Geoskill: Water Quality Remote Sensing

Estimate water quality parameters from multispectral satellite imagery using red and green bands, optionally NIR/SWIR, for analysis and report generation.

ruiduobao

@ruiduobao

Install

$ openclaw skills install @ruiduobao/geoskill-water-quality-remote-sensing

Prerequisites / 先准备 X 文件

⚠️ 必读 — 本 skill 不属于即用型,需要先准备特定文件才能跑。

本 skill 需要 红光 + 绿光两个波段栅格(GeoTIFF)。NIR/SWIR 可选。

👉 完整教程见仓库根目录 PREREQUISITES.md 1.8 节。

先准备 X 文件:从 Sentinel-2 提取 2-4 个波段,或 --bbox 让 skill 自动下载。

快速试跑命令:

python water_quality_remote_sensing.py --bbox 116,39,117,40 --date-range 2024-06-01,2024-06-30 --output-dir ./wq

--- name: water-quality-remote-sensing description: > Estimate water quality parameters from multispectral satellite imagery. Use when the user wants to analyze changes, compare multi-temporal rasters, compute indices, or generate assessment reports.

Water Quality Remote Sensing

Estimate water quality parameters from multispectral satellite imagery.

CLI Usage

python scripts/water_quality_remote_sensing.py --red red.tif --green green.tif
python scripts/water_quality_remote_sensing.py --red red.tif --green green.tif --nir nir.tif --swir swir.tif
python scripts/water_quality_remote_sensing.py --red red.tif --green green.tif --output-dir my_output

Parameters

ArgumentRequiredDefaultDescription
--redYesPath to red band raster (≈ 0.6–0.7 μm)
--greenYesPath to green band raster (≈ 0.5–0.6 μm)
--nirNoOptional NIR band raster (≈ 0.8–0.9 μm, enables NDWI / NDVI-based products)
--swirNoOptional SWIR band raster (≈ 1.6–2.2 μm, enables turbidity proxies)
--output-dir, -oNowater-quality-outputDirectory to write outputs

Output

FileDescription
water-quality-report.jsonMachine-readable water quality indices
report.htmlHuman-readable HTML report
output-manifest.jsonRun metadata + result summary

Exit Codes

CodeMeaning
0Success
2Argument error (e.g. missing input file)
7Processing failure

数据下载

本 skill 可自动从 Microsoft Planetary Computer 下载数据 (无需 API key):

python water_quality_remote_sensing.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 --red) 时,skill 自动下载数据。 当用户给 --red 时,走原文件路径 (向后兼容)。

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