Visualisierung raumzeitlicher Meta-Informationen zur Visualisierung nutzer-generierter Geodaten

Presented at Geoinformatik 2012 in Braunschweig, Germany.

Transcript

1. Visualisierung raum-zeitlicher Metainformationen zu nutzer- generierten Geodaten Ein technisches Framework Oliver Roick, Lukas Loos, Alexander Zipf
3. 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
4. van Exel, M. (2011): A new OpenStreetMap visualization: Version contour Lines. URL: http://wp.me/pcUHq-5f
5. Trame, J. & C. Kessler (2011): Exploring the linage of Volunteered Geographic Information with heat maps. GeoViz, Hamburg, Germany.
7. Min/Max/Avg: ‣ Version number ‣ Number of Contributions per User ‣ Number of attributes Sum: ‣ Attributes ‣ Features ‣ Contributing users Area: ‣ Buildings ‣ Landuse ...
8. Average version number Number of features Average number of contributions per user Niederlande Datenimport
9. Polen Digitalisierung einzelner Luftbilder
10. +
11. Workflow Prozessierung und Visualisierung
12. 3. create SLD 2. process data + OSM 1. OSM import Postgres DB Map Server 4. pull data 5. request information Client
13. Datenbankdesign
14. attributes id: INT values: DOUBLE FK_attribute_types_id: INT FK_valid (time.id): INT FK_expired (time.id): INT FK_cells_id: INT times id: INT timestamp: DATETIME cells id: INT geometry: GEOMETRY attribute_types id: INT attribute: TEXT description: TEXT attribute_001 attribute_002 attribute_003
15. select attribute_001.id, attribute_001.cell_id, attribute_001.value, cells.the_geom, attribute_types.attribute, timesV.time AS timeValid, timesE.time AS timeExpired from attribute_001 left 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)));
16. Visualisierung
17. http://osmatrix.geoserver/wms/osmatrix/? request=getMap& layer=osmatrix:landuse_industrial& viewparams=time:1296758206 [...]
18. 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" } }, {...} ]
19. Die nächsten Schritte
20. OSM Weitere Daten
21. Analysen
22. Hagenauer, J. & M. Helbich (2011): Mining urban land-use patterns from volunteered geographic information by means of genetic algorithms and artificial neural networks. International Journal of Geographical Information Science. DOI:10.1080/13658816.2011.619501
23. Einfluss von Zellgröße und -form ?
24. Danke. Fragen? Oliver Roick Ruprecht-Karls-Universität Heidelberg Institute of Geography Chair of GIScience roick@uni-heidelberg.de twitter.com/oliverroick slideshare.net/oliverroick