Analysis of GAC NDVI Data for Cropland Identification and Yield Forecasting in Mediterranean African Countries

The utilization of NOAA-AVHRR NDVI data for crop yield forecasting is of particular importance in semiarid regions where there are strong inter-year yield fluctuations due to meteorological vagaries. The present work deals with the use of monthly GAC NDVI data for the early estimation of cereal crop yield in Mediterranean African countries. A preliminary analysis showed that relatively high correlations were present between crop yield and mean NDvI values of specific months computed at national levels. The stratification of the countries according to the ~ S G S global land-cover map brought only marginal correlation increases. Greater improvements were instead reached by a statistical method which allows the estimation of the per-pixel fractions of agricultural and nonagricultural vegetation. When compared to available independent maps, the areas identified in this way were confirmed to be mainly covered by crop and forest land, respectively The methodology for cropland identification and yield forecasting was finally evaluated for operational applications.