Urban communities exhibit complex thermal behaviors driven by interactions among buildings, vegetation, and shadows, yet their combined effects remain insufficiently understood. This study analyzed 309 communities within Beijing's core urban area to quantify how green space ratio (GR), vegetation spatial configuration (ENNMN), building density, and shadow ratio influence land surface temperature (LST). Using multi-source remote sensing data, Gradient Boosted Regression Trees (GBRT), and SHAP interpretation, we found that building density is the dominant driver of community-scale thermal patterns (43. 7%), followed by shadows (35. 9%) and green spaces (20. 4%). Building density and shadow ratio exhibited clear threshold effects, with building density above 50% intensifying warming and shadow ratios below 10% failing to provide adequate cooling. Similar GR levels corresponded to varied cooling effects, demonstrating the strong interactions between community elements. These findings highlight the necessity of integrated planning that coordinates building form, shading, and vegetation structure to improve community thermal environments. The study provides actionable quantitative thresholds and configuration guidelines for designing climate-resilient urban communities.
Zhang et al. (Wed,) studied this question.