Recent trends in agricultural production of Africa based on AVHRR NDVI time series

African agriculture is expected to be hard-hit by ongoing climate change. Effects are heterogeneous within the continent, but in some regions resulting production declines have already impacted food security. Time series of remote sensing data allow us to examine where persistent changes occur. In this study, we propose to examine recent trends in agricultural production using 26 years of NDVI data. We use the 8-km resolution AVHRR NDVI 15-day composites of the GIMMS group (1981-2006). Temporal data-filtering is applied using an iterative Savitzky-Golay algorithm to remove noise in the time series. Except for some regions with persistent cloud cover, this filter produced smooth profiles. Subsequently two methods were used to extract phenology indicators from the profiles for each raster cell. These indicators include start of season, length of season, time of maximum NDVI, maximum NDVI, and cumulated NDVI over the season. Having extracted the indicators for every year, we aggregate them for agricultural areas at sub-national level using a crop mask. The aggregation was done to focus the analysis on agriculture, and allow future comparison with yield statistics. Trend analysis was performed for yearly aggregated indicators to assess where persistent change occurred during the 26-year period. Results show that the phenology extraction method chosen has an important influence on trend outcomes. Consistent trends suggest a rising yield trend for 500-1100 mm rainfall zones ranging from Senegal to Sudan. Negative yield trends are expected for the southern Atlantic coast of West Africa, and for western Tanzania.