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  • 1. Oliver Roick, Lukas Loos, Alexander ZipfVisualisierung raum-zeitlicherMetainformationen zu nutzer-generierten GeodatenEin technisches Framework
  • 2. Neis, P.; Zielstra, D. & Zipf, A. (2012): The Street Network Evolution of Crowdsourced Maps:OpenStreetMap in Germany 2007–2011. Future Internet, 4(1), 1-21
  • 3. van Exel, M. (2011): A new OpenStreetMap visualization: Version contour Lines.URL: http://wp.me/pcUHq-5f
  • 4. Trame, J. & C. Kessler (2011): Exploring the linage of Volunteered Geographic Information withheat maps. GeoViz, Hamburg, Germany.
  • 5. Min/Max/Avg: ‣ Version number ‣ Number of Contributions per User ‣ Number of attributesSum: ‣ Attributes ‣ Features ‣ Contributing usersArea: ‣ Buildings ‣ Landuse...
  • 6. Niederlande Datenimport Average number ofNumber of features contributions per user Average version number
  • 7. Polen Digitalisierung einzelner Luftbilder
  • 8. +
  • 9. WorkflowProzessierung und Visualisierung
  • 10. + 2. process data 1. OSM importOSM 4. pull data 5. request information Postgres DB Map Server Client 3. create SLD
  • 11. Datenbankdesign
  • 12. attribute_typesid: INTattribute: TEXTdescription: TEXT attributes id: INT values: DOUBLE FK_attribute_types_id: INT times FK_valid (time.id): INT FK_expired (time.id): INT id: INT FK_cells_id: INT timestamp: DATETIMEcellsid: INTgeometry: GEOMETRY attribute_001 attribute_002 attribute_003
  • 13. select attribute_001.id, attribute_001.cell_id, attribute_001.value, cells.the_geom, attribute_types.attribute, timesV.time AS timeValid, timesE.time AS timeExpiredfrom attribute_001left join cells on (attribute_001.cell_id = cells.id)left join times AS timesV on (attribute_001.valid = timesV.id)left join times AS timesE on (attribute_001.expired = timesE.id)left join attribute_types on (attribute_001.attribute_type_id = attribute_types.id)where (timesV.time <= to_timestamp(%dateV%) AND ((timesE.time > to_timestamp(%dateE%)) OR (timesE.time IS NULL)));
  • 14. Visualisierung
  • 15. http://osmatrix.geoserver/wms/osmatrix/? request=getMap& layer=osmatrix:landuse_industrial& viewparams=time:1296758206 [...]
  • 16. GetFeatureInfo"features": [ { "name": "landuse_industrial", "title": "Layer: landuse_industrial", "attributes": { "id": "154777", "cell_id": "1166098", "value": "78863.060546875", "the_geom": "POLYGON (...)", "attribute": "landuse_industrial", "timevalid": "21.12.2011 00:00:00", "timeexpired": "26.03.2012 14:32:33" } }, {...}]
  • 17. Die nächsten Schritte
  • 18. Weitere Daten OSM
  • 19. Analysen
  • 20. Hagenauer, J. & M. Helbich (2011): Mining urban land-use patterns from volunteered geographicinformation by means of genetic algorithms and artificial neural networks. International Journalof Geographical Information Science. DOI:10.1080/13658816.2011.619501
  • 21. Einfluss von Zellgröße und -form ?
  • 22. Danke.Fragen?Oliver RoickRuprecht-Karls-Universität Heidelberg roick@uni-heidelberg.deInstitute of Geography twitter.com/oliverroickChair of GIScience slideshare.net/oliverroick