Quantifying and simulating landscape composition and pattern impacts on land surface temperature: A decadal study of the rapidly urbanizing city of Beijing, China

Lijia Guo; Ruimin Liu; Cong Men; Qingrui Wang; Yuexi Miao; Yan Zhang

doi:10.1016/j.scitotenv.2018.11.108

Quantifying and simulating landscape composition and pattern impacts on land surface temperature: A decadal study of the rapidly urbanizing city of Beijing, China

Sci Total Environ. 2019 Mar 1:654:430-440. doi: 10.1016/j.scitotenv.2018.11.108. Epub 2018 Nov 10.

Authors

Lijia Guo¹, Ruimin Liu², Cong Men¹, Qingrui Wang¹, Yuexi Miao¹, Yan Zhang¹

Affiliations

¹ State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China.
² State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China. Electronic address: liurm@bnu.edu.cn.

PMID: 30447581
DOI: 10.1016/j.scitotenv.2018.11.108

Abstract

The increase in impervious surfaces due to the urbanization has caused many adverse effects on urban ecological systems, including the urban heat environmental risk. Revealing the relationship between landscape composition and pattern and land surface temperature (LST) gives insight into how to effectively mitigate the urban heat island (UHI) effect. It is also essential to simulate and optimize the distribution of impervious surfaces in urban planning. In this study, the multi-scale relationship between impervious surface and LST in Beijing was analyzed. Different distributions of land cover types and the corresponding LSTs were simulated under two development scenarios. Various geospatial approaches, including geographic information system (GIS), remote sensing, and the Conversion of Land Use and its Effects at Small regional extent (CLUE-S), were used to facilitate the analysis. The results showed that (1) impervious surfaces increased from 36.76% to 44.95% of the total area between 2005 and 2015 and the mean LST of impervious surfaces was approximately 2 °C higher than that of the areas with vegetation cover; (2) impervious surfaces had a positive logarithmic correlation with LST, while the vegetation coverage had a negative linear correlation with LST; (3) as the grid size increased, the correlation coefficients between the impervious surface density and mean LST increased at different magnitudes, and the correlation coefficients stabilized after the scale of 900 × 900 m; (4) large and contiguous patches of impervious surfaces aggravated the UHI effect when the total percentage of impervious surface remained the same; and (5) to achieve an improved and healthier urban living environment, populations controls should be considered to decrease future impervious surface demands by 7.69%-which corresponds to an average LST decrease of 1.1 °C. Landscape distribution and configuration should also be better integrated into landscape and urban planning.

Keywords: Impervious surface area; Land surface temperature; Land use simulation; Multi-scale relationship; Remote sensing; Urbanization.