Assessing the impact of urban block-scale landscape features on the diurnal cooling of green spaces using SDGSAT-1

• Blocks selected as spatial units to assess urban green space cooling intensity. • Nighttime cooling mechanisms differ from daytime in urban green spaces. • Key cooling metrics compared across cities in different climate zones. Urban green space (UGS) is a key component of Sustainable Development Goal (SDG) 11.7.1, urban public open space, and is essential for mitigating the urban heat island (UHI) effect. However, the impact of urban landscape features on the diurnal cooling performance of UGS at the block scale across different climates remains insufficiently understood. The objective of this study is to explore the differences in features that influence the cooling intensity of UGS at both day and night under varying climatic conditions. Four Chinese cities located in distinct climate zones—Beijing, Shanghai, Haikou, and Urumqi—were selected as study areas. High-resolution land surface temperature (LST) data for summer days and nights were derived from SDGSAT-1/TIS imagery, while land cover classifications were obtained from Gaofen (GF) satellite images. UGS cooling intensity was calculated as the temperature difference between impervious surfaces and UGS within each urban block. To identify the key metrics influencing UGS cooling, we employed a boosted regression tree (BRT) model incorporating seven UGS landscape metrics, one UGS biophysical metric, and four urban block morphology metrics. The results revealed that UGS exhibited a more pronounced cooling effect during the daytime than at night. Key metrics also varied across cities. During the day, UGS area (+), UGS edge density (−), and block patch density (−) were significant in Beijing and Shanghai, while block area (+), UGS aggregation index (+), and UGS edge density (−) were dominant in Haikou and Urumqi. At night, the UGS aggregation index (+) was the most influential metric across all four cities. Moreover, the key metrics exhibited optimal values or thresholds of influence, with significant differences observed across cities. This study provides an important insight into how UGS features regulate diurnal cooling across different climates and offers recommendations for UHI mitigation strategies.