) international conference on Ubiquitous computing, Copenhagen, Denmark, ACM, pp.223‐226. Yun H, Han D, Kee C (2013), Preliminary Test Results of Pseudolite‐Based Augmentation System (PBAS), Proceedings of the ION Pacific PNT Meeting, Honolulu, Hawaii, pp.pp. 631‐635. Zhang K, Wu F, Wu S, Rizos C, Lim S, Roberts C, Ge L, Kealy A (2007), The Latest Development of a State‐ wide GNSS Network‐based RTK System in Australia, 20th International Technical Meeting of the Satellite Division of the Institute of Navigation ION GNSS 2007, Fort Worth Convention Center, Fort Worth, Texas, 699‐707.

262

APPENDIX A – GEODETIC DATUMS & COORDINATE SYSTEMS

Every point on the Earth and in space has a unique position, which can be described using a coordinate system. Geodetic datums define the spatial relationship between coordinate systems and the Earth. Sections 2.3.2 and 3.5 identified why geodetic datums are needed to reference the absolute position of objects using satellite‐based positioning systems. Geodetic principles for defining and realising a datum are introduced below.

Datum Definition and the Reference Ellipsoid:

The Earth’s surface is a near spherical shape but has a slightly larger radius at the equator than at the poles, which creates an ellipsoidal shape. A three‐dimensional biaxial ellipsoid (generated by rotating an ellipse about its shorter semi‐minor axis shown in Figure 73) can therefore be used to approximate the size and shape of the Earth, or a region of the Earth. By defining the ellipsoid’s geometric size and shape, any other ellipsoidal constant can be computed, including the coordinates of a point located within or above its surface, such as a satellite. The reference ellipsoid is however meaningless unless its origin and orientation have been defined relative to the Earth’s centre of mass or a region of the Earth’s surface.

FIGURE 73: ELLIPSOID

The semi‐minor axis of an ellipsoid is shorter (flatter) than the semi‐major axis.

Datum definition therefore establishes a Terrestrial Reference System (TRS) that specifies the size, shape, origin and orientation of the reference ellipsoid. Many datums have been defined because there are many ways to fit an ellipsoid to the surface of the Earth.

Traditionally, reference ellipsoids are computed as a best‐fit surface over a particular region, such as a country or continent, however modern positioning systems such as GPS require reference ellipsoids that best‐fit the earth as a whole to create a global coordinate system. GPS uses the World Geodetic System

263

1984 (WGS84) datum, which has its origin aligned with the Earth’s centre of mass (CoM). Ellipsoids with an origin defined at the CoM are termed geocentric. GPS satellites also orbit the Earth’s CoM which is why geocentric datums provide a global reference system for deriving coordinates from satellite positioning systems.

The Geodetic Reference System 1980 (GRS80) ellipsoid is a best‐fit approximation of the Earth’s size and shape, and underpins many global datums including the International Terrestrial Reference System (ITRS). The conventions, algorithms and constants defined within the ITRS are a global benchmark for scientific applications. Its orientation is fixed in the x‐axis along the zero meridian in Greenwich, London. Its z‐axis is aligned parallel to the Conventional Terrestrial Pole (CTP) defined by the International Earth Rotation Service (IERS), and its y‐axis is positioned 90 degrees to the x‐axis in a right‐handed, Earth‐ Centred Earth‐Fixed (ECEF) orthogonal coordinate system.

Different coordinate systems can be used to represent the position of points in a TRS.

Coordinate Systems:

Three types of coordinate systems are commonly used to record the position of geographic features in a TRS:

1. Cartesian (geocentric) coordinates – derived from a three‐dimensional system whose origin coincides with the centre of the reference ellipsoid. Coordinates are expressed in X, Y, Z and are based purely on distance.

2. Geographic (geodetic or ellipsoidal) coordinates – referenced to the surface of the ellipsoid and expressed in latitude and longitude. Latitude is the angle between the ellipsoid normal and the equatorial plane. Longitude is the angle from the zero meridian (Greenwich in a geocentric ellipsoid; parallel to the Greenwich meridian otherwise) from the ellipsoid’s centre to a point on the ellipsoid’s surface.

3. Projected (map‐grid) coordinates – a mathematical projection of geographic coordinates onto a two‐dimensional surface. The standard Universal Transverse Mercator (UTM) projection is divided into zones across the Earth, and the origin of each zone is the point of intersection with the equator and the meridian central to the zone. UTM is a conformal projection meaning it preserves geometric shapes (angles), but distorts geometric directions (azimuth), distances and areas. Projected coordinates must therefore be scaled to determine their true three‐ dimensional geometry.

264

Datum Realisation:

Datum realisation identifies the coordinates of physical points on the Earth or in space in the chosen TRS. Datum realisation creates a Terrestrial Reference Frame (TRF) by measuring the location of physical reference points across the Earth relative to the reference ellipsoid. For example, coordinates obtained using a GPS device are triangulated from measurements to satellites whose coordinates are known (realised) relative to the Earth’s CoM using the WGS84 ellipsoid. Radio and optical measurements between points on the Earth’s surface and points in space are typically used to realise a datum.

Terrestrial control surveys undertaken using optical and GPS radio observation techniques are commonly used to propagate datums on a regional scale. Given the Earth’s shape is constantly changing, the position of certain points in global and regional TRFs will change over time. Periodic measurement of the TRF is therefore needed to monitor changes in the geodetic datum to produce new realisations. Each realisation of ITRF for example is referenced to an epoch in time, the latest of which is ITRF2008 (preparation of ITRF 2013 is underway). Changes in coordinates are detected because they are measured relative to the TRS which is defined using the same constants in each realisation. Depending on the adopted measurement techniques, different realisations can also produce new coordinates for points regardless of any physical movement of the point. For example, using modern GNSS technology to measure precise baselines over hundreds of kilometres can be more accurate than traditional optical measurements that were used in the original datum realisation.

Australia uses the Geocentric Datum of Australia (GDA94) as a reference for all spatial data. GDA94 is a static datum locked to the realisation of ITRF92 at epoch 1994.00. GDA94 was realised using a combination of space and terrestrial measurement techniques. Whilst ITRF and GDA are defined using the same TRS, new coordinates are realised periodically for ITRF to constantly measure tectonic and intra‐plate motion. ITRF2008 therefore contains different coordinates for the same points that were realised using GDA94 (see Section 3.5.2.4)

To summarise, global and regional TRFs provide access to a TRS by determining the coordinates of physical points on the Earth or in space relative to the origin, orientation, size and shape of a reference ellipsoid.

Geoid:

The Earth’s surface is an irregular shape characterised by mountains, valleys, plains and deep ocean trenches. Height measurements above or below an ellipsoid do not reflect the true height properties of the physical world given the ellipsoid is only a mathematical approximation of the true Earth surface. Height measurements must be referenced to a level surface instead.

Conceptually, a level surface is one that is at right angles to the direction of gravity at every location across the Earth’s surface. A non‐level surface creates the feeling of travelling ‘uphill’ or ‘downhill’

265 relative to the direction of Earth’s gravitational force. The strength of gravity varies across the Earth’s surface due to its non‐uniform distribution of mass, which is why the ellipsoid is only an approximation to a truly level surface. For example, mountainous regions with large mass have a stronger gravitational attraction than neighbouring flatlands. A perfectly spherical earth would have equal gravity potential at every point on or above the Earth’s surface, meaning an equipotential (level) surface is where the gravity potential between any two points is the same. Gravity potential is measured using precise ground and space‐based observations (locally and globally) to model an equipotential surface of the Earth known as the geoid: a conceptual surface that is irregular in shape but level in terms of fluid‐flow.

FIGURE 74: REFERENCE ELLIPSOID & GEOID

The geoid is a surface of equal gravity potential which is approximated by mean sea level in Australia. The reference ellipsoid is a mathematical surface that approximates the size and shape of the Earth, or a portion of the Earth’s surface. Image from Floyd (1978).

Theoretically, there are infinite equipotential surfaces above the Earth because gravity potential changes at different elevations. A ‘zero height’ level surface must therefore be chosen for referencing all other heights to enable accurate mapping of real‐world processes such as the direction of water flow. Mean Sea Level (MSL) is the zero height surface used to reference heights above and below the Earth’s surface. Hence, the geoid approximates the average shape (height) that the oceans would take under the influence of gravity alone. Reference ellipsoids such as GRS80 can vary by over 200 m from the geoid.

266

APPENDIX B – MEASUREMENT CRITERIA FOR NRTK COVERAGE IN AUSTRALIA

All area and distance measurements have been computed in ArcMAP Version 9.3 using the following criteria:

• Areas are quoted in square kilometres (sq km) using an Albers Equal Area Conic map projection (Table 24) to preserve the size of geographic shapes over the Australian land‐mass (ICSM, 2012).

TABLE 24: ALBERS EQUAL AREA CONIC MAP PROJECTION PARAMETERS

Albers Equal Area Conic Map Projection: Australia False Easting: 0.00 m False Northing: 0.00 m Central Meridian: 132.00° Standard Parallel 1: ‐18.00° Standard Parallel 2: ‐36.00° latitude of Origin: 0.00° Linear Unit: Metres

Map projection parameters used for NRTK area calculations.

• All areas are referenced to Geoscience Australia’s GEODATA TOPO 5M 2004 dataset; a vector representation of the Australian landscape with 5 metre (m) resolution. Table 25 compares Geoscience Australia’s published areas with those computed using the Albers map projection for the 5m Geodata. All areas calculated in this study are computed relative to the ArcMAP areas listed in Table 25 to maintain consistency. Small discrepancies may result compared with published values from service providers. Ellipsoidal distances are quoted in kilometres (km) and are referenced to the Geocentric Datum of Australia 1994 (GDA 1994), which is Australia’s current national datum.

TABLE 25: PUBLISHED AND COMPUTED AREA COMPARISON

Mainland ArcMAP 5m ArcMAP minus % National State/Territory Australia Geodata Mainland Coverage (sq km) (sq km) (sq km) Australian Capital Territory 0.03 2358 2357 ‐1 Tasmania 0.9 64519 64286 ‐233 Victoria 3 227010 227158 148 New South Wales 10.4 800628 800735 107 South Australia 12.7 978810 979470 660 Northern Territory 17.5 1335742 1334233 ‐1509 Queensland 22.5 1723936 1723321 ‐615 Western Australia 33 2526786 2523986 ‐2800 Jervis Bay Territory < 1 72 66 ‐6 AUSTRALIA — 7659861 8458704 798843

Comparison of Geoscience Australia (2010) published areas with those computed using 5m Geodata and an Albers Equal Area map projection in ArcMap.

267

268

APPENDIX C – GLOBAL & REGIONAL CORS NETWORKS

CORS infrastructure within the networks below is primarily funded by government to support geodetic activities, and commercial positioning services have been developed by licensing data from some of these networks.

TABLE 26: GLOBAL & REGIONAL CORS

Global IGS Tracking Network http://igscb.jpl.nasa.gov/network US National CORS Network http://www.ngs.noaa.gov/CORS/ North Plate Boundary Observatory http://pbo.unavco.org/ America Canadian Spatial Reference http://webapp.geod.nrcan.gc.ca/geod/ System http://www.ordnancesurvey.co.uk/business‐and‐ OSNET United Kingdom government/products/os‐net/index.html SAPOS Germany http://www.sapos.de/ SWEPOS Sweden http://swepos.lmv.lm.se/ Geodetic Data Archiving Facility http://geodaf.mt.asi.it/gps_page.html Reseau GPS Permanent http://rgp.ign.fr/ http://www.swisstopo.admin.ch/internet/swisstopo/en/home/ SWIPOS Switzerland products/services/swipos.html Europe GNSS Service Centre Hungary http://www.gnssnet.hu/ LATPOS Latvia http://www.latpos.lgia.gov.lv ROMPOS Romania http://www.rompos.ro AGROS Serbia http://www.agros.rgz.gov.rs SIGNAL ‐ Serbia http://www.gu‐signal.si TUSAGA‐Aktif Turkey http://tkgm.gov.tr/node/2231 EUREF Permanent Network http://www.epncb.oma.be/_networkdata/ European Point Determination http://www.eupos.org/ System NIGNET Nigeria http://www.nignet.net/ Africa South Africa http://www.trignet.co.za/ SIRENT Singapore http://www.sirent.inlis.gov.sg/ Asia GSI Japan http://www.gsi.go.jp/ENGLISH/page_e30030.html http://www.ga.gov.au/earth‐monitoring/geodesy/gnss‐ Australia ARGN & AuScope networks/station‐list‐and‐coordinates.html New Position New Zealand http://apps.linz.govt.nz/positionz/ Zealand

269

Minerva Access is the Institutional Repository of The University of Melbourne

Author/s: HAUSLER, GRANT

Title: National positioning infrastructure: technical, institutional and economic criteria for coordinating access to Australia's GNSS CORS infrastructure

Date: 2014

Persistent Link: http://hdl.handle.net/11343/40853

File Description: National positioning infrastructure: technical, institutional and economic criteria for coordinating access to Australia's GNSS CORS infrastructure