geoskill-snow-avalanche-susceptibility

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

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

bash

pip install numpy rasterio scipy

Usage / 使用方法

Basic Usage (Synthetic Data, Offline)

bash

python geoskill-snow-avalanche-susceptibility.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out

More Examples

bash

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; --synthetic mode 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

bash

pip install numpy rasterio scipy

使用方法

基本用法（合成数据，离线）

bash

python geoskill-snow-avalanche-susceptibility.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out

更多示例

bash

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