Agroclimatic & weather analytics
Hyperlocal weather history, in-season conditions, and agroclimatic risk indicators — the climate layer under every cropping decision, available for any admin unit or custom boundary.
- Village-level granularity
- Historical archives
- Drought & risk indices
Benefits
What agroclimatic & weather analytics unlocks
Short-term optimization
- Hyperlocal rainfall and temperature context on demand
- In-season risk flags for heat, dry spells, and excess rain
- Consistent indices across all monitored regions
Long-term impact
- Climate-trend baselines for planning and underwriting
- Parametric-product design support
- Better siting and crop-choice decisions
Approach & methodology
How the analytics work
We are transparent about data sources, models, and limits — so you can trust what you act on.
- Data sources
- Satellite-derived precipitation, temperature, and soil-moisture products with multi-year archives.
- Approach
- Aggregation to admin units or custom boundaries; standard agroclimatic indices (SPI-family, dry spells).
- Update cadence
- Daily-to-weekly updates depending on indicator.
- Limitations
- Satellite weather products are estimates; complex terrain increases local uncertainty.
Deliverables
Expected outputs
- GIS-ready data layers (GeoJSON / KML / SHP / GeoTIFF)
- Decision-ready PDF report with interpretation
- Interactive smart map with time-series view
Process
Project stages
1–3 weeks to first dashboard
Define area of interest and indicators with your team
Acquire and process multi-date satellite imagery
Run analytics models and validate outputs
Deliver layers, maps, and report; set up recurring monitoring