Regulating Effects of Blue–Green Spaces on Land Surface Temperature Based on Local Climate Zones: A Case Study of Suzhou (2000–2022)

Rapid urbanization has intensified urban surface thermal stress, yet how blue–green spaces (BGs) are associated with land surface temperature (LST) under different urban morphological contexts remains insufficiently understood. Using Suzhou, China, as a case study, this study integrates Landsat imagery from five representative years (2000, 2005, 2010, 2016, and 2022) with a 100 m local climate zone (LCZ) dataset to examine BGs–LST relationships over time. Two BGs indicators are considered: BGs proportion and the within-grid local dispersion of BGs, represented by BGs_std. The results show that LST in Suzhou’s built-up area exhibits a “rise–decline–rise” pattern during the study period, whereas BGs proportions evolve differently across LCZ types. Regression slope analysis shows that higher BGs proportion is generally associated with lower LST across most LCZ types and study years. Relatively stable negative associations are observed in LCZ 2, LCZ 3, LCZ 6, LCZ 9, and LCZ 10. Pearson correlation analysis further shows that BGs_std is generally positively associated with LST and that this relationship tends to strengthen over time. Relatively stronger associations are observed in LCZ 1, LCZ 3, LCZ 5, and LCZ 6 in some years. These findings suggest that BGs–LST relationships should be interpreted not only in terms of BGs proportion, but also in relation to urban form and within-unit BGs organization. This study provides an LCZ-based empirical perspective on BGs–LST associations in the context of a rapidly urbanizing city.