A vegetation map of the Central Congo basin was derived from observations performed by several imaging orbital instruments. These are the synthetic aperture radars on board the ESA ERS and the NASDA JERS-1 satellites (C-band and L-band), and the imaging spectrometer VEGETATION on board SPOT 4. The different properties of the composite microwave and optical observations are exploited in a complementary way to achieve the intended thematic goal. In particular the secondary forest formation that cannot be mapped consistently by the radar instruments, is captured by the optical observations. Information fusion is achieved at the level of the classification maps derived independently from the microwave and the optical instruments. The derived classification product is a data structure (dubbed VARMAP) composed of elementary variable size cells holding class labels. The VARMAP supports the generation of thematic products at different scales according to the end use. The paper touches upon some of the challenging issues that arise in the compilation of wide area multi-resolution thematic products, with emphasis on the classification methodology and in particular on novel non-contextual and contextual clustering techniques. The thematic products cover an area of approximately 576 million square kilometres, while keeping a resolution of 200 m for most of the thematic classes. It constitutes therefore an invaluable source of ecological information both for global change studies and for the sustainable management of local resources.
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