Frequent and accurate information on crop productivity and associated statistics are needed for a reliable food security policy and improved agriculture land use planning and extension. Traditional methods of gathering information using physical surveys are costly in terms of labor, time, effort, and resources. Manual agricultural monitoring generally can be inconsistent and erratic as well. The delivery of crop statistics by conventional methods is very slow, making the realistic utility of the data contentious for policy decisions. Also, it is not always possible to reach all the croplands. Hence, there is a need for an automated technology-based solution.