Install
openclaw skills install @ruiduobao/geoskill-land-value-estimationEstimate land value with a hedonic price model driven by accessibility, POI density and green proximity.
openclaw skills install @ruiduobao/geoskill-land-value-estimationEstimates the spatial distribution of land value with a hedonic price model, supporting land price assessment and location analysis.
Core algorithm: accessibility = exp(−distance to center / decay scale), higher closer to the center; green proximity works the same way; value = intercept + β_acc × accessibility + β_poi × POI density + β_green × green proximity. The model is linear and additive with non-negative values; it ships with a least-squares coefficient calibration function that can exactly recover known coefficients from samples.
pip install 'numpy' 'rasterio'
python geoskill-land-value-estimation.py --bbox 116.0 39.0 117.0 40.0 [other parameters]
python geoskill-land-value-estimation.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out
python geoskill-land-value-estimation.py --input features.tif --output-dir ./out
python geoskill-land-value-estimation.py --bbox 121.0 31.0 122.0 32.0 --decay 50 --output-dir ./out --quiet
python geoskill-land-value-estimation.py --input features.tif --coef-acc 8000 --intercept 2000 --output-dir ./out
python geoskill-land-value-estimation.py --bbox 116.0 39.0 117.0 40.0 --synthetic --coef-poi 3000 --output-dir ./out --quiet
| File | Format | Description |
|---|---|---|
land_value.tif | GeoTIFF | Land value raster |
hedonic_coefficients.json | JSON | Hedonic model coefficients and decay scale |
value_stats.json | JSON | Value mean/range, mean accessibility |
output-manifest.json | JSON | Run manifest |
A local three-band feature GeoTIFF (distance to center, POI density, distance to green space); --synthetic mode simulates a monocentric urban pattern.
--synthetic mode requires no network at all.MIT
用特征价格(Hedonic)模型估算土地价值空间分布,服务于地价评估与区位分析。
核心算法:可达性 = exp(−到中心距离/衰减尺度),越靠近中心越高;绿地邻近性同理;价值 = 截距 + β_acc×可达性 + β_poi×POI密度 + β_green×绿地邻近性。模型线性可加、价值非负;附带最小二乘系数标定函数,可由样本精确恢复已知系数。
pip install 'numpy' 'rasterio'
python geoskill-land-value-estimation.py --bbox 116.0 39.0 117.0 40.0 [其他参数]
python geoskill-land-value-estimation.py --bbox 116.0 39.0 117.0 40.0 --synthetic --output-dir ./out
python geoskill-land-value-estimation.py --input features.tif --output-dir ./out
python geoskill-land-value-estimation.py --bbox 121.0 31.0 122.0 32.0 --decay 50 --output-dir ./out --quiet
python geoskill-land-value-estimation.py --input features.tif --coef-acc 8000 --intercept 2000 --output-dir ./out
python geoskill-land-value-estimation.py --bbox 116.0 39.0 117.0 40.0 --synthetic --coef-poi 3000 --output-dir ./out --quiet
| 文件 | 格式 | 说明 |
|---|---|---|
land_value.tif | GeoTIFF | 土地价值栅格 |
hedonic_coefficients.json | JSON | Hedonic 模型系数与衰减尺度 |
value_stats.json | JSON | 价值均值/范围、平均可达性 |
output-manifest.json | JSON | 运行清单 |
本地三波段特征 GeoTIFF(到中心距离、POI 密度、到绿地距离);--synthetic 模式模拟单中心城市格局。
--synthetic 模式完全无网络。MIT