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GLC 2000 – South America map Presented by H.Eva E. E. de Miranda C. di Bella

GLC 2000 – South America map Presented by H.Eva E. E. de Miranda C. di Bella V. Gond O.Huber S.Jones. Contributing Institutions. Logistical Approach. 1/. Centralised processing 2/. First-pass class labels 3/. Regional expert assessment of classes – re-labeling

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GLC 2000 – South America map Presented by H.Eva E. E. de Miranda C. di Bella

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  1. GLC 2000 – South America map Presented by H.Eva E. E. de Miranda C. di Bella V. Gond O.Huber S.Jones

  2. Contributing Institutions

  3. Logistical Approach 1/. Centralised processing 2/. First-pass class labels 3/. Regional expert assessment of classes – re-labeling 4/. Class rationalisation 5/. Integration of specialist areas for regional product

  4. 1/. Centralised processing –the data set Creation of seasonal mosaics from S10 product Jan-Mar Apr-Jun July-Sept Oct-Dec Image selection on lowest SWIR Cloud Screening

  5. Combining of VGT seasonal images • Masking of evergreen forest (use of TREES 2000) • Unsupervised clustering to 50 classes

  6. 2/. First pass class labeling • Semi- evergreen forest • Dry forest • Shrubs (dense / sparse) • Savannah with shrubs • Savannah • Sparse grasslands • Agriculture • Barren

  7. Class labeling • Spectral signature • Texture and context • NDVI profile • Existing land cover maps and ancillary data

  8. Major Problems • Cloud shadow in forest areas and Andes • Seasonal aspects not directly related to the land cover – snow / flooding / burning • Main spectral ambiguity – grasslands / agriculture • Urban areas not easy to descriminate

  9. NE Brazil Caatingas Andes transect Southern Brazil Argentina from Monte to Steppe Magellan grasslands Main problem areas – V1.1

  10. Venezuela Brazil Southern Cone Amazon forest 3/. Regional Experts working on data

  11. Universidad Mayor de San Andrés Regional Experts helping with validation

  12. 4/. Integration of specialist areas for regional product • Whilst all of South America is completed to the mimimum GLC 2000 legend – some areas/land cover types will have more detailed products • NE Brazil • -Swamp forests (JERS-1 data) • -Bamboo dominated forests (Acre / Peru)

  13. Class rationalisation with other tropical regions

  14. Intercontinental comparisons of vegetation dynamic from NDVI- derived parameters for each map class -maximum NDVI -adjusted minimum NDVI -range of NDVI -rates of change of NDVI -integrated NDVI -parameters of seasonality (fit of seasonally adjusted curves)

  15. NDVI maximum monthly image – allowing intercontinental comparisons

  16. Current Status • first draft map has been created • Errors due to spectral confusion • Lack of adequate knowledge of certain cover types • NE Brazil should be ratified with EMBRAPA by the end of March • - A final “draft” for July / August

  17. Final Comment Importance of the Global Legend Importance of the Regional Legends and the partnerships with national experts worldwide

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