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Spatiotemporal Evolution and Driving Factors of the Cooling Capacity of Urban Green Spaces in Beijing over the Past Four Decades

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  • Chao Wang

    (School of Civil Engineering and Geomatics, Shandong University of Technology, Zibo 255000, China)

  • Chaobin Yang

    (School of Civil Engineering and Geomatics, Shandong University of Technology, Zibo 255000, China
    State Key Laboratory of Regional and Urban Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China)

  • Huaiqing Wang

    (School of Civil Engineering and Geomatics, Shandong University of Technology, Zibo 255000, China)

  • Lilong Yang

    (School of Civil Engineering and Geomatics, Shandong University of Technology, Zibo 255000, China)

Abstract

Urban green spaces (UGS) are crucial for mitigating rising urban land surface temperatures (LST). Rapid urbanization presents unresolved questions regarding (a) seasonal variations in the spatial co-distribution of UGS and LST, (b) the temporal and spatial changes in UGS cooling, and (c) the dominant factors driving cooling effects during different periods. This study focuses on Beijing’s Fifth Ring Road area, utilizing nearly 40 years of Landsat remote sensing imagery and land cover data. We propose a novel nine-square grid spatial analysis approach that integrates LST retrieval, profile line analysis, and the XGBoost algorithm to investigate the long-term spatiotemporal evolution of UGS cooling capacity and its driving mechanisms. The results demonstrate three key findings: (1) Strong seasonal divergence in UGS-LST correlation: A significant negative correlation dominates during summer months (June–August), whereas winter (December–February) exhibits marked weakening of this relationship, with localized positive correlations indicating thermal inversion effects. (2) Dynamic evolution of cooling capacity under urbanization: Urban expansion has reconfigured UGS spatial patterns, with a cooling capacity of UGS showing an “enhancement–decline–enhancement” trend over time. Analysis through machine learning on the significance of landscape metrics revealed that scale-related metrics play a dominant role in the early stage of urbanization, while the focus shifts to quality-related metrics in the later phase. (3) Optimal cooling efficiency threshold: Maximum per-unit-area cooling intensity occurs at 10–20% UGS coverage, yielding an average LST reduction of approximately 1 °C relative to non-vegetated surfaces. This study elucidates the spatiotemporal evolution of UGS cooling effects during urbanization, establishing a robust scientific foundation for optimizing green space configuration and enhancing urban climate resilience.

Suggested Citation

  • Chao Wang & Chaobin Yang & Huaiqing Wang & Lilong Yang, 2025. "Spatiotemporal Evolution and Driving Factors of the Cooling Capacity of Urban Green Spaces in Beijing over the Past Four Decades," Sustainability, MDPI, vol. 17(21), pages 1-23, October.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:21:p:9500-:d:1779596
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    References listed on IDEAS

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