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CONTEXT: EUSIS = nested databases

Building a EUROPEAN DATABASE SOTER 1:5M from the EUROPEAN DATABASE EUSIS 1:1M An example of generalization of a soil geographical database.

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CONTEXT: EUSIS = nested databases

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  1. Building aEUROPEAN DATABASE SOTER 1:5Mfrom theEUROPEAN DATABASE EUSIS 1:1MAn example of generalizationof a soil geographical database KING Dominique(1), SABY Nicolas(1), LE BAS Christine(1), NACHTERGAELE Freddy(2), VAN ENGELEN Vincent(3), EIMBERCK Micheline(1), JAMAGNE Marcel(1), LAMBERT Jean Jacques(1), BRIDGES Mike(3), HARTWICH Reinhard(4), MONTANARELLA Luca(5),CHARLE Fany(1), DAROUSSIN Joël(1) (1)INRA Soil Science, Orléans, FRANCE(2)FAO GLS, Roma, ITALY(3)ISRIC, Wageningen, THE NETHERLANDS(4) BGR, Berlin, GERMANY(5)JRC, European Soil Bureau, Ispra, ITALY

  2. World Soil and Terrain Database SOTER 1:5M European Soil Information System EUSIS 1:1M Georeferenced Soil Database of Europe Catchment Information System Local Soil Information System CONTEXT: EUSIS = nested databases

  3. transfer information... OBJECTIVE: World Soil and Terrain Database SOTER 1:5M European Soil Information System EUSIS 1:1M • Attribute data (semantic) • EUSIS  SOTER • Spatial data(geometry) • 1:1M  1:5M

  4. transfer information... OBJECTIVE: World Soil and Terrain Database SOTER 1:5M European Soil Information System EUSIS 1:1M • with aims to… • prevent from loss of information • preserve compatibility in • up-scaling(location, pattern, topology) • have an explicit algorithm

  5. Terrain Unit (TU) DEM Soil Mapping Unit (SMU) Terrain Component (TC) Soil Typological Unit (STU) Soil Component (SC) area data point data Soil Profile Soil Profile DATA STRUCTURES: EUSIS 1:1M SOTER 1:5M

  6. For building: • EUSIS database • (ESB, 2001) • - DEM 1x1 km • (Defence Mapping Agency, 1992) • For validating: • - SOVEUR project • (Batjes and Van Engelen, 1997) • - Soil Regions • (Finke and Hartwich, 1998) DATA USED:

  7. METHOD Semantic: derive SOTERcriteria from EUSIS and DEM attributes Geometry: delineate SOTER units from EUSIS boundaries

  8. Elevation Mean/EUSIS polygon Reclass to SOTER classes Slope (calibrated in some areas using higher resolution DEMs) Mean/EUSIS polygon Reclass to SOTER classes Relief (STD of elevation within 5km radius) Mean/EUSIS polygon Reclass to SOTER classes • Mean slope per • EUSIS polygon • SOTER classes DEM 1x1km Slope calculation Building SOTER criteria « Major Land Forms » DEM 1km

  9. DEM 1km Elevation Mean/EUSIS polygon Reclass to SOTER classes Slope (calibrated in some areas using higher resolution DEMs) Mean/EUSIS polygon Reclass to SOTER classes Relief (STD of elevation within 5km radius) Mean/EUSIS polygon Reclass to SOTER classes Combine (overlay) SOTER Major Land Forms (MLF) Building SOTER criteria « Major Land Forms »

  10. DEM 1km Elevation Mean/EUSIS polygon Reclass to SOTER classes Slope (calibrated in some areas using higher resolution DEMs) Mean/EUSIS polygon Reclass to SOTER classes Relief (STD of elevation within 5km radius) Mean/EUSIS polygon Reclass to SOTER classes Combine (overlay) Linear shape Soil name (Fluvisol, Gleysol, Histosol) + EUSIS Valleys Replace SOTER Major Land Forms (MLF) Building SOTER criteria « Major Land Forms »

  11. EUSIS Dominant SOTER Lithology/EUSIS polygon Taxotransfer rule Parent material Taxotransfer rule SOTER Lithology Building SOTER criteria « lithology » EUSIS lithology SOTER lithology Examples: Secondary chalk  SO1 (limestone, carbonate rocks) Marl  SO2 (marl and other mixtures) Claystone  SC3 (siltstone, mustone, claystone) … …  … …

  12. Combine (overlay) Agregate (dissolve) SOTER Terrain Units (TU) at 1:1M (MLF, Lithology) Rule driven polygon merge + line simplification SOTER TU at 1:5M (MLF, Lithology) Building Terrain Units (TU) SOTER Major Land Forms (MLF) Dominant SOTER Lithology/EUSIS polygon

  13. Structure of resulting TU database 1,1 n,1

  14. Combine Soil name (FAO level 2) Dominant soil name/EUSIS polygon Soil associations or « Terrain Components » (« TC ») (MLF, Lithology, Soil name) Rule driven polygon merge (25 mm2 SOTER criteria Within TUs) SOTER « TC » at 1:5M Building « Terrain Components » (TC) SOTER TU at 1:5M (MLF, Lithology) EUSIS

  15. n,1 Structure of resulting TU and TC database 1,1 n,1

  16. Integration Soil Mapping Units (SMU) List of Soil names (FAO level 2)/« TC » Select 10 most dominant soil names Rule driven distribution of remainers SOTER « Soil Components » (« SC ») Building « Soil Components » SOTER « TC » at 1:5M EUSIS

  17. 1,n n,n Structure of resulting SOTER database 1,1 n,1 n,1

  18. SOTER « Soil Components » (« SC ») Attach Profile dataset Select Building the profile dataset: the missing part EUSIS Profiles

  19. RESULTS EUSIS 1:1M SOTER 1:1M SOTER 1:5M Polygons 27500 20500 8200 Mapping units 1600 200 155 Mapping units 95% of Europe 420 80 75 semantic geometric

  20. SOTER 1:5M Major Lanforms

  21. SOTER 1:5M Lithology

  22. 100 90 80 Database stability 70 60 50 Percentage 25 mm² at 1:5 M 40 30 Reduction in the number of objects 20 10 0 0 200 400 600 800 1000 1200 1400 Threshold in km² 56 0 16 24 32 40 48 8 Threshold in mm² at 1/5 000 000 Analyse sensitivity

  23. 100 Polygon merge with rules 90 without rules 80 70 Percentage 60 25 mm² at 1:5 M 50 40 0 200 400 600 800 1000 1200 1400 Threshold in km² Stability to original database

  24. ? ? ? Influence of polygon merge with rules 46 % improvement using rules

  25. Example AFTER, WITHOUT RULES BEFORE AFTER, WITH RULES 200 km² threshold Soil name (FAO level 2)

  26. ? ? ? Which neighbour to merge in? Merging polygons (1)

  27. Without rules Merging polygons (2)

  28. ? ? ? Merging polygons (3) • Take the polygons semantic into account • Evaluate a degree of similarity between semantics (semantic distance)

  29. identical different +  0 Merging polygons (4) Semantic distance to be defined by expert rules

  30. With rules 2 1 2 Without rules Semantic distance between neighbouring polygons Merging polygons (5)

  31. a a b b c c d d 2 a a - 1 a 2 b b 2 - d b c c 1 - c d d 2 - Merging polygons (6) Building a contingencytable from the semanticsof polygons

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