Associated Determinants of Surface Urban Heat Islands across 1449 Cities in China

doi:10.1155/2019/4892714

	Associated Determinants of Surface Urban Heat Islands across 1449 Cities in China
	Li, Yuanzheng 1,2,3; Wang, Lan 4; Liu, Min 1,3; Zhao, Guosong 5; He, Tian 6; Mao, Qizheng 1
刊名	ADVANCES IN METEOROLOGY
	2019-07-21
卷号	2019 页码:14
ISSN号	1687-9309
DOI	10.1155/2019/4892714
通讯作者	Wang, Lan(wlsunshinelz@163.com) ; Zhao, Guosong(zhaogs86@126.com)
英文摘要	The thermal environment is closely related to human well-being. Determinants of surface urban heat islands (SUHIs) have been extensively studied. Nevertheless, some research fields remain blank or have conflicting findings, which need to be further addressed. Particularly, few studies focus on drivers of SUHIs in massive cities with different sizes under various contexts at large scales. Using multisource data, we explored 11 determinants of surface urban heat island intensity (SUHII) for 1449 cities in different ecological contexts throughout China in 2010, adopting the Spearman and partial correlation analysis and machine learning method. The main results were as follows: (1) Significant positive partial correlations existed between daytime SUHII and the differences in nighttime light intensity and built-up intensity between cities and their corresponding villages except in arid or semiarid western China. The differences in the enhanced vegetation index were generally partially negatively correlated with daytime and nighttime SUHII. The differences in white sky albedo were usually partially negatively correlated with nighttime SUHII. The mean air temperature was partially positively correlated with nighttime SUHII in 40% of cases. Only a few significant partial relationships existed between SUHII and urban area, total population, and differences in aerosol optical depth. The explanation rates during daytime were larger than during nighttime in 72% of cases. The largest and smallest rates occurred during summer days in humid cold northeastern China (63.84%) and in southern China (10.44%), respectively. (2) Both the daytime and nighttime SUHII could be well determined by drivers using the machine learning method. The RMSE ranged from 0.49 degrees C to 1.54 degrees C at a national scale. The simulation SUHII values were always significantly correlated with the actual SUHII values. The simulation accuracies were always higher during nighttime than daytime. The highest accuracies occurred in central-northern China and were lowest in western China during both daytime and nighttime.
资助项目	National Natural Science Foundation of China[41701501] ; National Natural Science Foundation of China[31600375] ; Social Science Fund of China[17BJL065] ; Key Scientific and Technological Project of Henan Province[192102310003] ; Key Scientific Research Projects of Henan Colleges and Universities[18A170014] ; Philosophy and Social Science Planning Project of Henan Province[2017BJJ005]
WOS关键词	LAND-COVER ; TEMPORAL TRENDS ; SATELLITE DATA ; CITY LIGHTS ; TEMPERATURE ; INTENSITY ; PATTERNS ; IMPACTS ; MODIS ; VEGETATION
WOS研究方向	Meteorology & Atmospheric Sciences
语种	英语
出版者	HINDAWI LTD
WOS记录号	WOS:000478958300001
资助机构	National Natural Science Foundation of China ; Social Science Fund of China ; Key Scientific and Technological Project of Henan Province ; Key Scientific Research Projects of Henan Colleges and Universities ; Philosophy and Social Science Planning Project of Henan Province
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/58067]
专题	中国科学院地理科学与资源研究所
通讯作者	Wang, Lan; Zhao, Guosong
作者单位	1.Henan Univ Econ & Law, Sch Resources & Environm, Zhengzhou 450046, Henan, Peoples R China 2.Henan Univ Econ & Law, Academician Lab Urban & Rural Spatial Data Min He, Zhengzhou 450046, Henan, Peoples R China 3.Chinese Acad Sci, Res Ctr Ecoenvironm Sci, State Key Lab Urban & Reg Ecol, Beijing 100085, Peoples R China 4.Chinese Acad Sci, Inst Urban Environm, Key Lab Urban Environm & Hlth, Xiamen 361021, Fujian, Peoples R China 5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China 6.Zhengzhou Univ, Sch Water Conservancy & Environm, Zhengzhou 450001, Henan, Peoples R China
推荐引用方式 GB/T 7714	Li, Yuanzheng,Wang, Lan,Liu, Min,et al. Associated Determinants of Surface Urban Heat Islands across 1449 Cities in China[J]. ADVANCES IN METEOROLOGY,2019,2019:14.
APA	Li, Yuanzheng,Wang, Lan,Liu, Min,Zhao, Guosong,He, Tian,&Mao, Qizheng.(2019).Associated Determinants of Surface Urban Heat Islands across 1449 Cities in China.ADVANCES IN METEOROLOGY,2019,14.
MLA	Li, Yuanzheng,et al."Associated Determinants of Surface Urban Heat Islands across 1449 Cities in China".ADVANCES IN METEOROLOGY 2019(2019):14.