OpenStreetMap in GIScience: Experiences, Research, and Applications
An Introduction to OpenStreetMap in Geographic Information Science: Experiences, Research, and Applications -- Assessment of logical consistency in OpenStreetMap based on the spatial similarity concept -- Quality assessment of the contributed land use information from OpenStreetMap versus authoritat...
Gespeichert in:
| 1. Verfasser: | |
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| Weitere Verfasser: | , , |
| Dokumenttyp: | Buch/Monographie |
| Sprache: | Englisch |
| Veröffentlicht: |
Cham Heidelberg
Springer
2015
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| Schriftenreihe: | Lecture Notes in Geoinformation and Cartography
SpringerLink Bücher |
| DOI: | 10.1007/978-3-319-14280-7 |
| Schlagworte: | |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1007/978-3-319-14280-7 Verlag, Volltext: http://dx.doi.org/10.1007/978-3-319-14280-7 Cover: https://swbplus.bsz-bw.de/bsz429163479cov.jpg 
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| Verfasserangaben: | edited by Jamal Jokar Arsanjani, Alexander Zipf, Peter Mooney, Marco Helbich |
MARC
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| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 6 Data Retrieval for Small Spatial Regions in OpenStreetMap | |
| 520 | |a An Introduction to OpenStreetMap in Geographic Information Science: Experiences, Research, and Applications -- Assessment of logical consistency in OpenStreetMap based on the spatial similarity concept -- Quality assessment of the contributed land use information from OpenStreetMap versus authoritative datasets -- Improving volunteered geographic information quality using a tag recommender system: The case of OpenStreetMap -- Inferring the Scale of OpenStreetMap Features -- Data retrieval for small spatial regions in OpenStreetMap -- The Impact of Society on Volunteered Geographic Information: The case of OpenStreetMap -- Social and political dimensions of the OpenStreetMap project: Towards a critical geographical research agenda -- Spatial Collaboration Networks of OpenStreetMap -- Route choice analysis of urban cycling behaviors using OpenStreetMap: Evidence from a British urban environment -- The Next Generation of Navigational Services using OpenStreetMap data: the Integration of Augmented Reality and Graph Databases -- Building a Multimodal Urban Network Model Using OpenStreetMap Data for the Analysis of Sustainable Accessibility -- Assessing OpenStreetMap as an Open Property Map -- Investigating the Potential of OpenStreetMap for Land Use/Land Cover Production: A Case Study for Continental Portugal -- Using Crowd-Sourced Data to Quantify the Complex Urban Fabric – OpenStreetMap and the Urban–Rural Index. | ||
| 520 | |a This edited volume presents a collection of lessons learned with, and research conducted on, OpenStreetMap, the goal being to promote the project’s integration. The respective chapters address a) state-of-the-art and cutting-edge approaches to data quality analysis in OpenStreetMap, b) investigations on understanding OpenStreetMap contributors and the nature of their contributions, c) identifying patterns of contributions and contributors, d) applications of OpenStreetMap in different domains, e) mining value-added knowledge and information from OpenStreetMap, f) limitations in the analysis OpenStreetMap data, and g) integrating OpenStreetMap with commercial and non-commercial datasets. The book offers an ideal opportunity to present and disseminate a number of cutting-edge developments and applications in the field of geography, spatial statistics, GIS, social science, and cartography. | ||
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