Assess crop health from NDVI time series. Use when the user wants to analyze changes, detect hazards, or generate assessment reports.
1 installs
Coding
Geoskill: Agricultural Disaster Assessment
Try itFuses crop distribution, hazard intensity, and NDVI anomaly to estimate agricultural disaster impact. Classifies damage severity (mild/moderate/severe) and generates field-level damage maps. Use when assessing flood/drought/heat impact on crops.
What it does
Fuses crop distribution, hazard intensity, and NDVI anomaly to estimate agricultural disaster impact. Classifies damage severity (mild/moderate/severe) and generates field-level damage maps. Use when assessing flood/drought/heat impact on crops.
The skill document
Agricultural Disaster Assessment
Estimates crop damage by combining hazard intensity with vegetation anomaly.
Trigger
Use when the user wants to:
- Assess flood/drought/heat impact on crops
- Map agricultural disaster severity
- Generate field-level damage estimates
- Prioritize inspection areas after a disaster
CLI Usage
# Basic assessment
python scripts/agricultural_disaster_assessment.py \
--crop-map crops.tif \
--hazard-raster flood_depth.tif \
--baseline-ndvi ndvi_normal.tif \
--post-ndvi ndvi_post.tif
# With custom thresholds
python scripts/agricultural_disaster_assessment.py \
--crop-map crops.tif \
--hazard-raster drought_spi.tif \
--baseline-ndvi ndvi_normal.tif \
--post-ndvi ndvi_post.tif \
--hazard-threshold 0.5 --anomaly-threshold -0.4
Parameters
| Parameter | Default | Description |
|---|---|---|
--crop-map | required | Crop distribution raster (1=crop) |
--hazard-raster | required | Hazard intensity (flood depth, SPI, etc.) |
--baseline-ndvi | required | Normal-year NDVI |
--post-ndvi | required | Post-disaster NDVI |
--hazard-threshold | 0.3 | Hazard intensity threshold |
--anomaly-threshold | -0.3 | NDVI anomaly threshold |
--min-area | 0 | Minimum field area filter |
--output-dir | ./disaster-output | Output directory |
Output
| File | Description |
|---|---|
affected_crops.tif | Damage level raster (0-4) |
field_damage.geojson | Damaged field polygons |
report.html | HTML summary report |
output-manifest.json | Machine-readable manifest |
Damage Levels
| Level | Label | Meaning |
|---|---|---|
| 0 | no crop | Not a crop pixel |
| 1 | no damage | Hazard below threshold |
| 2 | mild | Slight NDVI reduction |
| 3 | moderate | Significant NDVI reduction |
| 4 | severe | Major NDVI reduction + high hazard |
Exit Codes
| Code | Meaning |
|---|---|
| 0 | Success |
| 2 | Argument error |
| 3 | Dependency missing |
| 6 | Data validation failure |
| 7 | Processing failure |
数据下载
本 skill 可自动从 Microsoft Planetary Computer 下载数据 (无需 API key):
python agricultural_disaster_assessment.py --bbox 116,39,117,40 --date-range 2024-06-01,2024-06-30 --output-dir
--bbox W,S,E,N: WGS-84 边界框 (西, 南, 东, 北)--date-range START,END: 日期范围 (YYYY-MM-DD,YYYY-MM-DD)--aoi-file: 替代 --bbox 的 GeoJSON 多边形--cache-dir: 缓存目录 (默认 ~/.geoskill_cache)
当用户只给 --bbox + --date-range (没有 --image) 时，skill 自动下载数据。
当用户给 --image 时，走原文件路径 (向后兼容)。
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