Diurnal Asymmetry in the Relationships Between Urban Morphology and Canopy Urban Heat Islands: An Interpretable Machine Learning Analysis

Canopy urban heat island (CUHI), defined as the air temperature difference between the urban near-surface atmosphere and surrounding rural areas, exhibits diurnal variability and affects urban thermal environments and well-being. However, the nonlinear effects of urban morphology on daytime and nighttime CUHI remain insufficiently understood. Taking the Yangtze River Delta (YRD) as the study area, this study integrates remote sensing, building morphology, and ground-based meteorological data to characterize urban morphology and canopy urban heat island intensity (CUHII). Extreme Gradient Boosting (XGBoost), SHapley Additive exPlanations (SHAP), and dependence plots were used to quantify and interpret nonlinear morphology–CUHII relationships. The models showed moderate explanatory ability, indicating that the selected morphology indicators explained only part of CUHII variability. Nighttime CUHII was stronger than daytime CUHII, with average values of 0.848 °C and 0.431 °C, respectively, and high-value areas concentrated in Shanghai, northern Zhejiang, and southern Jiangsu. During the daytime, the Aggregation Index (AI) was the most important selected morphology variable and was positively associated with CUHII, suggesting that compact built-up patterns may enhance heat accumulation by increasing heat absorption and limiting ventilation. At night, the Splitting Index (SPLIT) ranked first, with higher values generally associated with weaker CUHII, possibly reflecting greater spatial openness and reduced continuity of built-up surfaces. The nonlinear transition ranges of AI and SPLIT further reveal diurnal asymmetry in morphology–CUHII relationships. These findings support time-specific urban heat mitigation while avoiding attribution of overall CUHII variability solely to urban morphology.