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

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Danke.Fragen?

Oliver RoickRuprecht-Karls-Universität HeidelbergInstitute of GeographyChair of GIScience

roick@uni-heidelberg.detwitter.com/oliverroick

slideshare.net/oliverroick