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name: forest-fire-burn-severity description: > Compute forest fire burn severity from pre/post-fire NIR and SWIR imagery using differenced Normalized Burn Ratio (dNBR). Classifies severity into unburned, low, moderate, and high categories. Use when the user wants to assess burn severity, map fire damage, or generate burn severity reports.

Forest Fire Burn Severity

Computes dNBR from pre/post-fire NIR+SWIR bands and classifies burn severity.

CLI Usage

python scripts/forest_fire_burn_severity.py \
  --pre-nir pre_nir.tif --pre-swir pre_swir.tif \
  --post-nir post_nir.tif --post-swir post_swir.tif

Or with synthetic demo data (no real inputs needed):

python scripts/forest_fire_burn_severity.py --synthetic

Parameters

Flag	Type	Required	Description
--pre-nir	path	one-of	Pre-fire NIR band GeoTIFF
--pre-swir	path	one-of	Pre-fire SWIR band GeoTIFF
--post-nir	path	one-of	Post-fire NIR band GeoTIFF
--post-swir	path	one-of	Post-fire SWIR band GeoTIFF
--synthetic	flag	one-of	Run with synthetic demo data (no real inputs needed)
--output-dir, -o	path	no	Output directory (default: burn-severity-output)
--version	flag	no	Show version and exit

Output

File	Description
report.html	Burn severity report
burn-severity-report.json	Detailed results
output-manifest.json	Machine-readable manifest

Exit Codes

Code	Meaning
0	Success
2	Argument error
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 forest_fire_burn_severity.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)。