The problem
Crop surveys are slow, and insurers and agencies lack an objective record of what was planted where and when. Manual verification does not scale to millions of plots.
What to build
Use freely available multispectral satellite imagery to detect field boundaries, classify the crop and estimate the sowing window for a district.
Success looks like
Field-level crop classification above 80% against ground-truth samples, with a map layer and an exportable report of confidence by plot.
Suggested technologies
- Sentinel-2
- Semantic segmentation
- Geospatial analytics
- Cloud-optimised GeoTIFF
- Open data
An original, independent statement. It is not an official Smart India Hackathon problem statement, and Arventiq Labs is not affiliated with or endorsed by that programme. The scenario is illustrative and does not describe any specific organisation. Free to use with credit.