Geoskill: Agricultural Disaster Assessment

Fuses crop distribution, hazard intensity, and NDVI anomaly to estimate agricultural disaster impact. Classifies damage severity (mild/moderate/severe) and generates field-level da…

ruiduobao

@ruiduobao

Install

$ openclaw skills install @ruiduobao/geoskill-agricultural-disaster-assessment

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

ParameterDefaultDescription
--crop-maprequiredCrop distribution raster (1=crop)
--hazard-rasterrequiredHazard intensity (flood depth, SPI, etc.)
--baseline-ndvirequiredNormal-year NDVI
--post-ndvirequiredPost-disaster NDVI
--hazard-threshold0.3Hazard intensity threshold
--anomaly-threshold-0.3NDVI anomaly threshold
--min-area0Minimum field area filter
--output-dir./disaster-outputOutput directory

Output

FileDescription
affected_crops.tifDamage level raster (0-4)
field_damage.geojsonDamaged field polygons
report.htmlHTML summary report
output-manifest.jsonMachine-readable manifest

Damage Levels

LevelLabelMeaning
0no cropNot a crop pixel
1no damageHazard below threshold
2mildSlight NDVI reduction
3moderateSignificant NDVI reduction
4severeMajor NDVI reduction + high hazard

Exit Codes

CodeMeaning
0Success
2Argument error
3Dependency missing
6Data validation failure
7Processing 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 <tmp>
  • --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 <path.geojson>: 替代 --bbox 的 GeoJSON 多边形
  • --cache-dir <path>: 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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