Footprint-level Building height Estimation

Using Random Forest (RF) and SHAP to estimate footprint-level building height.

Packages

• memopy
• pandas
• geopandas
• numpy
• rasterio
• sklearn

Data

• FABDEM
• AW3D30 DSM
• OpenStreet Map
• EUBUCCO

Result Compare

Citation

Chen, Y., Sun, W., Yang, L., Yang, X., Zhou, X., Li, X., ... & Tang, G. (2024). Refining urban morphology: An explainable machine learning method for estimating footprint-level building height. Sustainable Cities and Society, 105635.

Bibtex format

@article{chen2024refining,
  title={Refining urban morphology: An explainable machine learning method for estimating footprint-level building height},
  author={Chen, Yang and Sun, Wenjie and Yang, Ling and Yang, Xin and Zhou, Xingyu and Li, Xin and Li, Sijin and Tang, Guoan},
  journal={Sustainable Cities and Society},
  pages={105635},
  year={2024},
  publisher={Elsevier}
}