Seasonal Nonlinearity and Spatial Non-Stationarity of Urban Thermal Comfort Drivers: Implications for Sustainable Urban Planning in Tianjin, China

Rapid urbanization and intensifying thermal stress pose challenges to urban livability, climate resilience, and sustainable development. However, studies overlook the seasonal nonlinearity and spatial non-stationarity of urban thermal comfort and its driving factors, constraining seasonally differentiated, climate-adaptive planning strategies. Taking central Tianjin, China, as a case study, this research integrates a geographically weighted XGBoost model with shapley additive explanations to disentangle the seasonal and spatial differentiation, nonlinear relationships, and conditional interaction patterns of the Universal Thermal Climate Index (UTCI). Results indicate: (1) UTCI exhibits seasonal differences in spatial thermal gradients, with relatively high values concentrated in central and northern-central areas; (2) driver contributions shift across seasons, with evapotranspiration leading in summer, digital elevation model in autumn, and building density in winter, while landscape composition contributes most strongly in winter; (3) candidate nonlinear breakpoints include winter sky view factor (0.683; 95% interval 0.662–0.752) and water patch density (15.6 patches/100 ha; 13–17.8); (4) conditional interactions vary seasonally, involving environmental–terrain combinations in summer and building-morphology–landscape combinations in winter. These findings reveal season-specific thermal comfort associations, providing quantitative evidence for translating nonlinear relationships and spatial heterogeneity into climate-adaptive urban design. This supports targeted thermal-environment interventions for urban resilience and sustainability.