灾后重建遥感监测 | Post-Disaster Reconstruction Monitoring

Monitors reconstruction progress using a building-intensity proxy derived from multi-temporal high-resolution imagery: comparing the pre-disaster / damaged / reconstruction epochs, each pixel is classified (mutually exclusively) into one of five classes — non_building / unchanged / destroyed / under_construction / rebuilt. The recovery progress of a destroyed pixel is clip((R-D)/(B-D), 0, 1), which increases monotonically with the reconstruction-epoch intensity; the higher the reconstruction level, the more rebuilt pixels.

Dependencies / 依赖

pip install numpy rasterio scipy

Usage / 使用方法

Basic usage (synthetic data, offline)

python geoskill-post-disaster-reconstruction.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out

More examples

python geoskill-post-disaster-reconstruction.py --bbox 116 39 117 40 --synthetic --output-dir ./out
python geoskill-post-disaster-reconstruction.py --input series.tif --output-dir ./out
python geoskill-post-disaster-reconstruction.py --bbox 116 39 117 40 --recovery 0.9 --synthetic --output-dir ./out
python geoskill-post-disaster-reconstruction.py --bbox 117 39 118 40 --synthetic --quiet --output-dir ./out

Output / 输出

Each run also produces output-manifest.json (run manifest with inputs/outputs/QA summary).

Data Source / 数据源 / Source

Real mode reads a multi-band GeoTIFF (band1 = pre-disaster, band2 = damaged, band3 = reconstruction-epoch building intensity); synthetic mode generates the three-epoch scenes offline (recovery level adjustable).

Privacy / 隐私声明 / Privacy

• Runs offline by default; --synthetic mode requires no network at all.
• All processing is performed locally; no user data is ever uploaded.

License / License

MIT

name: geoskill-post-disaster-reconstruction description: '多期高分辨率影像建筑变化与重建进度分类'

灾后重建遥感监测 | Post-Disaster Reconstruction Monitoring

用多期高分辨率影像的建筑强度代理监测重建进度：对比灾前/损毁期/重建期三期，逐像元分为 non_building / unchanged / destroyed / under_construction / rebuilt 五类（互斥）。毁坏像元恢复进度 = clip((R-D)/(B-D),0,1)，随重建期强度单调增，重建程度越高 rebuilt 像元越多。

依赖

pip install numpy rasterio scipy

使用方法

基本用法（合成数据，离线）

python geoskill-post-disaster-reconstruction.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out

更多示例

python geoskill-post-disaster-reconstruction.py --bbox 116 39 117 40 --synthetic --output-dir ./out
python geoskill-post-disaster-reconstruction.py --input series.tif --output-dir ./out
python geoskill-post-disaster-reconstruction.py --bbox 116 39 117 40 --recovery 0.9 --synthetic --output-dir ./out
python geoskill-post-disaster-reconstruction.py --bbox 117 39 118 40 --synthetic --quiet --output-dir ./out

输出

每次运行还会产出 output-manifest.json（运行清单，含输入/产物/QA 摘要）。

数据源 / Source

真实模式读取多波段 GeoTIFF（band1=灾前、band2=损毁期、band3=重建期建筑强度）；合成模式离线生成三期场景（恢复程度可调）。

隐私声明 / Privacy

• 默认离线运行，--synthetic 模式完全无网络。
• 所有处理在本地完成，不上传任何用户数据。

License

MIT