Fractal and multifractal spatiotemporal patterns of land surface temperatures in a coastal city. Issue 1 (31st December 2022)

• Record Type: Journal Article
• Authors: Nie, Qin; Ran, Feipeng; Man, Wang; Li, Hui; Yuan, Ying; Hua, Lizhong
• Is Part Of: European journal of remote sensing. Volume 55:Issue 1(2022)
• Page Start: 429
• Page End: 439
• Publication Date: 2022-12-31
• Subjects: Land surface temperature -- spatiotemporal pattern -- fractal -- multifractal -- Xiamen city; Remote sensing -- Periodicals; Remote sensing; Electronic journals; Periodicals; 621.3678
• DOI: 10.1080/22797254.2022.2093277
• Languages: English
• ISSNs: 2279-7254

Abstract

ABSTRACT: In order to discover the fractal and multifractal nature of land surface temperature (LST) spatiotemporal patterns, this study computed the LST in thecoastal city, Xiamen, southeastern China using Landsat TM/OLI/TIRS images from 1994 to 2015, and introduced two-dimensional box-counting and two-dimensional multifractal box-counting methods to quantitatively characterize the LST pattern. Results suggest that increasing the binarization threshold decreased the box-counting dimensions with values from 1.86 to 1.65 in 1994, 1.67 in 2000, 1.56 in 2004, 1.57 in 2010, and 1.56 in 2015, respectively. The two-dimensional multifractal approach employs a set of intertwined nonfractal subsets over different spatial scales to describe the LST patterns. LST pattern possesses a increased multifractality and the similar multifractal spectra of left-hook shapes throughout the study period, suggesting the increasing trends of the spatial heterogeneity in LST distribution. The probability of a given pixel having a high LST value is consistently high in the study area, as indicated by the positive ratio between the regions in which the probability measure appears most concentrated and those in which it is most sparse. Rapid urbanization and the large-scale urban land surface changes in the coastal city determine the variation in the multifractal parameters.