Quantifying the cooling effects of multi-scale urban blue-green spaces on surrounding local climate zones in hot and humid climatic areas

Abstract

Urban blue-green spaces (UBGS) are widely known for mitigating urban overheating through their evapotranspiration and shading effects. This study integrates multi-source data, including remote sensing imagery and land cover, to identify 1,294 UBGS blocks of varying scales in Guangzhou, along with their characteristic parameters. Field measurements, combined with the Local Climate Zone (LCZ) framework, derived cooling effect parameters for 6,230 blocks. Results indicate that northern vegetation-dominated areas exhibit average NDVI values of 0.6∼0.8, whilst the highly urbanised central regions show higher ET values ranging from 0.6 to 1.0. The LCZ-based air temperature inversion models demonstrate considerable accuracy, and air temperature distribution maps reveal that UBGS present an average of 4.2°C lower than built-up areas in August. Correlation analysis of cooling effect parameters and LCZ types indicates that LCZ 5 exhibits a cooling intensity of 3∼7°C, whilst LCZ G demonstrates a cooling distance exceeding 600 metres. Through random forest regression, SHAP interpretation, and NSGA-II multi-objective optimisation, the cooling effects of UBGS are systematically quantified. Key influencing parameters are clarified: WAR and NDVI exert significant positive effects on CI and CD, while HR exhibits negative effects, and their optimal configuration ranges are obtained (WAR 0.04∼0.82, GAR 0.05∼0.83, FVC 0.02∼0.37, HR 0.06∼0.12, PA 246∼443, S_UBGS 11.2∼132hm²). The developed multi-scale UBGS-LCZ optimization framework of this study contributes to revealing parameterized cooling mechanism of UBGS on surrounding LCZs and helps guide UBGS optimization design.