Characterizing the impact of urban morphology heterogeneity on land surface temperature in Guangzhou, China

被引:151
|
作者
Guo, Guanhua [1 ,2 ]
Zhou, Xiaoqing [1 ,2 ]
Wu, Zhifeng [3 ]
Xiao, Rongbo [4 ]
Chen, Yingbiao [3 ]
机构
[1] Guangzhou Univ, Acad Bldg Energy Efficiency, Guangdong Prov Key Lab Technol Bldg Energy Effici, Guangzhou 510006, Guangdong, Peoples R China
[2] Guangzhou Univ, Sch Civil Engn, Guangzhou 510006, Guangdong, Peoples R China
[3] Guangzhou Univ, Sch Geog Sci, Guangzhou 510006, Guangdong, Peoples R China
[4] Guangdong Prov Acad Environm Sci, Guangzhou 510045, Guangdong, Peoples R China
基金
中国博士后科学基金;
关键词
Urban heat island (UHI); Land surface temperature (LST); Urban morphology; Building height; Building density; Sky view factor (SVF); HEAT-ISLAND; WINDOW ALGORITHM; DENSITY; URBANIZATION; THERMOGRAPHY; VENTILATION; REGRESSION; CITY; TOOL; TM;
D O I
10.1016/j.envsoft.2016.06.021
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The urban morphology is regarded as one of the main reasons for urban heat island (UHI). However, its effect on UHI in city-scale urban areas has seldom been examined. In this paper, we presented a rule based regression model for investigating the nonlinear relationship between land surface temperature (LST) and urban morphology represented by building height, building density and sky view factor (SVF) across different dates in 2005. Results found that an urban morphology of medium building height and lower density significantly yielded higher LST variation levels, whereas the lowest LST variation levels occurred in high-rise and high-dense building arrays. Compared to building height, building density had a stronger influence on LST. Medium SVF values produced the lowest LST, whereas the largest and smallest SVF values produced the highest LST. Results also showed how rule-based regression model offer great performance in detecting the nonlinear mechanisms of LST as well. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:427 / 439
页数:13
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