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      Google Earth Engine Open-Source Code for Land Surface Temperature Estimation from the Landsat Series

      , , , ,
      Remote Sensing
      MDPI AG

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          Abstract

          Land Surface Temperature (LST) is increasingly important for various studies assessing land surface conditions, e.g., studies of urban climate, evapotranspiration, and vegetation stress. The Landsat series of satellites have the potential to provide LST estimates at a high spatial resolution, which is particularly appropriate for local or small-scale studies. Numerous studies have proposed LST retrieval algorithms for the Landsat series, and some datasets are available online. However, those datasets generally require the users to be able to handle large volumes of data. Google Earth Engine (GEE) is an online platform created to allow remote sensing users to easily perform big data analyses without increasing the demand for local computing resources. However, high spatial resolution LST datasets are currently not available in GEE. Here we provide a code repository that allows computing LSTs from Landsat 4, 5, 7, and 8 within GEE. The code may be used freely by users for computing Landsat LST as part of any analysis within GEE.

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          Most cited references60

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          On the relation between NDVI, fractional vegetation cover, and leaf area index

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            Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors

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              Land surface temperature retrieval from LANDSAT TM 5

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                Author and article information

                Journal
                Remote Sensing
                Remote Sensing
                MDPI AG
                2072-4292
                May 2020
                May 06 2020
                : 12
                : 9
                : 1471
                Article
                10.3390/rs12091471
                54f94425-9362-4457-a7e5-89985f54d9b9
                © 2020

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

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