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 damage maps. Use when assessing flood/drought/heat impact on crops.

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

bash

# 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):

bash

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)。