Mapping long-term changes in savannah crop productivity in Senegal through trend analysis of time series of remote sensing data

Abstract

Implementation of the United Nations Convention on Combating Desertification (CCD) requires an identification of areas where vegetative production is consistently declining. Time series of remote sensing data are well suited to this task, and methods have been developed for assessing long-term trends in savannah net primary production (NPP) or biomass and crop yields, using time series of NOAA AVHRR normalized difference vegetation index (NDVI) data. In this study, trend analysis is used to identify areas within the Peanut Basin in Senegal with apparent positive or negative trends in agricultural productivity. Having identified such areas, in-depth analysis is undertaken to determine whether long-term changes in agricultural productivity are mainly a function of rainfall patterns or are due to anthropogenic influences. The trends observed cannot be solely explained by rainfall data, and there seems to be a significant correlation with changes in land cover and land use. It is concluded that NDVI trend analysis may be used to investigate long-term and wide-scale environmental changes, and that by pinpointing areas of major change it can serve as a starting point for local-level analysis or action.