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

Ermida, Sofia L.; Soares, Patrícia; Mantas, Vasco; Göttsche, Frank-M.; Trigo, Isabel F.


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.

Verlagsausgabe §
DOI: 10.5445/IR/1000119089
Veröffentlicht am 07.05.2020
DOI: 10.3390/rs12091471
Zitationen: 122
Zitationen: 135
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung – Atmosphärische Spurenstoffe und Fernerkundung (IMK-ASF)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 2072-4292
KITopen-ID: 1000119089
HGF-Programm 12.01.01 (POF III, LK 01) Clouds in a pertubed atmosphere
Erschienen in Remote sensing
Verlag MDPI
Band 12
Heft 9
Seiten 1471
Bemerkung zur Veröffentlichung This article belongs to the Collection Google Earth Engine Applications
Vorab online veröffentlicht am 06.05.2020
Schlagwörter Land Surface Temperature; Landsat; Google Earth Engine; ASTER GED; high resolution
Nachgewiesen in Dimensions
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