Vol. 7, No. 1, 1-10, 2008

Abstract
Time-series of SPOT-VEGETATION S10 imagery for the African continent for the period January 2000 to December 2004 have been analysed. A region of interest has been extracted using the CROP-VGT software package for a Central African region (15°S - 15°N; 5°E - 35°E). Clouds and cloud shadows were masked using information from the associated Status Maps distributed with the S10 images. Hence, a set of cloud free annual composites was produced using the ENVI band math function, extracting the maximal Normalised Difference Vegetation Index (NDVI) value for 36 decadal syntheses for each year from 2000 to 2004. Subsequently, an unsupervised ISODATA classification with 11 classes was performed using annual NDVI composites. Finally, new vegetation maps for Central Africa were produced. An RGB-NDVI change detection strategy to detect and quantify major decreases or increases in green biomass - associated with forest harvest or regeneration - was developed as well and applied for the years 2000 till 2004. The NDVI analysis will - in the near future - be applied to study reflectance behaviour in single channels to obtain a better accuracy for our classification results. The use of the Red (B2) and Near-Infrared (B3) channels, for example, provides complementary information to make a distinction between bright soil with high reflectances in both the B3 and B2 bands and vegetation, where reflectance is low in the B2 band.

ISSN 1729-3782