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• W3136379894 endingPage "1012" @default.
• W3136379894 startingPage "1012" @default.
• W3136379894 abstract "Over the past decade, satellite imaging has become a habitual way to determine the land surface temperature (LST). One means entails the use of Landsat 8 images, for which mono window (MW), single channel (SC) and split window (SW) algorithms are needed. Knowing the precision and seasonal variability of the LST can improve urban climate alteration studies, which ultimately help make sustainable decisions in terms of the greater resilience of cities. In this study we determine the LST of a mid-sized city, Granada (Spain), applying six Landsat 8 algorithms that are validated using ambient temperatures. In addition to having a unique geographical location, this city has high pollution and high daily temperature variations, so that it is a very appropriate site for study. Altogether, 11 images with very low cloudiness were taken into account, distributed between November 2019 and October 2020. After data validation by means of R2 statistical analysis, the root mean square error (RMSE), mean bias error (MBE) and standard deviation (SD) were determined to obtain the coefficients of correlation. Panel data analysis is presented as a novel element with respect to the methods usually used. Results reveal that the SC algorithms prove more effective and reliable in determining the LST of the city studied here." @default.
• W3136379894 created "2021-03-29" @default.
• W3136379894 creator A5030948710 @default.
• W3136379894 creator A5064423221 @default.
• W3136379894 date "2021-03-07" @default.
• W3136379894 modified "2023-10-06" @default.
• W3136379894 title "Spatial and Multi-Temporal Analysis of Land Surface Temperature through Landsat 8 Images: Comparison of Algorithms in a Highly Polluted City (Granada)" @default.
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• W3136379894 doi "https://doi.org/10.3390/rs13051012" @default.
• W3136379894 hasPublicationYear "2021" @default.
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