How Are Land-Use/Land-Cover Indices and Daytime and Nighttime Land Surface Temperatures Related in Eleven Urban Centres in Different Global Climatic Zones?

Yuanzheng Li, Zezhi Zhao, Yashu Xin, Ao Xu, Shuyan Xie, Yi Yan and Lan Wang ()
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Yuanzheng Li: School of Resources and Environment, Henan University of Economics and Law, Zhengzhou 450046, China
Zezhi Zhao: School of Resources and Environment, Henan University of Economics and Law, Zhengzhou 450046, China
Yashu Xin: School of Resources and Environment, Henan University of Economics and Law, Zhengzhou 450046, China
Ao Xu: School of Resources and Environment, Henan University of Economics and Law, Zhengzhou 450046, China
Shuyan Xie: School of Resources and Environment, Henan University of Economics and Law, Zhengzhou 450046, China
Yi Yan: Key Laboratory of Resources Conversion and Pollution Control of the State Ethnic Affairs Commission, College of Resources and Environmental Science, South-Central Minzu University, Wuhan 430074, China
Lan Wang: Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization Jointly Built by Henan Province and Ministry of Education, Henan University, Kaifeng 475001, China

Land, 2022, vol. 11, issue 8, 1-22

Abstract: Improving the urban thermal environment can enhance humans’ well-being. Nevertheless, it was not clear which land-use/land-cover (LU/LC) indices were optimal for explaining land surface temperatures (LSTs) and how they affected LSTs in cities in different climatic zones, especially during the nighttime. Thus, the Aqua/MODIS and Landsat/OLI data were mainly used to explore the optimal indices of building, vegetation, water and bare soil and to analyze their effects on LSTs in eleven urban centers in global distinct climatic regions. Results showed several LU/LC indices had high probabilities of being optimal indices to explain LSTs under different conditions. The daytime LSTs were usually significantly negatively correlated with vegetation indices and positively correlated with building and bare soil indices ( p < 0.05). These relationships were stronger in the summer than winter. The nighttime LSTs were usually significantly positively and negatively correlated with building and vegetation indices in the summer, respectively ( p < 0.05). These correlations were generally weaker during the nighttime than daytime. The nighttime LSTs were significantly positively and negatively correlated with water and bare soil indices, respectively ( p < 0.05). Significant linear multiple regressions commonly existed between daytime and nighttime LSTs and four kinds of LU/LC indices ( p < 0.05). These findings helped optimize urban thermal comfort, downscale city LSTs, etc.

Keywords: land surface temperatures; NDBI; NDVI; NDWI; NDBaI; spectral indices; land surface indices; daytime and nighttime; partial correlation analysis; urban heat islands (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:11:y:2022:i:8:p:1312-:d:887927

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