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Development of an Extension of Geoserver for Handling 3D Spatial Data Hyung-Gyu Ryoo Pusan National University
Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings Volume 17 Boston, USA Article 6 2017 Development of an extension of GeoServer for handling 3D spatial data Hyung-Gyu Ryoo Pusan National University Soojin Kim Pusan National University Joon-Seok Kim Pusan National University Ki-Joune Li Pusan National University Follow this and additional works at: https://scholarworks.umass.edu/foss4g Part of the Databases and Information Systems Commons Recommended Citation Ryoo, Hyung-Gyu; Kim, Soojin; Kim, Joon-Seok; and Li, Ki-Joune (2017) "Development of an extension of GeoServer for handling 3D spatial data," Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings: Vol. 17 , Article 6. DOI: https://doi.org/10.7275/R5ZK5DV5 Available at: https://scholarworks.umass.edu/foss4g/vol17/iss1/6 This Paper is brought to you for free and open access by ScholarWorks@UMass Amherst. It has been accepted for inclusion in Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings by an authorized editor of ScholarWorks@UMass Amherst. For more information, please contact [email protected]. Development of an extension of GeoServer for handling 3D spatial data Optional Cover Page Acknowledgements This research was supported by a grant (14NSIP-B080144-01) from National Land Space Information Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government and BK21PLUS, Creative Human Resource Development Program for IT Convergence. This paper is available in Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings: https://scholarworks.umass.edu/foss4g/vol17/iss1/6 Development of an extension of GeoServer for handling 3D spatial data Hyung-Gyu Ryooa,∗, Soojin Kima, Joon-Seok Kima, Ki-Joune Lia aDepartment of Computer Science and Engineering, Pusan National University Abstract: Recently, several open source software tools such as CesiumJS and iTowns have been developed for dealing with 3-dimensional spatial data. -
Relative Curve Orientation in the Alignment of Inconsistent Linear Datasets
Relative Curve Orientation in the Alignment of Inconsistent Linear Datasets David N. Siriba, Daniel Eggert, Monika Sester Institute of Cartography and Geoinformatics (IKG), Leibniz University of Hannover, Germany Appelstraße 9a, 30167 Hannover, Germany. E-mail: {david.siriba, daniel.eggert, monika.sester}@ikg.uni-hannover.de ABSTRACT An approach for the alignment of a linear dataset of inconsistent positional accuracy with a more accurate one is presented. The approach consists of two main steps: path-matching and alignment based on relative curve orientations of the corresponding feature followed by a non-rigid transformation based on Thin plate Splines (TPS). The results obtained with this approach on two experimental cases show significant improvement in alignment and geometric accuracy of the lower accuracy datasets. 1. INTRODUCTION Geometric alignment of spatial features is one of the typical problems of data integration and usually carried out so that spatial features from two datasets that describe the same object coincide. It is achieved through point-based transformation that utilizes corresponding point features, which represent either some identified point landmarks or nodes mainly in a road network. Point-based transformation is adequate only for simple cases where positional discrepancies between the datasets are low and almost evenly distributed. In case the discrepancies are high and unevenly distributed, point-based approaches are not sufficient for aligning linear and polygonal features as they only guarantee that the control points will coincide. This problem is often encountered when integrating legacy datasets that contain large positional distortions with more geometrically accurate and newer datasets. Therefore corresponding linear features could be used to determine a more suitable geometric transformation between the datasets, in addition to point features. -
The State of Open Source GIS
The State of Open Source GIS Prepared By: Paul Ramsey, Director Refractions Research Inc. Suite 300 – 1207 Douglas Street Victoria, BC, V8W-2E7 [email protected] Phone: (250) 383-3022 Fax: (250) 383-2140 Last Revised: September 15, 2007 TABLE OF CONTENTS 1 SUMMARY ...................................................................................................4 1.1 OPEN SOURCE ........................................................................................... 4 1.2 OPEN SOURCE GIS.................................................................................... 6 2 IMPLEMENTATION LANGUAGES ........................................................7 2.1 SURVEY OF ‘C’ PROJECTS ......................................................................... 8 2.1.1 Shared Libraries ............................................................................... 9 2.1.1.1 GDAL/OGR ...................................................................................9 2.1.1.2 Proj4 .............................................................................................11 2.1.1.3 GEOS ...........................................................................................13 2.1.1.4 Mapnik .........................................................................................14 2.1.1.5 FDO..............................................................................................15 2.1.2 Applications .................................................................................... 16 2.1.2.1 MapGuide Open Source...............................................................16 -
Gvsos: a New Client for Ogc® Sos Interface Standard
GVSOS: A NEW CLIENT FOR OGC® SOS INTERFACE STANDARD Alain Tamayo Fong i GVSOS: A NEW CLIENT FOR OGC® SOS INTERFACE STANDARD Dissertation supervised by PhD Joaquín Huerta PhD Fernando Bacao Laura Díaz March, 2009 ii ACKNOWLEDGEMENTS I would like to thank to professors Joaquin Huerta and Michael Gould for their support during every step of the Master Degree Program. I would also like to thanks the Erasmus Mundus Scholarship program for giving me the chance to be part of this wonderful experience. Last, to all my colleagues and friends, thank you for making this time together so pleasant. iii GVSOS: A NEW CLIENT FOR OGC® SOS INTERFACE STANDARD ABSTRACT The popularity of sensor networks has increased very fast recently. A major problem with these networks is achieving interoperability between different networks which are potentially built using different platforms. OGC’s specifications allow clients to access geospatial data without knowing the details about how this data is gathered or stored. Currently OGC is working on an initiative called Sensor Web Enablement (SWE), for specifying interoperability interfaces and metadata encodings that enable real‐time integration of heterogeneous sensor webs into the information infrastructure. In this work we present the implementation of gvSOS, a new module for the GIS gvSIG to connect to Sensor Observation Services (SOS). The SOS client module allows gvSIG users to interact with SOS servers, displaying the information gathered by sensors in a layer composed by features. We present the detailed software engineering development process followed to build the module. For each step of the process we specify the main obstacles found during the development such as, restrictions of the gvSIG architecture, inaccuracies in the OGC’s specifications, and a set of common problems found in current SOS servers implementations available on the Internet. -
Centre for Geo-Information Thesis Report GIRS-2018-06 Managing Big Geospatial Data with Apache Spark Msc Thesis Hector Muro Maur
Centre for Geo-Information Thesis Report GIRS-2018-06 Managing Big Geospatial Data with Apache Spark MSc Thesis Hector Muro Mauri March 2018 Managing Big Geospatial Data with Apache Spark MSc Thesis Hector Muro Mauri Registration number 920908592110 Supervisors: Dr Arend Ligtenberg Dr Ioannis Athanasiadis A thesis submitted in partial fulfillment of the degree of Master of Science at Wageningen University and Research Centre, The Netherlands. March 2018 Wageningen, The Netherlands Thesis code number: GRS80436 Thesis Report: GIRS 2018 06 Wageningen University and Research Centre Laboratory of Geo-Information Science and Remote Sensing Contents 1 Introduction 3 1.1 Introduction & Context.........................................3 1.2 Problem definition & Research questions................................5 1.3 Structure of the document........................................5 2 Methods & Tools 6 2.1 Methods..................................................6 2.2 Tools....................................................7 3 Tests Design & Definition 9 3.1 Functionality Test............................................9 3.2 Performance Benchmark Test...................................... 17 3.3 Use Case................................................. 19 4 Functionality Test Results 21 4.1 Magellan.................................................. 21 4.2 GeoPySpark................................................ 25 4.3 GeoSpark................................................. 28 4.4 GeoMesa................................................. 31 5 Results -
Client-Side Versus Server-Side Geoprocessing
CLIENT-SIDE VERSUS SERVER-SIDE GEOPROCESSING Benchmarking the performance of web browsers processing geospatial data using common GIS operations. by Erin L. Hamilton A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science (Cartography and Geographic Information Systems) at the UNIVERSITY OF WISCONSIN–MADISON 2014 i Acknowledgements The completion of this thesis could not have been accomplished without the help and support of many people. Thank you to Jim Burt for serving as my advisor. Your ability to see the big picture and ask hard questions made my work infinitely stronger. Your feedback on my drafts pushed me to produce my best work and I am thankful for that. Thank you to Qunying Huang and David Hart for serving on my committee. Your feedback on this thesis was much appreciated. More importantly, the support you provided me in improving my programming skills over the past three years enabled me to execute the technical pieces of this research. I am extremely grateful for that. Thank you to the members of the GIS group. The questions asked during my research progress presentations over the last year were significant in shaping and refining my work. Big thank you to the people in the Cartography Laboratory. Your guidance, support, and friendship were critical in keeping me moving forward. I especially want to thank Tanya Buckingham and Daniel Huffman for providing me with so much insightful perspective and advice along the way and Bill Buckingham for providing tremendously helpful recommendations on my writing. Thank you to my Mom and Dad for being my cheer team across the country. -
Handling Data Consistency Through Spatial Data Integrity Rules in Constraint Decision Tables
Handling Data Consistency through Spatial Data Integrity Rules in Constraint Decision Tables Fei Wang Vollständiger Abdruck von der Fakultät für Bauingenieur- und Vermessungswesen der Universität der Bundeswehr München zur Erlangung des akademischen Grades eines Doktor- Ingenieurs (Dr.-Ing.) genehmigten Dissertation. Vorsitzender: Univ.-Prof. Dr.-Ing. Wilhelm Caspary 1.Berichterstatter: Univ.-Prof. Dr.-Ing. Wolfgang Reinhardt 2.Berichterstatter: Univ.-Prof. Dr.-Ing. Anders Östman Diese Dissertation wurde am 31. Jan. 2008 bei der Universität der Bundeswehr münchen eingereicht. Tag der Mündlichen Prüfung: 13. Mai 2008 2 3 Abstract With the rapid development of the GIS world, spatial data are being increasingly shared, transformed, used and re-used. The quality of spatial data is put in a high priority because spatial data of inadequate quality is of little value to the GIS community. Several main components of spatial data quality were indentified by international standardization bodies such as ISO/TC 211, OGC and FGDC, which consists of seven usual quality elements: lineage, positional accuracy, attribute accuracy, semantic accuracy, temporal accuracy, logical consistency and completeness (two different names for similar aspects of quality are grouped in the same category). In this dissertation our work focuses on the data consistency issue of the spatial data quality components, which involves the logical consistency as well as semantic and temporal aspects. Due to complex geographic data characteristics, various data capture workflows and different data sources, the final large datasets often result in inconsistency, incompleteness and inaccuracy. To reduce spatial data inconsistency and provide users the data of adequate quality, the specification of spatial data consistency requirements should be explicitly described. -
The Decision Table Template for Geospatial Business Rules
The Decision Table Template For Geospatial Business Rules Alex Karman CTO and Co-Founder Revolutionary Machines, Inc. www.rev-mac.com San Jose, Oct 13-15, 2014 1 OpenRules Now Supports Spatial Rules • Leverages the popular JTS Topology Suite (“JTS”) • Supports the Egenhofer Relationships (“DE9-IM”) for 2D points, polygons and line strings – Contains, touches, crosses, overlaps, disjoint, etc. • Supports distance and area calculations; and ranking by distance or area • Supports aggregates (max/min) of spatial rules • Supports non-spatial mereological rules – Part of/comprises • Loads Geographic Markup Language (GML) from text files with a GeometryDatabaseBuilder utility Motivation • Last year, we used OpenRules to handle business rules related to security constraints and service level agreements in a data center management project. • This year, the customer asked us if OpenRules could manage fraud detection and privacy rules in a healthcare project in the same data center. • We looked at the problem domain and saw a large number of spatial rules. Spatial Business Rules Are Everywhere • Healthcare – Hospital Referral Region, Hospital Service Area, Hospital, Patient, Emergency Routes • Sales – Supplier and buyer territories, census block demographics • Utilities – Markets are usually defined geographically • Local government – Cadasters, zones, counties, municipalities Most Spatial Business Rules Only Require a Simple Vocabulary • Describe how simple points, polygons and lines interact • Describe distances between them • Describe “at least” or “no more than” rules (aggregate spatial rules) Most Spatial Business Rules Never Use Most GIS Features • Continuous field data – Weather, climate, netCDF, raster • Slope and aspect – Digital elevation model, bathymetry, viewshed • Topology – The shoreline borders the shore • Spatial statistics – Autocorrelation, Moran’s I, Geary’s C, etc. -
Maa-123.2441 GIS Software Development 4 Op 4 Op Data And
Maa-123.2441 GIS Software Development 4 op Data and databases 10/27/2013 Jari Reini GIS – in 4 categories •Categories based on competences – Data collection and management – Spatial data analysis – Software development – GIS Solutions • Today concentrating on data collection, management and analysis (and partly SW development) Jari Reini 10/27/2013 Architectural choices in GIS (simplified) Desktop Client-Server Internet Application Server Database Jari Reini Database 10/27/2013 Principles •Re-use, Keep it simple •Use COTS as much as possible –Less in-house development –Less maintenance –Already includes a lot of required functionality •For example –Storage: Oracle Spatial database –Editing: ESRI ArcGIS –Quality checking: Radius, JavaML, JTS –Product Creation: FME and own tools 10/27/2013 Architecture and flow Data Sourcing Editing Conversion Products Public Comm upload Delivery unity Database Server Other Rule engine Quality Pre-filter checks Specs Jari Reini 10/27/2013 Content types •Maps (2D) •Voice-Enabled Maps •Address Points •Points of Interest •City Guides •Landmarks •3D maps Jari Reini 10/27/2013 Content gategories •Business content Guide –Office locations, factories, stores … -Voice Maps –Environmental data -Speed Cameras –Etc -Traffic •Find -Logistics –POIs Display –Address Points -2D/3D City Maps –Locality Index -3D Landmarks -3D Terrain Model Jari Reini 10/27/2013 Tele Atlas:Mobile Mapping Vans •Faster data collection •Superior accuracy •Advanced image collection for richer, more accurate content –Renders texture to buildings -
Development of a Query Language for GML Based on Xpath∗
Development of a Query Language for GML based on XPath∗ Jes´usM. Almendros-Jim´enez,Antonio Becerra-Ter´onand Francisco Garc´ıa-Garc´ıa University of Almer´ıa Almeria, Spain fjalmen,abecerra,[email protected] Abstract Geography Markup Language (GML) has been established as the standard language for the transport, storage and modelling of geographic information. In this paper we study how to adapt the XPath query language to GML documents. With this aim, we have defined a semantic based XPath language which is not based on the (tree-based) syntactic structure of GML documents, instead it is based on the \semantic structure" of GML documents. In other words, the proposed XPath language is based on the GML schema. We have developed a system called UALGIS, in order to implement the approach. Such system stores GML documents by means of the PostGIS RDBMS. In order to execute semantic-based XPath queries we have defined a translation of the queries into SQL. Such translation takes into account the GML schema. Finally, the system allows to visualize the result. With this aim, the result of a query is exported to the Keyhole Markup Language (KML) format. 1 Introduction The Geography Markup Language (GML) [7, 20, 21, 8] has been established as the standard language for the transport, storage and modeling of geographic information. GML is a dialect of the eXtensible Markup Language (XML) [27], which adapts XML to Geo-spatial data. XML allows to describe the structure of Web data by means of a tree. The tree structure is used to describe relations between data: for instance, a paper tag contains author, title and publisher as subtree tags and the subtree publisher can be described by means of name of the journal, country, editors, etc. -
Analytic Rasterization of Curves with Polynomial Filters
EUROGRAPHICS ’0x / N.N. and N.N. Volume 0 (1981), Number 0 (Editors) Analytic Rasterization of Curves with Polynomial Filters Josiah Manson and Scott Schaefer Texas A&M University Figure 1: Vector graphic art of butterflies represented by cubic curves, scaled by the golden ratio. The images were analytically rasterized using our method with a radial filter of radius three. Abstract We present a method of analytically rasterizing shapes that have curved boundaries and linear color gradients using piecewise polynomial prefilters. By transforming the convolution of filters with the image from an integral over area into a boundary integral, we find closed-form expressions for rasterizing shapes. We show that a poly- nomial expression can be used to rasterize any combination of polynomial curves and filters. Our rasterizer also handles rational quadratic boundaries, which allows us to evaluate circles and ellipses. We apply our technique to rasterizing vector graphics and show that our derivation gives an efficient implementation as a scanline rasterizer. Categories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism—Color, shading, shadowing, and texture 1. Introduction Although many shapes are stored in vector format, dis- plays are typically raster devices. This means that vector im- There are two basic ways of representing images: raster ages must be converted to pixel intensities to be displayed. graphics and vector graphics. Raster graphics are images that A major benefit of vector images is that they can be drawn are stored as an array of pixel values, whereas vector graph- accurately at different resolutions. -
UNIT 2. Curvatures of a Curve
UNIT 2. Curvatures of a Curve ========================================================================================================= ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Convergence of k-planes, the osculating k-plane, curves of general type in Rn, the osculating flag, vector fields, moving frames and Frenet frames along a curve, orientation of a vector space, the standard orientation of Rn, the distinguished Frenet frame, Gram-Schmidt orthogonalization process, Frenet formulas, curvatures, invariance theorems, curves with prescribed curvatures. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- One of the most important tools of analysis is linearization, or more generally, the approximation of general objects with easily treatable ones. E.g. the derivative of a function is the best linear approximation, Taylor’s polynomials are the best polynomial approximations