The recent technological and computational advancements in the information and geospatial technology areas are finding new scope of application in the areas of agriculture, especially in the fields of crop management, Agriculture commodity markets, food pricing and food security.

This approach consists of data integration of spatial and topographic, remote sensing, historical weather patterns, weather forecasts, historical cropping patters, soil maps, ground water data and previous crop yields. Followed by developing computational model or an algorithm which establishes the relationship between the weather patterns, soil conditions and crop yields and predict yields with a certain accuracy and The developed algorithms are now be trained and tested over a large set of integrated historical spatial, weather and soil data, which will help validate the relationship between weather patterns, soil conditions and crop yields, and fine tune the algorithm to predict the crop yield with higher degree of accuracy.