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Visualisierung raumzeitlicher Meta-Informationen zur Visualisierung nutzer-generierter Geodaten

Visualisierung raumzeitlicher Meta-Informationen zur Visualisierung nutzer-generierter Geodaten

Presented at Geoinformatik 2012 in Braunschweig, Germany.

Oliver Roick

March 29, 2012
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  1. Visualisierung raum-zeitlicher
    Metainformationen zu nutzer-
    generierten Geodaten
    Ein technisches Framework
    Oliver Roick, Lukas Loos, Alexander Zipf

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  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

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  3. van Exel, M. (2011): A new OpenStreetMap visualization: Version contour Lines.
    URL: http://wp.me/pcUHq-5f

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  4. Trame, J. & C. Kessler (2011): Exploring the linage of Volunteered Geographic Information with
    heat maps. GeoViz, Hamburg, Germany.

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  5. Min/Max/Avg:
    ‣ Version number
    ‣ Number of Contributions per User
    ‣ Number of attributes
    Sum:
    ‣ Attributes
    ‣ Features
    ‣ Contributing users
    Area:
    ‣ Buildings
    ‣ Landuse
    ...

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

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  7. Polen Digitalisierung einzelner Luftbilder

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  8. Workflow
    Prozessierung und Visualisierung

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

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  10. Datenbankdesign

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  11. 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

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  12. 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)));

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  13. Visualisierung

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  14. http://osmatrix.geoserver/wms/osmatrix/?
    request=getMap&
    layer=osmatrix:landuse_industrial&
    viewparams=time:1296758206
    [...]

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  15. 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"
    }
    },
    {...}
    ]

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  16. Die nächsten Schritte

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  17. OSM
    Weitere Daten

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  18. 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

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  19. Einfluss von Zellgröße und -form
    ?

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  20. Danke.
    Fragen?
    Oliver Roick
    Ruprecht-Karls-Universität Heidelberg
    Institute of Geography
    Chair of GIScience
    [email protected]
    twitter.com/oliverroick
    slideshare.net/oliverroick

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