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The Evolution of Geo-Crowdsourcing: Bringing Volunteered Geographic Information to the Third Dimension

  • Marcus GoetzEmail author
  • Alexander Zipf
Chapter

Abstract

Volunteered geographic information (VGI) describes the collaborative and voluntary collection of any kind of spatial data, and has evolved to become an important source for geo-information. Users participate in VGI communities and share their data with other community members at no charge. The data is based on personal measurements or personal knowledge, as well as on available aerial imagery provided by Bing Maps etc. In the early beginnings, VGI comprised only two-dimensional (2D) data, but now more and more users also contribute 3D-compliant data such as height information. By utilizing such 3D information or 3D-VGI, it is possible to create virtual but increasingly realistic 3D map features and models that can be compared to products such as Google Earth. In this chapter, the evolution of VGI from 2D to 3D is discussed. In particular, the creation of a 3D virtual globe including visualization of 3D building models as well as traffic infrastructure, landuse areas, and points of interest (POIs) is reviewed. Additional data sources and the semantic enrichment of virtual models are also discussed. Crowdsourced geodata can serve as a real alternative data source and VGI can be utilized for generating rich 3D city models.

Keywords

Digital Terrain Model Volunteer Geographic Information Height Information Building Footprint Virtual Globe 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The authors would like to thank all members of the chair of GIScience for their proofreading and helpful hints and all contributors to the OSM-3D.org project. Additionally, we would like to thank our intern Daniel Söder for creating the screenshots of OSM-3D scenes for this chapter. This research has been partially funded by the Klaus-Tschira Foundation (KTS) Heidelberg.

References

  1. Brejc, I. (2011). Kosmos WorldFlier. http://igorbrejc.net/category/3d. Accessed November 7, 2011.
  2. Goetz, M., & Zipf, A. (2012). Towards defining a framework for the automatic derivation of 3D CityGML models from volunteered geographic information. International Journal of 3-D Information Modeling (IJ3DIM), 1(2), 1–16. Google Scholar
  3. Goodchild, M. F. (2007a). Citizens as sensors: The world of volunteered geography. GeoJournal, 69(4), 211–221.CrossRefGoogle Scholar
  4. Goodchild, M. F. (2007b). Citizens as voluntary sensors: Spatial data infrastructure in the world of Web 2.0. International Journal of Spatial Data Infrastructures Research, 2, 24–32.Google Scholar
  5. Gröger, G., Kolbe, T. H., Czerwinski, A., & Nagel, C. (2008). OpenGIS city geography markup language (CityGML) encoding standard – version 1.0.0. OGC Doc. No. 08–007r1.Google Scholar
  6. Kelly, T., & Wonka, P. (2011). Interactive architectural modeling with procedural extrusions. ACM Transactions on Graphics, 30(2), 14–28.CrossRefGoogle Scholar
  7. Kolbe, T. H., Gröger, G., & Plümer, L. (2008). CityGML – 3D city models and their potential for emergency response. In S. Zlatanova & J. Li (Eds.), Geospatial information technology for emergency response (pp. 257–274). London: Taylor & Francis.Google Scholar
  8. Laycock, R. G., & Day, A. M. (2003). Automatically generating roof models from building footprints. Paper presented at the 11th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG’ 03), Plzen – Bory, Czech Republic.Google Scholar
  9. Lee, J. (2001). 3D data model for representing topological relations of urban features. Paper presented at the 21st Annual ESRI International User Conference, San Diego, CA, United States.Google Scholar
  10. Lee, J. (2007). A three-dimensional navigable data model to support emergency response in microspatial built-environments. Annals of the Association of American Geographers, 97(3), 512–529.CrossRefGoogle Scholar
  11. Lee, J., & Zlatanova, S. (2008). A 3D data model and topological analyses for emergency response in urban areas. In S. Zlatanova & J. Li (Eds.), Geospatial information technology for emergency response (pp. 143–168). London: Taylor & Francis.Google Scholar
  12. OGC. (2005). Web 3D service. Discussion paper. Ref No. OGC 05–019.Google Scholar
  13. OSM. (2011a). OpenStreetMap. http://www.openstreetmap.org/. Accessed November 7, 2011.
  14. OSM. (2011b). OpenStreetMapWiki. http://wiki.openstreetmap.org/. Accessed November 7, 2011.
  15. OSM. (2011c). Proposed features/Building attributes. http://wiki.openstreetmap.org/wiki/Proposed_features/Building_attributes. Accessed November 7, 2011.
  16. OSM-3D. (2011). OSM-3D in XNavigator. http://www.osm-3d.org. Accessed November 7, 2011.
  17. Over, M., Schilling, A., Neubauer, S., & Zipf, A. (2010). Generating web-based 3D city models from OpenStreetMap: The current situation in Germany. Computers, Environment and Urban Systems, 34(6), 496–507.CrossRefGoogle Scholar
  18. Sarjakoski, T. (1998). Networked GIS for public participation – Emphasis on utilizing image data. Computers, Environment and Urban Systems, 22(4), 381–392.CrossRefGoogle Scholar
  19. Schilling, A., & Goetz, M. (2010). Decision support systems using 3D OGC services and indoor routing – Example scenario from the OWS-6 testbed. Paper presented at the 5th 3D GeoInfo conference, Berlin, Germany.Google Scholar
  20. Schilling, A., Over, M., Neubauer, S., Neis, P., Walenciak, G., & Zipf, A. (2009). Interoperable location based services for 3D cities on the web using user generated content from OpenStreetMap. Paper presented at the 27th urban data management symposium, Ljubljana, Slovenia.Google Scholar
  21. Song, W., & Sun, G. (2010). The role of mobile volunteered geographic information in urban management. Paper presented at the 18th international conference on geoinformatics, Beijing, China.Google Scholar
  22. Tagwatch. (2011). Tagwatch planet-latest. http://tagwatch.stoecker.eu/Planet-latest/En/tags.html. Accessed November 7, 2011.
  23. Yang, P. P.-J., Putra, S. Y., & Li, W. (2007). Viewsphere: A GIS-based 3D visibility analysis for urban design evaluation. Environment and Planning B: Planning and Design, 34(6), 971–992.CrossRefGoogle Scholar
  24. Ziegler, S. (2011). osm3d Viewer. http://www.osm3d.org. Accessed November 7, 2011.
  25. Zipf, A., Basanow, J., Neis, P., Neubauer, S., & Schilling, A. (2007). Towards 3D spatial data infrastructures (3D-SDI) based on open standards – Experiences, results and future issues. Paper presented at the 3D GeoInfo07, ISPRS WG IV/8 International Workshop on 3D Geo-information: Requirements, acquisition, modelling, analysis, visualisation, Delft, Netherlands.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht. 2013

Authors and Affiliations

  1. 1.GIScience research groupUniversity of HeidelbergHeidelbergGermany

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