干旱脆弱性指数 | Drought Vulnerability Index
Fuses three components based on the IPCC vulnerability framework: exposure (meteorological drought), sensitivity (crops/population), and adaptive capacity (irrigation/economy). Vulnerability V = (w_E·E' + w_S·S' + w_A·(1-A'))/Σw, with each component normalized to [0,1]. V increases monotonically with exposure/sensitivity and decreases monotonically with adaptive capacity; E=S=0, A=1 → V=0, and E=S=1, A=0 → V=1.
Dependencies / 依赖
pip install numpy rasterio scipy
Usage / 使用方法
Basic usage (synthetic data, offline)
python geoskill-drought-vulnerability-index.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out
More examples
python geoskill-drought-vulnerability-index.py --bbox 110 35 111 36 --synthetic --output-dir ./out
python geoskill-drought-vulnerability-index.py --input region.tif --output-dir ./out
python geoskill-drought-vulnerability-index.py --bbox 110 35 111 36 --synthetic --quiet --output-dir ./out
python geoskill-drought-vulnerability-index.py --bbox 113 40 114 41 --synthetic --output-dir ./out
Output / 输出
| File | Format | Description |
|---|---|---|
vulnerability.tif |
GeoTIFF | Drought vulnerability index [0,1] |
vulnerability_level.tif |
GeoTIFF | Vulnerability grade (0 low – 3 severe) |
drought_params.json |
JSON | Method description |
Each run also produces output-manifest.json (run manifest, including input/output/QA summary).
Data Source / 数据源 / Source
Real mode reads a multi-band GeoTIFF (band1=exposure, band2=sensitivity, band3=adaptive capacity); synthetic mode generates a scenario offline.
Privacy / 隐私声明 / Privacy
- Runs offline by default;
--syntheticmode requires no network at all. - All processing is done locally; no user data is uploaded.
License / License
MIT
name: geoskill-drought-vulnerability-index description: '暴露敏感性与适应能力三分量归一化干旱脆弱性评估'
干旱脆弱性指数 | Drought Vulnerability Index
基于 IPCC 脆弱性框架融合三分量:暴露度(气象干旱)、敏感性(作物/人口)、适应能力(灌溉/经济)。脆弱性 V = (w_E·E' + w_S·S' + w_A·(1-A'))/Σw,各分量归一化到 [0,1]。V 对暴露度/敏感性单调递增、对适应能力单调递减;E=S=0,A=1 → V=0,E=S=1,A=0 → V=1。
依赖
pip install numpy rasterio scipy
使用方法
基本用法(合成数据,离线)
python geoskill-drought-vulnerability-index.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out
更多示例
python geoskill-drought-vulnerability-index.py --bbox 110 35 111 36 --synthetic --output-dir ./out
python geoskill-drought-vulnerability-index.py --input region.tif --output-dir ./out
python geoskill-drought-vulnerability-index.py --bbox 110 35 111 36 --synthetic --quiet --output-dir ./out
python geoskill-drought-vulnerability-index.py --bbox 113 40 114 41 --synthetic --output-dir ./out
输出
| 文件 | 格式 | 说明 |
|---|---|---|
vulnerability.tif |
GeoTIFF | 干旱脆弱性指数 [0,1] |
vulnerability_level.tif |
GeoTIFF | 脆弱性分级(0低-3严重) |
drought_params.json |
JSON | 方法说明 |
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=暴露度、band2=敏感性、band3=适应能力);合成模式离线生成场景。
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
