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LAND COVER MAPPING OVER France USING S1-S10 VEGETATION DATASET J-L CHAMPEAUX, S. GARRIGUES

This workshop discusses the first results of land cover mapping in France using the S1-S10 vegetation dataset. The classification methodology includes unsupervised classification, principal component analysis, and confusion matrix analysis. The workshop highlights the challenges and improvements with the vegetation data and focuses on validation using the Corine Land Cover dataset.

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LAND COVER MAPPING OVER France USING S1-S10 VEGETATION DATASET J-L CHAMPEAUX, S. GARRIGUES

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  1. LAND COVER MAPPING OVER France USING S1-S10 VEGETATION DATASET J-L CHAMPEAUX, S. GARRIGUES METEO-FRANCE GLC 2000 – “FIRST RESULTS” WORKSHOP JRC – Ispra, 18-22 March 2002

  2. Climatic stratification of France (FIRS)

  3. Classification methodology: * First method Unsupervised classification (k-means) on annual temporal 10-days (MVC) NDVI profiles • * Second method • Selection of clear dates uniformly distributed during the year • Each pixel is defined: • Pi (B0J1,B2J1,B3J1,MIRJ1,… B0Jn,B2Jn,B3Jn,MIRJn) • Principal Component Analysis and selection of principal components the more explicative • Unsupervised classification (kmeans) on principal • components

  4. Confusion matrix between LC classification And Corine Land Cover used as reference Region « CENTRE » Urban Crops Pastu. BLFt MF Mix Urb+oth Urban Crops Pastures Forests Water 93.3 1.9 0.4 1.3 2. 2.1 39.8 4.2 87.5 31.7 20.2 4.7 49.1 41.0 0.3 4.3 63.2 7.5 2.8 23.3 4.8 0.4 5.2 4.5 70.4 87.7 24.5 10.3 1.6 0 0 0 1.9 0 1.7 Reliability: Urban 53%, Crops 74%, Pastures 70%, Forests 72%.

  5. Confusion matrix between LC classificationAnd Corine Land Cover used as reference for FRANCE Urban Crops Pastu. BLF CF MF Shrubs 64.4 2.2 0.6 0.9 0.7 0.7 0.4 19.4 81.3 20.2 17.9 3.8 8.7 7.2 3.4 9.0 71.0 8.8 2.9 11.2 21.1 2.9 5.6 4.3 71.6 89.2 74.9 18.0 2.3 0 0.1 0 0.9 0.2 1.2 2. 0 0.8 0.3 2.0 3.2 44.8 Urban Crops Pastures Forests Water Shrubs

  6. Problems …questions….ANSWERS (?) • Unsatisfactory detection of permanent crops • Unsatisfactory discrimination of coniferous and broad-leaved forests • Problem of detection of urban areas: Use of an urban mask (not up to date?) • Detection of water bodies Use of a water mask? • Discontinuities of land cover classes at the frontier of 2 different regions • How to treat mixed classes in nomenclature: pastures-crops, forests-crops-pastures

  7. Good accuracy with VEGETATION data some improvements were obtained with S1 channels (B2,B3,MIR) CONCLUSIONS • Some problems must be solved before running • the operational algorithm over France • VALIDATION: we have an updated Corine Land • Cover file (Spot, Landsat 1999) for • Provence-Alpes-Cote d’Azur region

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