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Impacts of park landscape structure on thermal environment using QuickBird and Landsat images
Authors:Xinliang Xu  Hongyan Cai  Zhi Qiao  Liang Wang  Cui Jin  Yaning Ge  Luyao Wang  Fengjiao Xu
Institution:1.State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing,China;2.School of Environmental Science and Engineering,Tianjin University,Tianjin,China;3.University of Chinese Academy of Sciences,Beijing,China;4.College of Urban and Environmental Science,Liaoning Normal University,Dalian,China;5.School of Soil and Water Conservation,Beijing Forestry University,Beijing,China;6.College of Urban and Environmental Sciences,Central China Normal University,Wuhan,China;7.Geography Department College of Sciences,Yanbian University,Yanji,China
Abstract:Urban parks composed mostly of vegetation and water bodies can effectively mitigate the urban heat island effect. Many studies have investigated the cooling effects of urban parks; however, little attention has been given to park landscape structure. Based on landscape metrics, this study has explored the influences of the park landscape structure on its inner thermal environment, taking heavily urbanized Beijing Municipality in China as the study area. Three indices, including the percentage of landscape (PLAND), landscape shape index (LSI) and aggregation index (AI), were used to measure the composition and configuration characteristics of the landscape components inside the parks. The indices were calculated for five landscape types being interpreted from Quickbird images. Urban thermal conditions were measured using the land surface temperature (LST) derived from Landsat TM images. The results showed that the park LST had a negative relationship with the park size, but no significant relationship was found with park shape. For the park’s interior landscape, however, the configuration and composition characteristics of the landscape components inside the park explained 70% of the park LST variance. The area percentage of water bodies and the aggregation index of woodland were identified as the key influencing characteristics. In addition, when the composition and configuration characteristics of the park landscape components were separately considered, the configuration characteristics (LSI and AI) explained approximately 54% of the variance in park LST, which was comparable with that explained by the composition characteristics (PLAND). Thus, this study suggested that an effective and practical way for urban cooling park design is the optimization of spatial configuration of landscape components inside the park.
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