Remote sensing evaluation of land surface temperature and urban area expansion in Zhengzhou city during 2013-2015

Sheheryar Khan; Sajid Gul; Weidong Li

doi:10.47264/idea.nasij/2.1.4

Authors

Sheheryar Khan College of Information Engineering, Henan University of Technology, Zhengzhou, China | Key Laboratory of Grain Information Processing and Control, Henan University of Technology, Zhengzhou, China.
Sajid Gul School of Mathematics and Statistics, Zhengzhou University, Zhengzhou, China.
Weidong Li College of Information Engineering, Henan University of Technology, Zhengzhou, China | Key Laboratory of Grain Information Processing and Control, Henan University of Technology, Zhengzhou, China. https://orcid.org/0000-0001-5618-9154

DOI:

https://doi.org/10.47264/idea.nasij/2.1.4

Keywords:

Landsat 8, remote sensing, surface temperature, land surface temperature, mono-window algorithm, challenges of urbanisation

Abstract

The Urban Heat Island (UHI) concept is one of the most serious ecological and social challenges of the urbanisation. As a result of these events, several man-made urban areas have displaced the rural areas with increased thermal conductivity surfaces, resulting in higher temperatures in the urban areas. Thus, this paper analyses the variations in Land Surface Temperature (LST) and the heat island area using Landsat 8 data and NPP VIIRS night-time light data. The data sources during 2013-2015 of Zhengzhou city, China, are selected to be a case study in this research work. According to the research, the economic centre of Zhengzhou city is shifting eastward, and the mean centre of urban area acquired from NPP VIIRS night-light data is extremely similar to the heat island area derived from Landsat 8 data. Also, the heat island areas obtained from the NPP VIIRS night-light data, and the yearbook data of Zhengzhou Bureau of Statistics are comparable with the accuracies of 96-99%. Hence, our proposed procedure can be implemented practically to point out the urban areas, to identify the UHI areas with high accuracies in other regions and also can be used to indicate how large the UHI effects on the urban area with increased population and industries.

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