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

• Published in: Land (Basel) Vol. 11; no. 8; p. 1312
• Main Authors: Li, Yuanzheng, Zhao, Zezhi, Xin, Yashu, Xu, Ao, Xie, Shuyan, Yan, Yi, Wang, Lan
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.08.2022
• Subjects: Archives & records; Atmospheric temperature; China; Climate change; Climatic zones; Correlation; Correlation analysis; Daytime; Environmental aspects; Global climate; land; Land cover; Land surface temperature; land surface temperatures; Land use; land use and land cover maps; Landsat; Metropolitan areas; NDBaI; NDBI; NDVI; NDWI; Night; Nighttime; Optimization; Remote sensing; Seasonal variations; soil; Soil analysis; Soil water; Soils; spectral indices; Summer; Surface temperature; Thermal comfort; Thermal environments; Urban areas; Urban environments; Urbanization; Vegetation; Vegetation index; winter; China; Asia; Europe
• DOI: 10.3390/land11081312
• ISSN: 2073-445X

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.