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Correlation Analysis between Urban Green Space and Land Surface Temperature from the Perspective of Spatial Heterogeneity: A Case Study within the Sixth Ring Road of Beijing

Author

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  • Wenrui Liu

    (Research Institute of Forestry, Chinese Academy of Forestry, Key Laboratory of Tree Breeding and Cultivation, National Forestry and Grassland Administration, Beijing 100091, China
    Research Center of Urban Forestry, National Forestry and Grassland Administration, Beijing 100091, China
    School of Tourism and Planning, Pingdingshan University, Pingdingshan 467000, China)

  • Baoquan Jia

    (Research Institute of Forestry, Chinese Academy of Forestry, Key Laboratory of Tree Breeding and Cultivation, National Forestry and Grassland Administration, Beijing 100091, China
    Research Center of Urban Forestry, National Forestry and Grassland Administration, Beijing 100091, China)

  • Tong Li

    (Research Institute of Forestry, Chinese Academy of Forestry, Key Laboratory of Tree Breeding and Cultivation, National Forestry and Grassland Administration, Beijing 100091, China
    Research Center of Urban Forestry, National Forestry and Grassland Administration, Beijing 100091, China)

  • Qiumeng Zhang

    (Research Institute of Forestry, Chinese Academy of Forestry, Key Laboratory of Tree Breeding and Cultivation, National Forestry and Grassland Administration, Beijing 100091, China
    Research Center of Urban Forestry, National Forestry and Grassland Administration, Beijing 100091, China)

  • Jie Ma

    (Henan Institute of Science and Technology, Xinxiang 453003, China)

Abstract

Urban greening has been widely regarded as the most effective, lasting, and economical strategy for alleviating the effects of urban heat islands (UHIs). Previous studies on the cooling effect of urban green spaces (UGSs) tend to analyze the correlation between landscape metrics and land-surface temperature (LST) based on a global parameter estimation, while ignoring urban heterogeneity and autocorrelation. This study focuses on the sixth ring road of Beijing and uses Landsat 8 imagery to retrieve the LST and extract the position of UGSs. We propose a new approach to optimize the selection of landscape metrics, to identify the least and most effective metrics to establish a geographically weighted regression (GWR) model, and to plot the distribution of local regression coefficients to investigate the spatially heterogeneous cooling effects of greenspaces. The effect of UGS landscape metrics on the LST differs according to spatial location; the method enhances our understanding of the effects of UGS spatial configuration on UHIs and better guides the planning and construction of future UGSs.

Suggested Citation

  • Wenrui Liu & Baoquan Jia & Tong Li & Qiumeng Zhang & Jie Ma, 2022. "Correlation Analysis between Urban Green Space and Land Surface Temperature from the Perspective of Spatial Heterogeneity: A Case Study within the Sixth Ring Road of Beijing," Sustainability, MDPI, vol. 14(20), pages 1-20, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:20:p:13492-:d:946929
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    References listed on IDEAS

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    1. Hongbo Zhao & Juntao Tan & Zhibin Ren & Zheye Wang, 2020. "Spatiotemporal Characteristics of Urban Surface Temperature and Its Relationship with Landscape Metrics and Vegetation Cover in Rapid Urbanization Region," Complexity, Hindawi, vol. 2020, pages 1-12, July.
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