Note: Intro -- Foreword -- Contents -- 1 An Introduction to OpenStreetMap in Geographic Information Science: Experiences, Research, and Applications -- Abstract -- 1 Introduction -- 2 A Short Overview of the OpenStreetMap Research Landscape -- 3 Geography of OpenStreetMap -- 4 Objectives and Scope -- 5 Structure of the Book -- References -- Part IData Management and Quality -- 2 Assessment of Logical Consistency in OpenStreetMap Based on the Spatial Similarity Concept -- Abstract -- 1 Introduction -- 2 Logical Consistency for OSM -- 3 Proposed Framework -- 3.1 Directional Relationships -- 3.2 Topological Relationships -- 3.3 Metric Distance Relationships -- 3.4 Proposed Methodology -- 4 Implementation -- 5 Conclusion -- References -- 3 Quality Assessment of the Contributed Land Use Information from OpenStreetMap Versus Authoritative Datasets -- Abstract -- 1 Introduction -- 2 Materials and Data Processing -- 2.1 OSM Dataset -- 2.2 GMESUA Dataset as a Reference Dataset -- 2.3 Study Areas -- 3 Methods -- 3.1 Logical Consistency and Topology -- 3.2 Harmonization of the Datasets Nomenclatures -- 3.3 Completeness -- 3.4 Thematic Accuracy -- 4 Results -- 4.1 Sensitivity to Pixel Size -- 4.2 Degree of Data Completeness -- 4.3 Overall and Per-class Analysis of Thematic Accuracy -- 4.3.1 Frankfurt -- 4.3.2 Munich -- 4.3.3 Berlin -- 4.3.4 Hamburg -- 4.4 Spatial Distribution of Agreements and Disagreements -- 5 Discussions and Conclusions -- 6 Recommendations -- Acknowledgments -- References -- 4 Improving Volunteered Geographic Information Quality Using a Tag Recommender System: The Case of OpenStreetMap -- Abstract -- 1 Introduction -- 2 Volunteered Geographic Information Quality -- 2.1 Data-Centric Approach -- 2.2 User-Centric Approach -- 2.3 Context-Centric Approach -- 3 Semantic Heterogeneity of OpenStreetMap Dataset. , 3.1 Sources of Semantic Heterogeneities -- 3.2 OpenStreetMap Tag Distribution -- 4 Improving VGI Dataset Quality Using Semantic Measurements and Folksonomy of Tags -- 4.1 Data Sources -- 4.2 User Interface and Prototype Functionalities -- 4.2.1 Automatic Suggestions of Tags -- 4.2.2 Notification of Unrelated Tags -- 5 Evaluations and Results -- 5.1 Experimental Setup -- 5.2 User Evaluation Results -- 6 Discussion and Conclusions -- Acknowledgments -- References -- 5 Inferring the Scale of OpenStreetMap Features -- Abstract -- 1 Introduction -- 2 Scale and Level of Detail -- 3 Two Methods for the Automatic Inference of Scale -- 3.1 Scale Inference with a Multiple Criteria Decision Technique -- 3.1.1 Measuring Level of Detail -- 3.1.2 Combining Criteria to Infer a LoD Category -- 3.2 Empiric Scale Inference -- 4 Combining Both Methods to Improve Scale Inference -- 4.1 Compared Evaluation of Both Inference Methods -- 4.2 Mixing Both Inference Methods -- 5 LoD Harmonization for Large-Scale Automatic Mapping -- 6 Open Problems -- 6.1 Scale Inference for Point Objects -- 6.2 Does Feature Density Alter Scale Level? -- 6.3 The Scale of Objects with Simple Shapes -- 7 Conclusions -- References -- 6 Data Retrieval for Small Spatial Regions in OpenStreetMap -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Challenges -- 3.1 Structure of OSM Data -- 3.2 General Query Concepts -- 3.3 Featured Usage Patterns -- 3.4 Hardware Constraints -- 4 Design Considerations -- 4.1 Initial Design -- 4.2 Adaptions -- 5 Evaluation -- 5.1 Performance on Essential Queries -- 5.1.1 Methodology -- 5.1.2 Different Area Sizes -- 5.1.3 Speedup of Filtering -- 5.1.4 Comparison to the Main API -- 5.2 Performance in the Field -- 5.2.1 Discussion and Conclusion -- 5.3 Future Improvements -- References -- Part IISocial Context. , 7 The Impact of Society on Volunteered Geographic Information: The Case of OpenStreetMap -- Abstract -- 1 Introduction -- 2 OpenStreetMap London -- 2.1 Benchmarks -- 2.2 Metrics -- 3 Impact of Society on Information Completeness -- 3.1 A Non-uniform Completeness -- 3.2 Growth of Spatial Content Production -- 4 Impact of Social Mapping Parties -- 4.1 Direct Impact of Mapping Parties -- 4.2 Indirect Impact of Mapping Parties -- 5 Summary and Conclusion -- References -- 8 Social and Political Dimensions of the OpenStreetMap Project: Towards a Critical Geographical Research Agenda -- Abstract -- 1 Introduction -- 2 Geoinformation, Cartographic (Re)presentation and Society -- 2.1 Critical Cartography I: The Social Construction of Maps -- 2.2 Critical Cartography II: Mapping as Socio-technical Practice -- 2.3 Social Science Perspectives on the Transformation of Geoinformation and Cartography in the Age of GIS and the Geoweb -- 3 OpenStreetMap: Opening and Democratizing Geoinformation and Cartography? -- 4 Mapping Modes: The Social and Political Dimensions of OpenStreetMap -- 4.1 Authorship: The Socio-cultural Embeddedness of OSM Practices -- 4.2 Algorithms and Other Blackboxes: Unpacking the Technical Infrastructure of OSM -- 4.3 Governance of OSM: Doocracy---Meritocracy---Technocracy---Bureaucracy -- 5 Methods: Analyzing OSM -- 5.1 Data-Driven Research on OSM -- 5.2 Ethnography and Auto-ethnography -- 5.3 The Need for Mixed Methods Approaches -- 6 Maps and Mosques: A Case Study on the Transformation of Techniques, Practices, and Conventions Within OSM -- 6.1 Concealed Mosques in State-Based Cartography -- 6.2 Newly Open but Fixed Practices in OSM -- 6.2.1 Data Structure and the Wiki -- 6.2.2 Rendering and Editing Software -- 6.2.3 Community Practices -- 6.2.4 New Openings and Fixations -- 7 Conclusions -- References. , 9 Spatial Collaboration Networks of OpenStreetMap -- Abstract -- 1 Introduction -- 2 Non-spatial and Spatial Forms of Collaboration -- 3 Spatial Collaboration Network Analysis -- 4 Measuring Collaboration Depth by Interlocking -- 5 Breadth and Depth of Collaboration in OSM -- 6 Conclusion and Outlook -- References -- Part IIINetwork Modeling and Routing -- 10 Route Choice Analysis of Urban Cycling Behaviors Using OpenStreetMap: Evidence from a British Urban Environment -- Abstract -- 1 Introduction -- 2 Contextual Background -- 3 Methods -- 3.1 Study Area and Sample -- 3.2 OpenStreetMap -- 3.3 Variable and Route Generation for Route Choice Analysis -- 4 Analysis and Results -- 5 Discussion and Conclusion -- Acknowledgments -- References -- 11 The Next Generation of Navigational Services Using OpenStreetMap Data: The Integration of Augmented Reality and Graph Databases -- Abstract -- 1 Introduction -- 2 Storage and Management of Highly Connected Data in SQL and NoSQL -- 3 SQL (Relational) Database and Managing Highly Connected Data -- 4 NoSQL Databases and Handling Highly Connected Data -- 5 What Is Special About Graph Databases? -- 6 Related Work and Benchmarks -- 7 Implementation -- 8 Augmented Reality Navigation Service Implementation -- 9 Conclusion and Future Work -- Acknowledgments -- References -- 12 Building a Multimodal Urban Network Model Using OpenStreetMap Data for the Analysis of Sustainable Accessibility -- Abstract -- 1 Introduction -- 2 The Structure and Infrastructure of a Multimodal Urban Network Model -- 2.1 Data and Software Stack -- 2.2 Spatial Data Model -- 3 Creating the Private Transport System -- 3.1 Street Network Segment Classification and Correction -- 3.1.1 Street Network Segment Classification -- 3.1.2 Street Network Segment Correction -- 3.2 Street Intersection Node Classification -- 3.3 Pedestrian Areas Links Generation. , 4 Creating the Public Transport System -- 4.1 Public Transport Networks Preparation -- 4.1.1 The Rail, Metro and Tram Networks -- 4.1.2 The Bus Network -- 4.2 Public Transport Network Interfaces Generation -- 5 Creating the Land Use System -- 6 Results -- 6.1 Multimodal Network Model Analysis -- 6.2 Reflections on the Multimodal Network Model -- 7 Conclusions -- Acknowledgments -- References -- Part IVLand Management and Urban Form -- 13 Assessing OpenStreetMap as an Open Property Map -- Abstract -- 1 Setting the Scene -- 2 Assessing Spatial Data Quality -- 3 Assessment Methodology -- 3.1 Area of Study -- 3.2 Feature Matching -- 3.3 Quality of Feature Representations -- 3.4 Positional Uncertainty -- 3.5 Attribute Accuracy -- 4 Results of the Assessment -- 4.1 Data Completeness -- 4.2 Feature Vertex and Part Differences -- 4.3 Mean Vertex Spacing Differences -- 4.4 Feature Area Differences -- 4.5 Shape Similarity -- 4.6 Position Accuracy -- 4.7 Attribute Accuracy -- 5 Discussion of the Results -- 6 Conclusions and Future Research -- References -- 14 Investigating the Potential of OpenStreetMap for Land Use/Land Cover Production: A Case Study for Continental Portugal -- Abstract -- 1 Introduction -- 1.1 Land Use and Land Cover Production -- 1.2 Volunteered Geographic Information and OpenStreetMap -- 2 Volunteered Geographic Information and OpenStreetMap for Land Use/Land Cover Production -- 2.1 Volunteered Geographic Information for Land Use/Land Cover Production -- 2.2 OpenStreetMap for Land Use/Land Cover Production -- 3 Materials and Methods -- 3.1 Study Area and Data -- 3.2 Methods -- 4 Results and Discussion -- 4.1 Analysis of the OSM Dataset -- 4.2 Correspondence Between OSM Point Types and CLC Classes -- 4.3 Classification Accuracy Analysis -- 5 Conclusions and Future Research Directions -- References. , 15 Using Crowd-Sourced Data to Quantify the Complex Urban Fabric---OpenStreetMap and the Urban--Rural Index.

Note: Förderkennzeichen BMBF 13N11381. - Verbund-Nummer 01090025 , Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden

Note: Förderkennzeichen BMBF 28-1-54.049-10 [richtig] - 28-1-54.050-10 [falsch]. - Verbund-Nr. 01106705 , Im Kopf der Titelseite: "CLAAS, E-Systems GmbH & Co. KG", "GIScience" , Zusammenfassung in deutscher Sprache , Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden

Note: Systemvoraussetzungen: Acrobat reader. , Kurzfassung dt. und engl.

Note: Includes bibliographical references , Vendor-supplied metadata , Foreword; Contents; 1 An Introduction to OpenStreetMap in Geographic Information Science: Experiences, Research, and Applications; Abstract; 1 Introduction; 2 A Short Overview of the OpenStreetMap Research Landscape; 3 Geography of OpenStreetMap; 4 Objectives and Scope; 5 Structure of the Book; References; Part IData Management and Quality; 2 Assessment of Logical Consistency in OpenStreetMap Based on the Spatial Similarity Concept; Abstract; 1 Introduction; 2 Logical Consistency for OSM; 3 Proposed Framework; 3.1 Directional Relationships; 3.2 Topological Relationships , 3.3 Metric Distance Relationships3.4 Proposed Methodology; 4 Implementation; 5 Conclusion; References; 3 Quality Assessment of the Contributed Land Use Information from OpenStreetMap Versus Authoritative Datasets; Abstract; 1 Introduction; 2 Materials and Data Processing; 2.1 OSM Dataset; 2.2 GMESUA Dataset as a Reference Dataset; 2.3 Study Areas; 3 Methods; 3.1 Logical Consistency and Topology; 3.2 Harmonization of the Datasets Nomenclatures; 3.3 Completeness; 3.4 Thematic Accuracy; 4 Results; 4.1 Sensitivity to Pixel Size; 4.2 Degree of Data Completeness , 4.3 Overall and Per-class Analysis of Thematic Accuracy4.3.1 Frankfurt; 4.3.2 Munich; 4.3.3 Berlin; 4.3.4 Hamburg; 4.4 Spatial Distribution of Agreements and Disagreements; 5 Discussions and Conclusions; 6 Recommendations; Acknowledgments; References; 4 Improving Volunteered Geographic Information Quality Using a Tag Recommender System: The Case of OpenStreetMap; Abstract; 1 Introduction; 2 Volunteered Geographic Information Quality; 2.1 Data-Centric Approach; 2.2 User-Centric Approach; 2.3 Context-Centric Approach; 3 Semantic Heterogeneity of OpenStreetMap Dataset , 3.1 Sources of Semantic Heterogeneities3.2 OpenStreetMap Tag Distribution; 4 Improving VGI Dataset Quality Using Semantic Measurements and Folksonomy of Tags; 4.1 Data Sources; 4.2 User Interface and Prototype Functionalities; 4.2.1 Automatic Suggestions of Tags; 4.2.2 Notification of Unrelated Tags; 5 Evaluations and Results; 5.1 Experimental Setup; 5.2 User Evaluation Results; 6 Discussion and Conclusions; Acknowledgments; References; 5 Inferring the Scale of OpenStreetMap Features; Abstract; 1 Introduction; 2 Scale and Level of Detail; 3 Two Methods for the Automatic Inference of Scale , 3.1 Scale Inference with a Multiple Criteria Decision Technique3.1.1 Measuring Level of Detail; 3.1.2 Combining Criteria to Infer a LoD Category; 3.2 Empiric Scale Inference; 4 Combining Both Methods to Improve Scale Inference; 4.1 Compared Evaluation of Both Inference Methods; 4.2 Mixing Both Inference Methods; 5 LoD Harmonization for Large-Scale Automatic Mapping; 6 Open Problems; 6.1 Scale Inference for Point Objects; 6.2 Does Feature Density Alter Scale Level?; 6.3 The Scale of Objects with Simple Shapes; 7 Conclusions; References , 6 Data Retrieval for Small Spatial Regions in OpenStreetMap

Note: Förderkennzeichen BMBF 01UV1815 , Laufzeit: 01.11.2018-31.06.2022

Note: Förderkennzeichen BMVI 19F2073A-G , Verbundnummer 01184214 , Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden

Note: Förderkennzeichen BMBF 1704B05 [falsch] - 1704C05 [richtig] , Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden. - Auch als gedr. Ausg. vorhanden , Systemvoraussetzungen: Acrobat reader.