This document summarizes a study that assessed drought risk using remote sensing and GIS. Satellite-derived NDVI data and ground-based precipitation data were analyzed over a 10-year period. Correlations between NDVI, standardized precipitation index (SPI), rainfall anomaly, and food grain anomaly were performed. Results showed SPI can indicate regional crop production. NDVI, SPI, and detrended food grain yield anomaly were linearly correlated, indicating they can efficiently monitor and evaluate food grain output. Different data sources were analyzed spatially and temporally to classify drought risk into very high, high, moderate, slight, and no risk categories based on regression analyses between precipitation, NDVI, and crop yields. The integrated approach aimed to properly deline