Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1155/2019/4892714 |
Associated Determinants of Surface Urban Heat Islands across 1449 Cities in China | |
Li, Yuanzheng1,2,3; Wang, Lan4; Liu, Min1,3; Zhao, Guosong5; He, Tian6; Mao, Qizheng1 | |
通讯作者 | Wang, Lan ; Zhao, Guosong |
来源期刊 | ADVANCES IN METEOROLOGY
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ISSN | 1687-9309 |
EISSN | 1687-9317 |
出版年 | 2019 |
卷号 | 2019 |
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. |
类型 | Article |
语种 | 英语 |
国家 | Peoples R China |
开放获取类型 | gold |
收录类别 | SCI-E ; SSCI |
WOS记录号 | WOS:000478958300001 |
WOS关键词 | LAND-COVER ; TEMPORAL TRENDS ; SATELLITE DATA ; CITY LIGHTS ; TEMPERATURE ; INTENSITY ; PATTERNS ; IMPACTS ; MODIS ; VEGETATION |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
来源机构 | 中国科学院地理科学与资源研究所 |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/213882 |
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]. 中国科学院地理科学与资源研究所,2019,2019. |
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. |
MLA | Li, Yuanzheng,et al."Associated Determinants of Surface Urban Heat Islands across 1449 Cities in China".ADVANCES IN METEOROLOGY 2019(2019). |
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