The Cooling Effects of Landscape Configurations of Green–Blue Spaces in Urban Waterfront Community

Abstract

Optimizing the configuration of green–blue spaces is crucial in mitigating the urban heat island effect. However, many existing studies neglect to consider the synergistic cooling effect of green–blue space and its spatial comparison, focusing instead on individual ecological elements of green space or water bodies. Additionally, the relative importance of different configuration indicators and their marginal effects on the cooling effect of green–blue space remain unclear, with an identified need for the quantification of indicator thresholds for maximizing the cooling effect. To address these gaps, this study investigated green–blue spaces in 30 urban waterfront communities located in Kunshan City, Jiangsu Province, China, and measured the scale, distribution, morphology, green–blue relationship, and built environment of these spaces. To determine the cooling effect, maximum air temperature and mean cold island intensity were measured using ENVI-met simulations. Correlation analyses and boosted regression trees (BRT) were utilized to identify the configuration indicators that affect the cooling effect and their action threshold. The results show that green space distribution and water body shape are the most important features affecting the maximum air temperature, with green space patch density (PD) and water landscape shape index (LSI) contributing 21.3% and 20.9% to the reduction in temperature, while the thresholds are 550 and 4.2, respectively. The contribution of green–blue space percentage is critical in raising urban cold island intensity, with threshold effects at 43%. These findings provide practical guidance for the efficient exploitation of the synergistic cooling effects of green–blue space and enhancement of climate resilience in coastal cities.