Demand Estimation for Agricultural Inputs
Accurately estimating the demand and requirement for seeds, fertilizers, and agriculture equipment requires granular data on crop health, crop variety, crop acreage that is ground verified. However, this data is difficult to collect and verify. It is also labor and cost intensive to collect such micro level quantitative data on a macro scale.
Our image processing experts employed satellite imagery captured using different sensors to assess crop health, crop variety, crop patterns, and crop acreage. This was quantified to generate reports. In conjunction to crop assessment, we also quantified factors that affect crops such as rainfall, temperature, soil, and wind. Combining crop data with environmental data, we were able to conduct irrigation potential analysis, land use land cover analysis, change detection analysis, and post event (extreme weather) analysis in order to understand demand. Finally, we defined catchment and serviceability areas for agriculture equipment providers and field advisory teams to understand connectivity and accessibility to remote farms with respect to demand.
Remote sensing and geospatial analysis of farms reduced monitoring costs and loss due to negligence. Farmers had a better idea of their fields in terms of cultivable area and irrigation potential. The accessibility index and catchment analysis for agriculture equipment providers revealed insights on demand to optimize supply chain.
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