A Quantitative Analysis of the Complex Response Relationship between Urban Green Infrastructure (UGI) Structure/Spatial Pattern and Urban Thermal Environment in Shanghai

The urban heat island (UHI) effect has evolved into one of the key environmental problems affecting the urban ecological environment and sustainable development. Based on 52 Urban Thermal Heat spots (UTHSs) with significant differences between land use structure and urban green infrastructure (UGI) spatial layout within the influence range of UHI in Shanghai, Landsat-8/9 satellite images were used to construct a high-dimensional dataset reflecting the impact of built environment components on urban thermal environment. Descriptive statistical analysis was used to analyze the spatial difference qualitatively. Using the stepwise regression (SWR) model and partial least square regression (PLSR) model, the complex response relationship between UGI’s structure/spatial pattern differentiation and urban thermal environment in three spatial stratification ranges of UTHSs was quantitatively analyzed. Overall, the statistical explanatory power of the PLSR model is much better than the stepwise regression model. The PLSR model points out that moderately increasing the average building height, class area (CA), percentage of landscape (PLAND), landscape shape index (LSI), and largest patch index (LPI) play a positive role in inhibiting the growth of land surface temperature (LST), and the cooling effect of index weights decreases in order. However, the interaction effects of the box-cox transformed indices with underlines, e.g., CA × Cohesion × AI × LPI and PLAND × CA × Cohesion × AI × LPI, exert relatively small weight on the cooling effect. According to the results, suggestions such as optimization of the UGI structure and urban construction layout were proposed, which can effectively mitigate the UHI effect.