UAV Farm Health Index Map Generation

Problem

After UAV field scouting, farm imagery often remains as individual orthophotos, mosaics, or short videos. Manual review is slow and makes it hard to quantify early stress zones related to nutrient deficiency, water stress, pests, disease, or weeds. This skill turns that workflow into a repeatable analysis pipeline: provide imagery or video, and receive crop health distribution plus problem-zone extent.

How It Works

The skill is designed for multispectral or high-resolution RGB data captured by agricultural UAVs. It processes the input with built-in scripts, computes vegetation indices, and renders a farm health-index heatmap. Core capabilities include:
- Imaging support: accepts jpg/png/tiff images or mp4/avi/mov videos, up to 10MB;
- Index calculation: covers NDVI, NDRE, OSAVI, GNDVI, VARI, and ExG;
- Result output: uses red, yellow, and green to separate low, medium, and high health, and reports anomaly polygons, area estimates, and crop coverage statistics;
- History lookup: uses --list to query cloud-hosted report lists for past scouting and monitoring records.

Limits

The output is best treated as a management reference and should be confirmed with field inspection. Multispectral imagery must include an NIR band to compute NDVI or NDRE; pure RGB falls back to VARI or ExG. Historical reports are read only from cloud APIs, not from local memory or manual summaries.