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ContextUrban green space (UGS) has been widely acknowledged to effectively reduce ambient temperature, and thus improving its cooling effect has become a hot topic in urban planning. Although the impact of UGS spatial pattern on land surface temperature (LST) has been investigated in previous studies, the differences caused by the heterogeneity of...
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The significance of urban green space (UGS) in alleviating the urban heat island effect has attracted increasing attentions. The size, growth dynamics, and surroundings of UGS evolve with urbanization. However, the impact of these changes on the UGS cooling remains unknown, hindering the formulation of targeted greening policies at different urbanization stages. Focused on the Three Ring Road area in Changsha City, comprehensive urbanization indexes from 2000 to 2020 were computed, identifying the periods characterized by high-speed growth, transition, and steady development. By calculating the cooling indicators of UGS, employing partial correlation analysis and geographic detectors, this study clarified the determinants of the cooling effect of UGS. Results revealed that urbanization significantly impacted the cooling effect of UGS, with the cooling gradient, intensity, range, and distance exhibiting a gradual increase. Meanwhile, cooling efficiency demonstrated an initial ascent followed by a subsequent decline. Notably, the pivotal factors influencing the cooling effect of UGS shifted from external factors (surrounding construction land and ecological land) to internal factors (growth status), and eventually to the synergy of both internal and external factors. This study contributed valuable insights for delineating optimal UGS cooling strategies across diverse urbanization stages to improve urban climate adaptability.
Urban park green spaces exhibit significant cool island effects, which can effectively mitigate the urban heat environment. Clarifying the characteristics and differences in the cool island effects of urban parks across different spatial gradients within cities is instrumental in identifying potential issues and optimizing the structure and resource allocation of park green spaces in a scientifically rational manner. This study focuses on parks within the central urban area of Beijing, utilizing remote sensing image interpretation and land surface temperature (LST) inversion to extract relevant characteristics of park green spaces and the park cool island intensity (PCI) index. Various mathematical and statistical methods including correlation analysis, regression analysis, and cluster analysis are employed to conduct comparative studies across three gradients: within the 3rd ring road, between the 3rd and 5th ring roads, and outside the 5th ring road. The analysis reveals that both park green space characteristics and urban heat island effects exhibit spatial gradient differences, collectively influencing the cool island effects of urban park green spaces. PCI gradually decreases across the three spatial gradients. Cluster analysis identifies four distinct types of parks with different cool island effect characteristics, highlighting the need for optimization and improvement in over half of the parks. Various indicators of park green space characteristics show different correlations with PCI, with variations in correlation strength and thresholds across gradients. The fitting effects of regression equations for each characteristic indicator and PCI gradually worsen from within the 3rd ring road to outside the 5th ring road, with different factors playing important roles across gradients. This study enhances our understanding of the cool island effects of urban park green spaces and facilitates the proposition of differentiated optimization management strategies for urban park green space planning and system construction in different regions.
