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      Satellite-Derived Land Surface Temperature Dynamics in the Context of Global Change—A Review

      , ,
      Remote Sensing
      MDPI AG

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          Abstract

          Satellite-derived Land Surface Temperature (LST) dynamics have been increasingly used to study various geophysical processes. This review provides an extensive overview of the applications of LST in the context of global change. By filtering a selection of relevant keywords, a total of 164 articles from 14 international journals published during the last two decades were analyzed based on study location, research topic, applied sensor, spatio-temporal resolution and scale and employed analysis methods. It was revealed that China and the USA were the most studied countries and those that had the most first author affiliations. The most prominent research topic was the Surface Urban Heat Island (SUHI), while the research topics related to climate change were underrepresented. MODIS was by far the most used sensor system, followed by Landsat. A relatively small number of studies analyzed LST dynamics on a global or continental scale. The extensive use of MODIS highly determined the study periods: A majority of the studies started around the year 2000 and thus had a study period shorter than 25 years. The following suggestions were made to increase the utilization of LST time series in climate research: The prolongation of the time series by, e.g., using AVHRR LST, the better representation of LST under clouds, the comparison of LST to traditional climate change measures, such as air temperature and reanalysis variables, and the extension of the validation to heterogenous sites.

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          Most cited references194

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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Remote Sensing
                Remote Sensing
                MDPI AG
                2072-4292
                April 2023
                March 30 2023
                : 15
                : 7
                : 1857
                Article
                10.3390/rs15071857
                a26dd75e-8b35-4238-b77c-2459178be937
                © 2023

                https://creativecommons.org/licenses/by/4.0/

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