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University of Reading (1994)

Vegetation and rainfall studies in Sahelian and Saharan Africa using satellite data

Bonifacio, Rogerio

Titre : Vegetation and rainfall studies in Sahelian and Saharan Africa using satellite data

Auteur : Bonifacio, Rogerio.

Université de soutenance : University of Reading

Grade : Doctor of Philosophy (Ph.D.) 1994

Résumé _ Satellite data are used routinely to monitor the growing season over the Sahelian zone of Africa. This study brings together rainfall estimates and a vegetation index (NDVI) both derived from meteorological satellites, with the data covering five years of study - 1986 to 1990.The theoretical, empirical and practical background on the derivation and use of vegetation indices and rainfall estimates is reviewed. The timing of the growing season in Sahelian Africa and its spatial pattern is analysed and the information used to derive indicators of biomass production.Plant water use was calculated from a simple water balance model that takes into account the timing and distribution of rainfall and the vegetation seasonal development. Characterisation of the study area in terms of mean estimated rainfall, water use, production and efficiencies in the use of rainfall is achieved from the model output.The dynamics of the seasonal development of vegetation in relation to the availability of water were analysed by mapping the interval between assumed water availability and vegetation development. The within season time lag between plant water use and NDVI was also analysed. Operational forecasts of beginning of growing season are possible from the rainfall estimates alone.A simple model for end of season production is developed and validated for a test year. The parameters of this model vary in space to account for variations in the region’s characteristics.Finally, the difficulties in the use of NDVI in very arid climates is demonstrated with a data set for the Algerian Sahara. Variations with changes in viewing conditions were found to be important compared to the seasonal range. Soil effects leading to high NDVI values over bare soil were identified and a way to discriminate sparse vegetation using additional information from the AVHRR mid infrared channel (3) is proposed.

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