Crop health monitoring
Continuous crop-condition intelligence built on vegetation indices and time-series analysis. Monitor any boundary — from a single field to a district — with consistent, comparable indicators across the season.
- Field-to-district scale
- Updated through the season
- Custom boundaries supported
Benefits
What crop health monitoring unlocks
Short-term optimization
- Detect crop stress weeks before it is visible on the ground
- Prioritize field visits where indicators flag problems
- Verify insured or financed acreage remotely
Long-term impact
- Season-on-season performance baselines per region
- Lower loss ratios through earlier intervention
- A defensible evidence trail for claims and audits
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
- Multispectral optical satellite imagery (10 m class), with historical archives for baselines.
- Approach
- Vegetation index time-series (NDVI-family) with crop-calendar-aware anomaly detection.
- Update cadence
- Refreshed with each usable satellite pass; cloud-affected dates flagged.
- Limitations
- Persistent cloud cover reduces optical revisit; very small plots (<0.5 ha) carry mixed-pixel noise.
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
2–4 weeks to first delivery
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