Install
openclaw skills install @ruiduobao/geoskill-informal-settlement-detectionDetect informal settlements by fusing texture irregularity, building morphology and spectral mixing into a classification score.
openclaw skills install @ruiduobao/geoskill-informal-settlement-detectionDetects informal settlements (urban villages / shantytowns) by fusing texture irregularity, building density, and spectral mixing, serving urban renewal surveys and human settlement environment monitoring.
Core algorithm: quantifies texture disorder with the local standard deviation; combines building density with NDVI (low vegetation), weighted on an absolute physical scale to derive an informal score in [0, 1]; thresholding then extracts the informal settlements. High texture + high density + low NDVI → high score.
pip install 'numpy' 'rasterio' 'scipy'
python geoskill-informal-settlement-detection.py --bbox 116.0 39.0 117.0 40.0 [other arguments]
python geoskill-informal-settlement-detection.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out
python geoskill-informal-settlement-detection.py --input multispectral.tif --footprints fp.tif --output-dir ./out
python geoskill-informal-settlement-detection.py --bbox 121.0 31.0 122.0 32.0 --threshold 0.6 --output-dir ./out --quiet
python geoskill-informal-settlement-detection.py --input ms.tif --kernel-size 7 --output-dir ./out
python geoskill-informal-settlement-detection.py --bbox 116.0 39.0 117.0 40.0 --synthetic --threshold 0.4 --output-dir ./out --quiet
| File | Format | Description |
|---|---|---|
informal_score.tif | GeoTIFF | Two bands: band1 = informal score, band2 = classification mask |
informal_stats.json | JSON | Mean score, informal ratio, threshold |
output-manifest.json | JSON | Run manifest |
Local multispectral GeoTIFF (Red, NIR) + optional building footprints; --synthetic mode simulates a scene with half informal and half formal areas.
--synthetic mode is fully offline with no network access.MIT
融合纹理不规则性、建筑密度与光谱混合检测非正规聚居区(城中村/棚户区),服务于城市更新调查与人居环境监测。
核心算法:用局部标准差量化纹理无序度;结合建筑密度与 NDVI(低植被),以绝对物理标度加权得到非正规评分 [0,1],阈值分割出非正规聚居区。高纹理 + 高密度 + 低 NDVI → 高评分。
pip install 'numpy' 'rasterio' 'scipy'
python geoskill-informal-settlement-detection.py --bbox 116.0 39.0 117.0 40.0 [其他参数]
python geoskill-informal-settlement-detection.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out
python geoskill-informal-settlement-detection.py --input multispectral.tif --footprints fp.tif --output-dir ./out
python geoskill-informal-settlement-detection.py --bbox 121.0 31.0 122.0 32.0 --threshold 0.6 --output-dir ./out --quiet
python geoskill-informal-settlement-detection.py --input ms.tif --kernel-size 7 --output-dir ./out
python geoskill-informal-settlement-detection.py --bbox 116.0 39.0 117.0 40.0 --synthetic --threshold 0.4 --output-dir ./out --quiet
| 文件 | 格式 | 说明 |
|---|---|---|
informal_score.tif | GeoTIFF | 双波段:band1=非正规评分,band2=分类掩膜 |
informal_stats.json | JSON | 评分均值、非正规比例、阈值 |
output-manifest.json | JSON | 运行清单 |
本地多光谱 GeoTIFF(Red, NIR)+ 可选建筑足迹;--synthetic 模式模拟非正规区与正规区各半的场景。
--synthetic 模式完全无网络。MIT