Cooling Efficiency of Urban Green Spaces Across Functional Zones: Mitigating Heat Island Effects Through Spatial Configuration

With the acceleration of urbanization, the urban heat island effect has garnered increasing attention. However, few studies have explored the differential impacts of urban green spaces on the UHI across various urban functional zones (UFZs). This study takes Xiamen Island as the research object and selects nine representative landscape pattern indices to characterize the spatial patterns of UGS in each urban functional zone. Through Pearson correlation analysis, four landscape indices—largest patch index (LPI), mean patch area (AREA_MN), area-weighted average shape index (SHAPE_AM), and aggregation index (AI)—were chosen to reveal the varying influences of UGS spatial patterns on the UHI in different urban functional zones. These four landscape indices reflect aspects such as area, shape complexity, density size, and variation, as well as the aggregation of UGS. To address the spatial autocorrelation of variables, a spatial regression model was established. Given that the parameters of the spatial lag model outperformed those of the spatial error model, the spatial lag model was selected. Key findings reveal that the cooling efficiency of UGS varies across UFZs. In urban residential zones (URZs), UGS with complex shapes significantly enhances cooling, as indicated by a negative correlation between SHAPE_AM and LST (β = −0.446, p < 0.05). In urban village zones (UVZs), larger green patches have a stronger cooling effect, with AREA_MN showing a significant negative correlation with LST (β = −1.772, p < 0.05). The results indicate that UGS in different urban functional zones plays distinct roles in mitigating the UHI, with its cooling effects being associated with the spatial patterns of UGS. Therefore, it is recommended to adopt differentiated planning strategies for UGS in various urban functional zones to contribute to a more sustainable and thermally comfortable urban environment.