Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/106655
DC FieldValueLanguage
dc.contributor.authorErmida, Sofia L.-
dc.contributor.authorSoares, Patrícia-
dc.contributor.authorMantas, Vasco-
dc.contributor.authorGöttsche, Frank-M.-
dc.contributor.authorTrigo, Isabel F.-
dc.date.accessioned2023-04-14T08:55:32Z-
dc.date.available2023-04-14T08:55:32Z-
dc.date.issued2020-
dc.identifier.issn2072-4292pt
dc.identifier.urihttps://hdl.handle.net/10316/106655-
dc.description.abstractLand 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.pt
dc.language.isoengpt
dc.publisherMDPIpt
dc.relationPTDC/CTA-MET/28946/2017pt
dc.rightsopenAccesspt
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt
dc.subjectLand Surface Temperaturept
dc.subjectLandsatpt
dc.subjectGoogle Earth Enginept
dc.subjectASTER GEDpt
dc.subjecthigh resolutionpt
dc.titleGoogle Earth Engine Open-Source Code for Land Surface Temperature Estimation from the Landsat Seriespt
dc.typearticle-
degois.publication.firstPage1471pt
degois.publication.issue9pt
degois.publication.titleRemote Sensingpt
dc.peerreviewedyespt
dc.identifier.doi10.3390/rs12091471pt
degois.publication.volume12pt
dc.date.embargo2020-01-01*
uc.date.periodoEmbargo0pt
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextCom Texto completo-
item.openairetypearticle-
item.cerifentitytypePublications-
item.languageiso639-1en-
crisitem.author.orcid0000-0002-6109-4958-
Appears in Collections:FCTUC Ciências da Terra - Artigos em Revistas Internacionais
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This item is licensed under a Creative Commons License Creative Commons