Derive aerodynamic roughness and ventilation potential from building morphology and extract least-resistance ventilation corridors.
1 次安装
编程
geoskill-urban-microclimate
试用Analyze urban heat island intensity and ventilation index from land surface temperature, NDVI, impervious surface and building morphology.
它能做什么
Analyze urban heat island intensity and ventilation index from land surface temperature, NDVI, impervious surface and building morphology.
技能文档
城市微气候分析 | Urban Microclimate Analysis
Analyzes urban microclimate from land surface temperature, vegetation, impervious surface and building morphology, supporting heat island mitigation and ventilation planning.
Core algorithm: LST modeling = baseline temperature + α×ISA − β×NDVI (impervious surfaces heat, vegetation cools through evapotranspiration); heat island intensity UHII = LST − rural reference temperature, positively correlated with ISA; ventilation index VI = SVF×(1−building density) ∈ [0,1] — high density combined with a low sky view factor indicates poor ventilation.
Dependencies / 依赖
pip install 'numpy' 'rasterio'
Usage / 使用方法
Basic Usage
python geoskill-urban-microclimate.py --bbox 116.0 39.0 117.0 40.0 [other parameters]
Examples
Example 1 (Synthetic Data (Offline))
python geoskill-urban-microclimate.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out
Example 2 (Usage 2)
python geoskill-urban-microclimate.py --input features.tif --output-dir ./out
Example 3 (Usage 3)
python geoskill-urban-microclimate.py --bbox 121.0 31.0 122.0 32.0 --rural-temp 23 --output-dir ./out --quiet
Example 4 (Usage 4)
python geoskill-urban-microclimate.py --input features.tif --alpha 12 --beta 5 --output-dir ./out
Example 5 (Usage 5)
python geoskill-urban-microclimate.py --bbox 116.0 39.0 117.0 40.0 --synthetic --base-temp 26 --output-dir ./out --quiet
Output / 输出
| File | Format | Description |
|---|---|---|
microclimate.tif | GeoTIFF | Three bands: band1=LST, band2=heat island intensity UHII, band3=ventilation index |
microclimate_stats.json | JSON | Mean LST/UHII, max UHII, ventilation index, UHII-ISA correlation coefficient |
output-manifest.json | JSON | Run manifest |
Data Source / 数据源 / Source
Local four-band GeoTIFF (ISA, NDVI, building density, SVF); --synthetic mode simulates a center-to-suburb heat island gradient scenario.
Privacy / 隐私声明 / Privacy
- Runs offline by default;
--syntheticmode requires no network at all. - All processing is done locally; user data is never uploaded.
License / License
MIT
name: geoskill-urban-microclimate description: 'Analyze urban heat island intensity and ventilation index from land surface temperature, NDVI, impervious surface and building morphology.'
城市微气候分析 | Urban Microclimate Analysis
从地表温度、植被、不透水面与建筑形态分析城市微气候，服务于热岛缓解与通风规划。
核心算法：LST 建模 = 基准温度 + α×ISA − β×NDVI（不透水面加热、植被蒸散降温）；热岛强度 UHII = LST − 郊区参考温度，与 ISA 正相关；通风指数 VI = SVF×(1−建筑密度) ∈ [0,1]，密度高且天空可视因子低 → 通风差。
依赖
pip install 'numpy' 'rasterio'
使用方法
基本用法
python geoskill-urban-microclimate.py --bbox 116.0 39.0 117.0 40.0 [其他参数]
示例
示例 1（合成数据（离线））
python geoskill-urban-microclimate.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out
示例 2（用法 2）
python geoskill-urban-microclimate.py --input features.tif --output-dir ./out
示例 3（用法 3）
python geoskill-urban-microclimate.py --bbox 121.0 31.0 122.0 32.0 --rural-temp 23 --output-dir ./out --quiet
示例 4（用法 4）
python geoskill-urban-microclimate.py --input features.tif --alpha 12 --beta 5 --output-dir ./out
示例 5（用法 5）
python geoskill-urban-microclimate.py --bbox 116.0 39.0 117.0 40.0 --synthetic --base-temp 26 --output-dir ./out --quiet
输出
| 文件 | 格式 | 说明 |
|---|---|---|
microclimate.tif | GeoTIFF | 三波段：band1=LST，band2=热岛强度 UHII，band3=通风指数 |
microclimate_stats.json | JSON | 平均 LST/UHII、最大 UHII、通风指数、UHII-ISA 相关系数 |
output-manifest.json | JSON | 运行清单 |
数据源 / Source
本地四波段 GeoTIFF（ISA, NDVI, 建筑密度, SVF）；--synthetic 模式模拟中心-郊区热岛梯度场景。
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，不上传用户数据。
License
MIT
相关技能
Compute street canyon height-to-width ratio and sky view factor (SVF) from a digital surface model.
1 次安装
Delineate urban growth boundaries from historical expansion rate and direction plus terrain, cropland and ecological constraints.
1 次安装
Detect and quantify urban expansion from multi-temporal built-up rasters. Use when the user wants to analyze changes, compare multi-temporal rasters, compute indices, or generate assessment reports.
1 次安装
Map slums and shanty areas using a multi-indicator index of texture, building density, night light and population density.
1 次安装
Detect informal settlements by fusing texture irregularity, building morphology and spectral mixing into a classification score.
1 次安装