Long term observation of space-borne remote sensing data provides a means to explore temporal variation on the Earth`s surface. This improved understanding of variability is required by numerous global change studies to explain annual and inter-annual trends and to separate those from individual events. This knowledge also can be included into budgeting and modeling for global change studies. The study employs daily 8 km NOAA-AVHRR data of the Pathfinder program to study changes in the annual variability of vegetation in Sudan, during the time period from 1982 to 1993. The daily data were processed to improve 15 day composites using an iterative approach including metadata and robust statistical techniques. This study employs GIS to examine the relationship between rainfall and the Normalized Difference Vegetation Index (NDVI) in the context of the Sudan and the value of NDVI is taken as a tool for drought monitoring. The relationship between rainfall and NDVI during 1982 and 1993 in Sudan is examined using spatial analysis methods and a strong positive correlation is found. The correlation is strongest during years of heaviest rainfall, indicating that the relationship between rainfall and NDVI is not a simple linear one. However it is argued that the input data accuracy has affected the quality of the GIS output and the shortcomings of the data are highlighted. The study stresses the need for the use of remote sensing to provide real time data for forecasting. Whilst most countries in the Sahel including Sudan lack the resources (financial, technical and human) to establish the information systems necessary for drought monitoring, this study concludes that remote sensing is the only feasible data source to fill such a gap. NDVI is a valuable first cut indicator for such systems, although analyzing and interpreting its relationship to rainfall is complex and must be based on detailed analysis of its relationship to ecological zone, vegetation type and season.