Understanding seasonal contributions of urban morphology to thermal environment based on boosted regression tree approach
文献类型： 外文期刊
作者： Han, Dongrui 1 ; An, Hongmin 2 ; Wang, Fei 1 ; Xu, Xinliang 3 ; Qiao, Zhi 4 ; Wang, Meng 1 ; Sui, Xueyan 1 ; Liang, Shouzhen 1 ; Hou, Xuehui 1 ; Cai, Hongyan 3 ; Liu, Yihui 5 ;
作者机构： 1.Shandong Acad Agr Sci, Inst Agr Informat & Econ, Jinan 250100, Peoples R China
2.Shandong Univ, Sch Management, Jinan 250100, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
4.Tianjin Univ, Sch Environm Sci & Engn, Tianjin 300350, Peoples R China
5.Linyi Bur Nat Resources & Planning, Urban & Rural Planning Res Ctr, Linyi 276000, Peoples R China
6.11A,Datun Rd, Beijing 100101, Peoples R China
关键词： Urban morphology; Building; Thermal environment; Land surface temperature; Boosted regression tree
期刊名称：BUILDING AND ENVIRONMENT （ 影响因子：7.093； 五年影响因子：7.503 ）
ISSN： 0360-1323
年卷期： 2022 年 226 卷
页码：
收录情况： SCI
摘要： Urban morphology significantly affects the urban thermal environment. Seasonal impacts of two-dimensional (2D) and three-dimensional (3D) urban morphology on land surface temperature (LST) remain uncertain, and the impacts exist scale effects. Thus, taking Beijing as the study area, boosted regression tree (BRT) model was used to investigate the seasonal contributions of urban morphology to the thermal environment. Building density (BD), building height (BH), floor area ratio (FAR), sky view factor (SVF), and frontal area index (FAI), were used to comprehensively characterize urban morphology, and 13 scales ranging from 30 m to 600 m were used to investigate scale effects. The results showed that there are obvious spatial differences in LST and urban morphology indicators in the study area. 270 m was determined as the optimal scale for modeling in the study area. BH and BD are the domain indicators, which together contribute more than 75% of the variance of LST among four seasons, while the relative influences of SVF, FAR, and FAI are relatively low. Relationships between urban morphology indicators and LST are nonlinear among four seasons. The findings provide a scientific un-derstanding for urban planners on mitigating the UHI effects through optimizing buildings.
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