Abstract: Problem statement: The Normalized Difference Vegetation Index (NDVI) is the most
extensively used satellite-derived index of vegetation health and density. Since climate is one of the
most important factors affecting vegetation condition, satellite-derived vegetation indexes have been
often used to evaluate climatic and environmental changes at regional and global scale. The proposed
study attempted to investigate the temporal vegetation dynamics in the whole Africa using historical
NDVI time-series. Approach: For this aim, 15 day maximum value NDVI composites at 8 km spatial
resolution produced from the NASA Global Inventory Mapping and Monitoring System (GIMMS) had
been used. They were derived from data collected daily by NOAA AVHRR satellites. The AVHRR
NDVI GIMMS dataset was freely available and gives global coverage over an extensive time period.
First of all, the selected NDVI base data had been geometrically pre-processed and organized into a
historical database implemented in order to grant their spatial integration. Starting from this archive,
monthly and yearly NDVI historical time-series, extended from 1982-2006, had been then developed
and analysed on a pixel basis. Several routines hade been developed in IDL (Interactive Data Language
programming tool) with the purpose of applying suitable statistical analysis techniques to the historical
information in the database in order to identify the long-term trend components of generated NDVI
time-series and extract vegetation dynamics. Specific tests had been then considered in order to define
the validity of results. Results: The existence of clear regional trends of NDVI, both decreasing and
increasing had been showed, which helped to highlight areas subject, respectively to reduction or
increase in vegetation greenness. Conclusion: As the relationship between the NDVI and vegetation
productivity was well established, these estimated long-term trend components may be also, with much
more caution, related to historical and ongoing land degradation or improvement processe