Geographical Data Mining

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Presentation transcript:

Geographical Data Mining Thales Sehn Korting tkorting@dpi.inpe.br http://www.dpi.inpe.br/~tkorting/

Dynamic areas New Frontiers Intense Pressure Future expansion INPE 2003/2004: Intense Pressure Deforestation Forest Future expansion Non-forest Clouds/no data

Research Questions What are the different land use agents? When did a certain land use agent emerge? What are the dominant land use agents for each region? How do agents emerge and change in time?

More Research Questions What objects are in the image? How many houses? Where are the streets? What is hidden by the shadow?

Amount of data Simple crop 2562pixels x 3channels = 196608 values!

How to reduce input data? Segmentation  Regions Data Information Patch Metrics Area Perimeter Rectangularity … Spectral Metrics Pixels’ Mean Pixels’ STD Texture …

Geo Data Mining in Practice Segment image = software A Visualize segmentation = software B Extract attributes = software C Normalize attributes = software D Visualize attributes’ space = software D Select Samples = software E Classify regions = software F Visualize results = software B

In Practice More than 5 different softwares! Processing time File-conversion time etc. GeoDMA – Geographical Data Mining Analyst All tools on the same system

GeoDMA Input Processing Output Raster Polygons Attributes Extraction Normalization Supervised training Output Thematic classification

GeoDMA Dataflow Adapted from [Silva, 2005]

GeoDMA Dataflow Adapted from [Silva, 2005]

GeoDMA Dataflow Adapted from [Silva, 2005]

GeoDMA Dataflow Adapted from [Silva, 2005]

GeoDMA Dataflow Adapted from [Silva, 2005]

GeoDMA Dataflow Adapted from [Silva, 2005]

GeoDMA and TerraLib Image processing functions Data Mining algorithms Segmentation Region Growing Attributes Extraction Data Mining algorithms C4.5 Decision Tree Self-Organizing Maps ...

GeoDMA and TerraLib Image processing functions Data Mining algorithms Segmentation Region Growing Attributes Extraction Data Mining algorithms C4.5 Decision Tree Self-Organizing Maps ...

Application – Terra do Meio 1997 - 2004 Silva et al, 2008

Future Works Allow multi-temporal data mining Snapshots Try to explain changes More classification algorithms More precise segmentation

Geographical Data Mining Try GeoDMA! http://www.dpi.inpe.br/geodma/