This document presents a technical framework for visualizing spatial and temporal metadata from user-generated geospatial data. It describes a workflow and database design to process and visualize OpenStreetMap data. Attributes from OSM features are stored along with their valid and expired timestamps. A WMS and GetFeatureInfo service are used to visualize the attribute data for different points in time. Future work includes analyzing additional OSM data and the influence of cell size and shape on analyses.

1. Oliver Roick, Lukas Loos, Alexander Zipf
Visualisierung raum-zeitlicher
Metainformationen zu nutzer-
generierten Geodaten
Ein technisches Framework

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. Niederlande Datenimport
Average number of
Number of features contributions per user Average version number

9. Polen Digitalisierung einzelner Luftbilder

10. +

11. Workflow
Prozessierung und Visualisierung

12. +
2. process data
1. OSM import
OSM
4. pull data 5. request
information
Postgres DB Map Server Client
3. create SLD

13. Datenbankdesign

14. attribute_types
id: INT
attribute: TEXT
description: 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: DATETIME
cells
id: INT
geometry: GEOMETRY
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. Weitere Daten
OSM

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 roick@uni-heidelberg.de
Institute of Geography twitter.com/oliverroick
Chair of GIScience slideshare.net/oliverroick