用当量因子法评估供给、调节、支持、文化四类生态系统服务价值。Estimates four ecosystem service values with a simplified InVEST plus equivalent-factor method. 输出四类服务价值 GeoTIFF 与总量 JSON。
编程
geoskill-environmental-impact-assessment
试用多压力因子归一化加权叠加得综合影响指数，独立概率模型估算累积效应，按阈值划分5 级影响等级。Assesses environmental impact grades by multi-factor overlay and cumulative effects. 输出影响指数与等级 GeoTIFF。
它能做什么
多压力因子归一化加权叠加得综合影响指数，独立概率模型估算累积效应，按阈值划分5 级影响等级。Assesses environmental impact grades by multi-factor overlay and cumulative effects. 输出影响指数与等级 GeoTIFF。
技能文档
环境影响评价 | Environmental Impact Assessment
Four pressure factors (pollution, land-use change, noise, and habitat fragmentation) are each min-max normalized and combined by weighted overlay using sensitivity weights (0.30/0.25/0.25/0.20); cumulative effects are estimated with the independent-probability model C = 1 − Π(1 − Ii), ensuring that the multi-project superposition does not exceed 1 and is ≥ any single project; the final index = 0.5 × weighted overlay + 0.5 × cumulative effect, classified by thresholds of 0.1/0.3/0.5/0.7 into five grades: negligible/slight/moderate/significant/severe.
Use cases: environmental impact assessment (EIA) of construction projects, planning-level EIA, and cumulative environmental impact screening.
Dependencies / 依赖
pip install numpy rasterio scipy
Usage / 使用方法
Example 1: synthetic four-factor pressure scenario
python geoskill-environmental-impact-assessment.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./output
Example 2: real multi-band pressure raster (each band = one pressure factor)
python geoskill-environmental-impact-assessment.py --input pressures.tif --output-dir ./real
Example 3: different region
python geoskill-environmental-impact-assessment.py --bbox 121 31 122 32 --synthetic --output-dir ./shanghai
Example 4: tiny region for quick validation
python geoskill-environmental-impact-assessment.py --bbox 116.39 39.90 116.40 39.91 --synthetic --output-dir ./tiny
Example 5: silent batch run
python geoskill-environmental-impact-assessment.py --bbox 113 23 114 24 --synthetic --quiet --output-dir ./batch
Output / 输出
| File | Format | Description |
|---|---|---|
impact_index.tif | GeoTIFF (float32) | Composite impact index ∈ [0,1], EPSG:4326 |
impact_grade.tif | GeoTIFF (float32) | Impact grade 0-4 |
eia_params.json | JSON | Weights, thresholds, pixel counts per grade |
output-manifest.json | JSON | Run manifest (inputs/outputs/QA/software versions) |
Data Source / 数据源 / Source
Local GeoTIFF (multi-band pressure factors, optional); the independent-probability model for cumulative effects is a published EIA method; synthetic mode generates an urban-gradient pressure field locally with no external data sources.
Privacy / 隐私声明 / Privacy
- Runs fully offline by default and makes no network requests
--syntheticmode reads no external data- All computation is done locally; user data is never uploaded
License / License
MIT
name: geoskill-environmental-impact-assessment description: '多压力因子归一化加权叠加得综合影响指数，独立概率模型估算累积效应，按阈值划分5 级影响等级。Assesses environmental impact grades by multi-factor overlay and cumulative effects. 输出影响指数与等级 GeoTIFF。'
环境影响评价 | Environmental Impact Assessment
四个压力因子（污染、土地利用变化、噪声、生境破碎化）各自 min-max 归一化后按敏感度权重（0.30/0.25/0.25/0.20）加权叠加；累积效应用独立概率模型 C = 1 - Π(1-Ii)，保证多项目叠加不超过 1 且 ≥ 任一单独项目；最终指数 = 0.5×加权叠加 + 0.5×累积效应，按 0.1/0.3/0.5/0.7 阈值分为可忽略/轻微/中等/显著/严重 5 级。
适用场景：建设项目环评、规划环评、累积环境影响筛查。
依赖
pip install numpy rasterio scipy
使用方法
示例 1：合成四因子压力场景
python geoskill-environmental-impact-assessment.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./output
示例 2：真实多波段压力栅格（每波段=一个压力因子）
python geoskill-environmental-impact-assessment.py --input pressures.tif --output-dir ./real
示例 3：不同区域
python geoskill-environmental-impact-assessment.py --bbox 121 31 122 32 --synthetic --output-dir ./shanghai
示例 4：极小区域快速验证
python geoskill-environmental-impact-assessment.py --bbox 116.39 39.90 116.40 39.91 --synthetic --output-dir ./tiny
示例 5：静默批量
python geoskill-environmental-impact-assessment.py --bbox 113 23 114 24 --synthetic --quiet --output-dir ./batch
输出
| 文件 | 格式 | 说明 |
|---|---|---|
impact_index.tif | GeoTIFF (float32) | 综合影响指数 ∈ [0,1]，EPSG:4326 |
impact_grade.tif | GeoTIFF (float32) | 影响等级 0-4 |
eia_params.json | JSON | 权重、阈值、等级像元计数 |
output-manifest.json | JSON | 运行清单（输入/输出/QA/软件版本） |
数据源 / Source
本地 GeoTIFF（多波段压力因子，可选）；累积效应独立概率模型为公开环评方法；合成模式本地生成城市梯度压力场，无外部数据源。
隐私声明 / Privacy
- 默认完全离线运行，不发起任何网络请求
--synthetic模式不读取任何外部数据- 所有计算在本地完成，不上传用户数据
License
MIT
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