Centre for Geo-Information Thesis Report GIRS-2016-34 Robin

Centre for Geo-Information Thesis Report GIRS-2016-34 Robin

Centre for Geo-Information Thesis Report GIRS-2016-34 Robin Ammerlaan September, 2016 September, Wageningen UR Droevendaalsesteeg 4 6708 PB Wageningen Telephone: +31 (0)31 7480100 AMS Institute Mauritskade 62 1092AD Amsterdam Telephone: +31 (0)20 6651350 Robin Ammerlaan (920626 014 100) Supervisors Corné Vreugdenhil Msc.1 prof. dr. ir. Arnold Bregt1 1 Laboratory of Geo-Information Science and Remote Sensing Wageningen, The Netherlands A thesis submitted in partial fulfilment of the degree of Master of Science at Wageningen University and Research Centre, The Netherlands September, 2016 Wageningen, The Netherlands Thesis code number: GRS-80436 Thesis report: GIRS-2016-34 Wageningen University and Research Centre Laboratory of Geo-Information Science and Remote Sensing ii During the 2015 United Nations Climate Change Conference (COP21) world leaders acknowledged that previous goals to reduce global warming were inadequate. Countries are to pursue efforts to limit the global temperature increase to 1.5 °C. The waste sector is in a unique position to reduce emissions from all sectors of the global economy by reducing and recovering waste. Metropolitan areas present particularly interesting opportunities. This study will focus on the municipal solid waste infrastructure of Amsterdam. More accessible waste containers yield higher recycling rates. But how do we determine accessibility? Through a review of the literature and the exploration of the study area we establish which factors determine pedestrian route choice within the context of household waste disposal. Distance is the most important of these factors. In order to determine distance, specific paths need to be predicted. In doing so we tackle something everyone has an intuitive feeling about, but is never the less complex and difficult to quantify. We compare the commonly applied Euclidean and Network distance methods with a less common approach: Least Cost Path Analysis (LCPA). The Behavioural Model of Environment provides the conceptual framework for a LCPA-model. The three distance measurement methods are compared through descriptive statistics and visual mapping methods. The results show that LCPA has various advantages over Euclidean and Network distance measurements. A validation of the results shows Euclidean distances to be clear underestimations of real pedestrian route distances. The accuracy of the LCPA and Network method cannot be established conclusively. While the validation indicates that LCPA may be most accurate, a more large-scale validation is required. Keywords: Household waste, Facility placement, Pedestrian route choice, Route distance iii iv I would like to take this opportunity to thank my supervisors: Corné Vreugdenhil, whose infectious enthusiasm for the subject has greatly inspired my own and whose in-depth discussions and feedback have greatly improved my work, and Arnold Bregt, who managed to give me elaborate feedback despite being unable to type due to a hand injury. I would like to thank the others within the ‘Smart Wasting in Amsterdam’ project: Frits Steenhuisen, whose keen interest in the results motivated me, and Steven Schrauwen, whose own master thesis complements this one. I would like to thank my girlfriend, Laura, whose support and insights were invaluable. I would also like to thank my fellow students for their company and friendship. Especially the hardy few who, like me, worked throughout the summer holidays. Finally, I would like to thank my friends and family for their support. Robin Ammerlaan September, 2016 v vi Abstract ____________________________________________ iii Acknowledgements _____________________________________ v Table of Contents _____________________________________ vii List of Figures ______________________________________ x List of Tables ______________________________________ xi List of Abbreviations _________________________________ xii 1 Introduction _______________________________________ 1 1.1 The global context _________________________________ 1 1.2 The European and Dutch Context ________________________ 3 1.3 Recycling behaviour ________________________________ 5 1.4 Objective and research questions ________________________ 6 1.5 Reading guide____________________________________ 8 2 Background _______________________________________ 9 2.1 Pedestrian behaviour _______________________________ 9 2.1.1 Route choice __________________________________ 9 2.1.2 Walkability ___________________________________ 10 2.2 Spatial accessibility ________________________________ 11 2.2.1 Facility placement _______________________________ 12 2.3 Measuring physical distance ___________________________ 13 2.3.1 Euclidean distance ______________________________ 14 2.3.2 Network distance _______________________________ 15 2.3.3 Least Cost Path Analysis (LCPA) _______________________ 15 3 Frameworks _______________________________________ 17 3.1 Conceptual framework ______________________________ 17 3.2 Environmental factors for Least Cost Path Analysis (LCPA) _________ 18 3.2.1 Physical barriers ________________________________ 19 3.2.2 Spatial-temporal obstacles __________________________ 19 3.2.3 Walking surface ________________________________ 19 3.3 Legislative framework _______________________________ 21 4 Methodology ______________________________________ 22 4.1 Study area ______________________________________ 23 vii 4.1.1 Amsterdam __________________________________ 24 4.1.2 Oostelijk havengebied ____________________________ 25 4.2 Gathering and pre-processing data ______________________ 25 4.2.1 Source point dataset ____________________________ 26 4.2.2 Destination point dataset __________________________ 28 4.2.3 Network dataset ________________________________ 31 4.2.4 Land use dataset ________________________________ 32 4.3 Calculating Euclidean Distance __________________________ 33 4.4 Calculating Network Distance _________________________ 34 4.5 Least Cost Path Analysis (LCPA) _________________________ 35 4.5.1 Parameter choices ______________________________ 36 4.5.2 Assigning weight values __________________________ 38 5 Results _________________________________________ 45 5.1 Euclidean distance measurements _______________________ 45 5.2 Network distance measurements _______________________ 47 5.3 Least Cost Path Analysis (LCPA) distances __________________ 49 5.4 Methods side-by-side ______________________________ 52 6 Discussion _______________________________________ 56 6.1 Discussion of results _______________________________ 56 6.1.1 Euclidean distance _____________________________ 56 6.1.2 Network distance ______________________________ 56 6.1.3 Least Cost Path Analysis distance _____________________ 58 6.2 Validation ______________________________________ 61 6.3 Limitations of the research ____________________________ 61 6.3.1 Source point dataset ____________________________ 62 6.3.2 Destination point dataset __________________________ 63 6.3.3 Cost rasters __________________________________ 63 6.3.4 Practicality __________________________________ 64 6.4 Amsterdam’s waste collection infrastructure ________________ 65 7 Conclusion and Recommendations _________________________ 66 7.1 Conclusion ____________________________________ 66 7.2 Recommendations for further research ____________________ 68 7.2.1 Weight values ________________________________ 68 viii 7.2.2 Internal pathways ______________________________ 68 7.3 Recommendations to the municipality of Amsterdam ___________ 68 Appendix A: Validation __________________________________ 70 A.1.1 Sample selection ___________________________________ 71 A.1.2 Gathering data ____________________________________ 71 A.1.2.1 Interviewing method ______________________________ 71 A.1.2.2 Contents of the interview ___________________________72 A.1.2.3 Processing the data _______________________________72 A.1.3 Results _______________________________________ 74 A.1.3.1 Predictions ___________________________________ 74 A.1.3.2 Route distances ________________________________ 74 A.1.4 Discussion ______________________________________ 77 A.1.4.1 Sample bias ___________________________________ 77 A.1.4.2 Validation results ________________________________ 77 A.1.4.3 An alternative cost raster __________________________ 78 APPENDIX B: EUCLIDEAN VISUALS ______________________________ 79 APPENDIX C: NETWORK DISTANCE VISUALS __________________________ 81 APPENDIX D: DVD CONTENTS ________________________________ 83 ix Figure 1: The waste hierarchy (Hoornweg and Bhada-Tata, 2012) __________ 2 Figure 2: A scatterplot of household waste separation rates and address density per km2 ______________________________________________ 4 Figure 3: Flow chart of the methodology, results, and validation __________ 22 Figure 4: The municipality of Amsterdam (base map by StamenDesign) _______ 23 Figure 5: The Eastern Docklands and Java-eiland (base map by StamenDesign) ___ 23 Figure 6 A simplified overview of model 0A _______________________27 Figure 7: Types of MSW containers in Amsterdam __________________ 29 Figure 8: Number of households per waste container ________________ 30 Figure 9: The network dataset for Amsterdam based on OSM data __________ 31 Figure 10: An information model of the objects included in the BGT (Gemeente Amsterdam, 2016b) _____________________________________ 32 Figure 11: The principle of Euclidean Distance ______________________ 33 Figure 12: A simplified overview of the Euclidean distance model _________ 34 Figure 13: The principle of Network Distance

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