Long-term analysis of the urban heat island effect using multisource Landsat images considering inter-class differences in land surface temperature products

Xiong Xu; Haoyang Pei; Chao Wang; Qingyu Xu; Huan Xie; Yanmin Jin; Yongjiu Feng; Xiaohua Tong; Changjiang Xiao

doi:10.1016/j.scitotenv.2022.159777

Long-term analysis of the urban heat island effect using multisource Landsat images considering inter-class differences in land surface temperature products

Sci Total Environ. 2023 Feb 1;858(Pt 1):159777. doi: 10.1016/j.scitotenv.2022.159777. Epub 2022 Oct 26.

Authors

Xiong Xu¹, Haoyang Pei², Chao Wang³, Qingyu Xu², Huan Xie⁴, Yanmin Jin⁴, Yongjiu Feng¹, Xiaohua Tong¹, Changjiang Xiao¹

Affiliations

¹ College of Surveying and Geo-informatics, Tongji University, Shanghai 200092, China; Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, Tongji University, Shanghai 200092, China; Frontiers Science Center for Intelligent Autonomous Systems, Tongji University, Shanghai 201210, China.
² College of Surveying and Geo-informatics, Tongji University, Shanghai 200092, China.
³ College of Surveying and Geo-informatics, Tongji University, Shanghai 200092, China; Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, Tongji University, Shanghai 200092, China. Electronic address: wangchao2019@tongji.edu.cn.
⁴ College of Surveying and Geo-informatics, Tongji University, Shanghai 200092, China; Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, Tongji University, Shanghai 200092, China.

PMID: 36309260
DOI: 10.1016/j.scitotenv.2022.159777

Abstract

It is imperative to quantitatively analyze the long-term temporal and spatial characteristics of the urban heat island (UHI) effect on cities for applications, such as urban expansion and environmental protection. Owing to the high spatial resolution and availability of long time-series data, remote sensing images from Landsat satellites are widely used for land surface temperature (LST) retrieval. However, limited by the satellite revisit cycle and image quality, the use of multisource Landsat images in a long-term study of the UHI effect is inevitable. Nonetheless, owing to the differences among multisource sensors, such as Landsat-7 and Landsat-8, there may be apparent deviations in the LST results retrieved from different sensor data, which are obtained from the same area and under similar circumstances. Consequently, it is necessary to build a relationship between the LST results generated from multisource Landsat sensors for future research on the UHI effect. In this study, Shenzhen city was studied to explore the fitting relationship between the corresponding LST products from Landsat-7 and Landsat-8 images obtained from adjacent dates with similar climatic conditions. Furthermore, factors affecting the fitting models, such as land cover types, seasonal and inter-annual differences, were analyzed. The constructed fitting model had a strong relationship with land cover types but a relatively weak relationship with seasonal and inter-annual differences; this indicates that a pseudo Landsat-8-based LST product can be generated from a Landsat-7-based LST product using a model fitted by a Landsat-7/8 pair obtained from adjacent years (or different seasons). Finally, by considering the consistency between LST products from multisource Landsat images, the spatiotemporal variations in the UHI effect in Shenzhen can be accurately explored using long time-series data.

Keywords: Fitted models; Long-term analysis; Multisource Landsat images; Urban heat island effect.

MeSH terms

Cities
Environmental Monitoring / methods
Hot Temperature*
Temperature
Urbanization*