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dc.contributor.authorHidalgo García, David 
dc.contributor.authorArco Díaz, Julián 
dc.date.accessioned2021-04-23T10:25:45Z
dc.date.available2021-04-23T10:25:45Z
dc.date.issued2021
dc.identifier.citationHidalgo García, D.; Arco Díaz, J. Spatial and Multi-Temporal Analysis of Land Surface Temperature through Landsat 8 Images: Comparison of Algorithms in a Highly Polluted City (Granada). Remote Sens. 2021, 13, 1012. https:// doi.org/10.3390/rs13051012es_ES
dc.identifier.urihttp://hdl.handle.net/10481/68076
dc.description.abstractOver 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.es_ES
dc.description.sponsorshipERDF (European Rural Development Fund)es_ES
dc.description.sponsorshipMinistry of Science and Innovation (State Research Agency) EQC2018-004702-Pes_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsAtribución 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectLandsat 8 imageses_ES
dc.subjectPanel data analysises_ES
dc.subjectLand surface temperaturees_ES
dc.subjectLand surface temperaturees_ES
dc.titleSpatial and Multi-Temporal Analysis of Land Surface Temperature through Landsat 8 Images: Comparison of Algorithms in a Highly Polluted City (Granada)es_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.3390/rs13051012


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Atribución 3.0 España
Except where otherwise noted, this item's license is described as Atribución 3.0 España