The Impact of Spatiotemporal Effect and Relevant Factors on the Urban Thermal Environment Through the XGBoost-SHAP Model

The urban thermal environment is a critical topic in contemporary urban studies. However, the mechanisms driving the relationships between influencing factors and the urban thermal environment across different spatial scales and temporal dimensions remain unclear, particularly as most of these relationships exhibit nonlinearity. This study utilizes XGBoost and SHAP models, combined with a partial dependency plot, to analyze the influence of population activities, built environment, urban topography, ecological and climatic conditions, and urban landscape pattern on the diurnal and nocturnal land surface temperature (LST) changes across urban and rural areas of Hangzhou throughout the year. The results indicate that during the daytime, urban topography exerts a strong influence on LST changes in both urban and rural areas of Hangzhou. At nighttime, the influence of population activities becomes more pronounced. Meanwhile, urban landscape patterns show no significant impact on LST in either urban or rural areas, regardless of daytime or nighttime. Additionally, we analyzed the specific nonlinear relationships between influencing factors and LST. Finally, our findings suggest that influencing factors can interact synergistically in pairs to affect LST, with this mechanism being more prominent in urban areas. Overall, the study categorizes and examines the factors contributing to urban thermal environment changes from spatial and temporal perspectives, providing insights for developing urban planning strategies to mitigate urban heat issues in the future.