DEVELOPING SIMPLE, OPERATIONAL, CONSISTENT NDVI-VEGETATION MODELS BY APPLYING ENVIRONMENTAL AND CLIMATIC INFORMATION - PART II - CROP YIELDASSESSMENT

Millet yield can consistently be assessed using AVHRR NDVI data. Two y ears of data showed that one linear regression line between grain yiel d and integrated NDVI could be statistically justified. Adding environ mental information and using multiple regression techniques improved t he yield model further. The agricultural domain was stratified into in tensive and extensive cultivated land. By adding the environmental var iable of livestock density to the millet yield-integrated NDVI model, the level of explained yield variance was improved to 88 per cent for the intensively cultivated area. For the rest of the agricultural doma in, the variable percentage cultivated land was included to the yield- integrated NDVI model explaining altogether 76 per cent of the yield v ariance. GIS spatial interpolation tools were used to generated surfac es of per cent cultivated land and livestock density from point observ ations. The use of Photosynthetically Active Radiation (PAR) data alon g with NDVI to assess millet grain yield or total crop biomass, was fo und to be of limited use since no single regression line valid for bot h years could be established and the level of explained variance was r educed compared with using the NDVI alone.