Research on the Contribution of Urban Land Surface Moisture to the Alleviation Effect of Urban Land Surface Heat Based on Landsat 8 Data

Yu Zhang; Longqian Chen; Yuchen Wang; Longgao Chen; Fei Yao; Peiyao Wu; Bingyi Wang; Yuanyuan Li; Tianjian Zhou; Ting Zhang

doi:10.3390/rs70810737

Remote Sensing (Aug 2015)

Research on the Contribution of Urban Land Surface Moisture to the Alleviation Effect of Urban Land Surface Heat Based on Landsat 8 Data

Yu Zhang,
Longqian Chen,
Yuchen Wang,
Longgao Chen,
Fei Yao,
Peiyao Wu,
Bingyi Wang,
Yuanyuan Li,
Tianjian Zhou,
Ting Zhang

Affiliations

Yu Zhang: Jiangsu Key Laboratory of Resources and Environmental Information Engineering, School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
Longqian Chen: Jiangsu Key Laboratory of Resources and Environmental Information Engineering, School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
Yuchen Wang: Jiangsu Key Laboratory of Resources and Environmental Information Engineering, School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
Longgao Chen: Land Resources Research Institute, Jiangsu Normal University, Xuzhou 221116, China
Fei Yao: Jiangsu Key Laboratory of Resources and Environmental Information Engineering, School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
Peiyao Wu: Jiangsu Key Laboratory of Resources and Environmental Information Engineering, School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
Bingyi Wang: Jiangsu Key Laboratory of Resources and Environmental Information Engineering, School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
Yuanyuan Li: Jiangsu Key Laboratory of Resources and Environmental Information Engineering, School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
Tianjian Zhou: Jiangsu Key Laboratory of Resources and Environmental Information Engineering, School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
Ting Zhang: Jiangsu Key Laboratory of Resources and Environmental Information Engineering, School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China

DOI: https://doi.org/10.3390/rs70810737
Journal volume & issue: Vol. 7, no. 8
pp. 10737 – 10762

Abstract

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This paper presents a new assessment method for alleviating urban heat island (UHI) effects by using an urban land surface moisture (ULSM) index. With the aid of Landsat 8 OLI/TIRS data, the land surface temperature (LST) was retrieved by a mono-window algorithm, and ULSM was extracted by tasselled cap transformation. Polynomial regression and buffer analysis were used to analyze the effects of ULSM on the LST, and the alleviation effect of ULSM was compared with three vegetation indices, GVI, SAVI, and FVC, by using the methods of grey relational analysis and Taylor skill calculation. The results indicate that when the ULSM value is greater than the value of an extreme point, the LST declines with the increasing ULSM value. Areas with a high ULSM value have an obvious reducing effect on the temperature of their surrounding areas within 150 m. Grey relational degrees and Taylor skill scores between ULSM and the LST are 0.8765 and 0.9378, respectively, which are higher than the results for the three vegetation indices GVI, SAVI, and FVC. The reducing effect of the ULSM index on environmental temperatures is significant, and ULSM can be considered to be a new and more effective index to estimate UHI alleviation effects for urban areas.

Published in Remote Sensing

ISSN: 2072-4292 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Science
Website: http://www.mdpi.com/journal/remotesensing/

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