An Integrated Framework of Residential Community Construction year and Building Height Analysis

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This repository contains the code and sample data for "Spatiotemporal Patterns and Influencing Factors of Residential Building Height in Beijing". Files are numbered to reflect the analytical workflow: (1) Landsat time-series extraction via GEE, (2) Random Forest binary classification of pre/post-2000 communities, (3) classifier validation, (4) temporal segmentation for construction year identification, (5) temporal segmentation validation, and (6) XGBoost-SHAP influencing factor analysis. Place data files in ./data/ before running scripts. Required Python packages: pandas, numpy, matplotlib, scikit-learn, xgboost, shap, geopandas, statsmodels, scipy, seaborn, joblib.

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