雪崩易发性评估 | Snow Avalanche Susceptibility
Snow avalanche susceptibility is assessed by fusing terrain and snow/meteorological factors: a slope factor (Gaussian-shaped, peaking at ~38°, with 30–45° being the high-risk range), an aspect factor (higher on north-facing leeward slopes in the Northern Hemisphere), terrain roughness (smoother surfaces are more susceptible), snow depth (saturating increase), and temperature (wet snow near 0 °C is the most unstable). Each factor is normalized to [0,1], then combined by weighted sum into a susceptibility index, which is subsequently classified into levels.
Dependencies / 依赖
pip install numpy rasterio scipy
Usage / 使用方法
Basic Usage (Synthetic Data, Offline)
python geoskill-snow-avalanche-susceptibility.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out
More Examples
python geoskill-snow-avalanche-susceptibility.py --bbox 90 30 91 31 --synthetic --output-dir ./out
python geoskill-snow-avalanche-susceptibility.py --input terrain.tif --output-dir ./out
python geoskill-snow-avalanche-susceptibility.py --bbox 90 30 91 31 --roughness 0.5 --synthetic --output-dir ./out
python geoskill-snow-avalanche-susceptibility.py --bbox 91 30 92 31 --synthetic --quiet --output-dir ./out
Output / 输出
| File | Format | Description |
|---|---|---|
susceptibility.tif |
GeoTIFF | Avalanche susceptibility index [0,1] |
susceptibility_level.tif |
GeoTIFF | Susceptibility level (0 low – 3 extremely high) |
avalanche_params.json |
JSON | Factor weights |
Each run also produces output-manifest.json (a run manifest containing input, outputs, and a QA summary).
Data Source / 数据源 / Source
Real mode reads a multi-band GeoTIFF (band1 = slope°, band2 = aspect°, band3 = snow depth m, band4 = temperature °C); synthetic mode generates a mountain scene 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-snow-avalanche-susceptibility description: '坡度坡向地形粗糙度叠加积雪与温度的雪崩易发性评估'
雪崩易发性评估 | Snow Avalanche Susceptibility
融合地形与积雪/气象因子评估雪崩易发性:坡度因子(高斯型,峰值 ~38°,30–45° 高发)、坡向因子(北半球偏北背风坡更高)、地形粗糙度(越光滑越易发)、积雪深度(饱和递增)与温度(接近 0°C 湿雪最不稳定)。各因子归一到 [0,1] 后加权求和得易发性指数,再分级。
依赖
pip install numpy rasterio scipy
使用方法
基本用法(合成数据,离线)
python geoskill-snow-avalanche-susceptibility.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out
更多示例
python geoskill-snow-avalanche-susceptibility.py --bbox 90 30 91 31 --synthetic --output-dir ./out
python geoskill-snow-avalanche-susceptibility.py --input terrain.tif --output-dir ./out
python geoskill-snow-avalanche-susceptibility.py --bbox 90 30 91 31 --roughness 0.5 --synthetic --output-dir ./out
python geoskill-snow-avalanche-susceptibility.py --bbox 91 30 92 31 --synthetic --quiet --output-dir ./out
输出
| 文件 | 格式 | 说明 |
|---|---|---|
susceptibility.tif |
GeoTIFF | 雪崩易发性指数 [0,1] |
susceptibility_level.tif |
GeoTIFF | 易发性分级(0低-3极高) |
avalanche_params.json |
JSON | 因子权重 |
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=坡度°、band2=坡向°、band3=雪深m、band4=温度°C);合成模式离线生成山地场景。
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
