How Do High- and Low-Canopy Landscape Patterns Affect Human Heat Exposure? Mechanisms and Regional Heterogeneity in Chinese Cities, 2000–2020

Urban canopy mitigates urban heat, yet how the spatial configuration of high- and low-canopy layers shapes population heat exposure across a national urban system remains insufficiently understood. Drawing on a panel of 369 Chinese prefecture-level cities for 2000, 2005, 2010, 2015, and 2020, this study constructs a population-weighted thermal-exposure metric—the Human Heat Exposure Index (HEI)—and stratifies urban vegetation into high- and low-canopy classes based on Chinese Land Cover Dataset (CLCD) land-cover types. Multiscale Geographically Weighted Regression (MGWR) and Extreme Gradient Boosting (XGBoost) with SHapley Additive exPlanations (SHAP)-based interpretation are combined to identify spatially varying associations and nonlinear marginal effects of stratified canopy patterns on HEI. HEI shows a persistent south–high, north–low spatial structure, with Global Moran’s I stable at approximately 0.85 throughout the study period. High-canopy edge density and cohesion are increasingly associated with reduced heat exposure in densely built regions, while low-canopy mean patch area and edge density retain explanatory power across all years through near-surface evapotranspirative regulation. The marginal cooling effect of vegetation strengthens appreciably only above an Normalized Difference Vegetation Index (NDVI) of approximately 0.6, and the apparent inflection ranges for impervious surface proportion and standardized solar radiation lie near 25% and 0.4, respectively. These findings suggest that in cities with high impervious loads, cooling-network connectivity and within-zone canopy configuration matter more than additional canopy area alone, and that planning targets should be calibrated to climate zone, city type, and existing surface conditions.