Crop Condition Monitor
Assess crop health from NDVI time series.
CLI Usage
python scripts/crop_condition_monitor.py --ndvi ndvi1.tif ndvi2.tif ndvi3.tif
python scripts/crop_condition_monitor.py --ndvi ndvi1.tif ndvi2.tif --dates 2024-04-01,2024-05-01
python scripts/crop_condition_monitor.py --ndvi ndvi1.tif ndvi2.tif --output-dir my_output
Parameters
| Argument | Required | Default | Description |
|---|---|---|---|
--ndvi |
Yes | — | One or more NDVI rasters (chronological order, same grid) |
--dates |
No | — | Optional comma-separated acquisition dates matching --ndvi files (ISO YYYY-MM-DD) |
--output-dir, -o |
No | crop-output |
Directory to write outputs |
Output
| File | Description |
|---|---|
crop-report.json |
Machine-readable crop condition stats (mean NDVI, anomaly area) |
report.html |
Human-readable HTML report |
output-manifest.json |
Run metadata + result summary |
Exit Codes
| Code | Meaning |
|---|---|
| 0 | Success |
| 2 | Argument error |
| 7 | Processing failure |
Data Download
When --bbox (or --aoi-file) and --date-range are provided, this skill
auto-downloads a small set of Sentinel-2 L2A (sentinel-2-l2a) visual
previews from the Microsoft Planetary Computer STAC catalog (no API key
required) and uses them as the multi-temporal NDVI stack.
The downloaded files are written to <output_dir>/downloaded/ and the
downstream monitor_crop analysis runs on them. The output-manifest.json
records data_source / collection / bbox / date_range / fetched_at for
traceability.
python scripts/crop_condition_monitor.py \
--bbox 116.4,39.6,116.6,39.8 \
--date-range 2024-06-01,2024-06-30 \
--output-dir my_output