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Enhancing the cooling effectiveness of green spaces (GSs) is crucial for improving urban thermal environments in the context of global warming. Increasing GS coverage and optimizing its spatial distribution individually proved to be effective urban cooling measures. However, their comparative cooling effectiveness and potential interaction remain unclear. Here, using the moving window approach and random forest algorithm, we established a robust model (R2= 0.89 ± 0.01) to explore the relationship between GS and land surface temperature (LST) in the Chinese megacity of Guangzhou. Subsequently, the response of LST to varying GS coverage and its spatial distribution was simulated, both individually and in combination. The results indicate that GS with higher coverage and more equitable spatial distribution is conducive to urban heat mitigation. Increasing GS coverage was found to lower the city’s average LST by up to 4.73 °C, while optimizing GS spatial distribution led to a decrease of 1.06 °C. Meanwhile, a synergistic cooling effect was observed when combining both measures, resulting in additional cooling benefits (0.034–0.341 °C). These findings provide valuable insights into the cooling potential of GS and crucial guidance for urban green planning aimed at heat mitigation in cities.

As a vital component of urban green infrastructures, urban green space (UGS) provides essential ecological, recreational, and social-cultural services to urban residents. Ensuring adequate and equitable accessibility to UGS for all urban residents has become an integral aspect of promoting social justice. However, studies that comprehensively investigate the long-term changes in urban green space accessibility (UGSA) and its equity under rapid urbanization are scarce, thereby limiting the potential guidance for implementing nature-based solutions to enhance ecosystem services that benefit urban residents. In this study, taking Guangzhou, China, as the empirical study area, the UGSA and its equity during 2000–2015 were evaluated at the district level by combining the Gaussian-based two-step floating catchment area method (Gaussian-based 2SFCA) and the Gini coefficient. Meanwhile, the changes in land cover and land use (LULC) were also investigated to reveal the dynamics of the UGS. Moreover, the long-term synchronous changes between UGSA and its equity were explored through a grouping analysis based on the four-quadrant method. The results revealed spatial heterogeneity in UGSA, with peri-urban districts having more accessibility to UGS compared to core-urban districts. The equity of UGSA exhibited an uneven spatial pattern, with most districts displaying consistently low levels of equality. The results of grouping analysis underscored the significance of considering both the improvements of UGSA and its equity in policy-making, leading to specific policy implications for each district. Our study provides valuable insights that can inform future urban spatial greening strategies and contribute to the promotion of sustainable urban development.