Visualisierung raum-zeitlicher Metainformationen zu nutzer-generierten GeodatenEin technisches Framework
Oliver Roick, Lukas Loos, Alexander Zipf
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
van Exel, M. (2011): A new OpenStreetMap visualization: Version contour Lines. URL: http://wp.me/pcUHq-5f
Trame, J. & C. Kessler (2011): Exploring the linage of Volunteered Geographic Information with heat maps. GeoViz, Hamburg, Germany.
Min/Max/Avg:‣ Version number‣ Number of Contributions per User‣ Number of attributes
Sum:‣ Attributes‣ Features‣ Contributing users
Area:‣ Buildings‣ Landuse
...
Average version numberNumber of featuresAverage number of contributions per user
Niederlande Datenimport
Polen Digitalisierung einzelner Luftbilder
+
WorkflowProzessierung und Visualisierung
3. create SLD
2. process data
+
OSM1. OSM import
Postgres DB Map Server
4. pull data 5. request information
Client
Datenbankdesign
attributesid: INTvalues: DOUBLEFK_attribute_types_id: INTFK_valid (time.id): INTFK_expired (time.id): INTFK_cells_id: INT
timesid: INTtimestamp: DATETIME
cellsid: INTgeometry: GEOMETRY
attribute_typesid: INTattribute: TEXTdescription: TEXT
attribute_001 attribute_002 attribute_003
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)));
Visualisierung
http://osmatrix.geoserver/wms/osmatrix/? request=getMap& layer=osmatrix:landuse_industrial& viewparams=time:1296758206 [...]
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" } },
{...}]
Die nächsten Schritte
OSM
Weitere Daten
Analysen
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
Einfluss von Zellgröße und -form
?
Danke.Fragen?
Oliver RoickRuprecht-Karls-Universität HeidelbergInstitute of GeographyChair of GIScience
[email protected]/oliverroick
slideshare.net/oliverroick