1. Geographical Data Mining
Thales Sehn Korting

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

3. 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?

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

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

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

7. 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

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

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

10. GeoDMA Dataflow
Adapted from [Silva, 2005]

11. GeoDMA Dataflow
Adapted from [Silva, 2005]

12. GeoDMA Dataflow
Adapted from [Silva, 2005]

13. GeoDMA Dataflow
Adapted from [Silva, 2005]

14. GeoDMA Dataflow
Adapted from [Silva, 2005]

15. GeoDMA Dataflow
Adapted from [Silva, 2005]

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

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

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

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

20. Geographical Data Mining
Try GeoDMA!