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Time-series analyses of land surface temperature changes with Google Earth Engine in a mountainous region

2023Journal article Open access
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dc.contributor.authorAlmeida, Cátia Rodrigues de
dc.contributor.authorGarcia, Nuno
dc.contributor.authorCampos, João C.
dc.contributor.authorAlirio, João
dc.contributor.authorArenas-Castro, Salvador
dc.contributor.authorGonçalves, Artur
dc.contributor.authorSillero, Neftali
dc.contributor.authorTeodoro, Ana Cláudia
dc.date.accessioned2011-04-14T09:44:05Z
dc.date.available2011-04-14T09:44:05Z
dc.date.issued2023
dc.description.abstractStudying changes in temperature is fundamental for understanding its interactions with the environment and biodiversity. However, studies in mountainous areas are few, due to their complex formation and the difficulty of obtaining local data. We analysed changes in temperature over time in Montesinho Natural Park (MNP) (Braganca, Portugal), an important conservation area due to its high level of biodiversity. Specifically, we aimed to analyse: i) whether temper-ature increased in MNP over time, ii) what environmental factors influence the Land Surface Temperature (LST), and iii) whether vegetation is related to changes in temperature. We used annual summer and winter mean data acquired from the Moderate-Resolution Imaging Spec-troradiometer (MODIS) datasets/products (e.g. LST, gathered at four different times: 11am, 1pm, 10pm and 2am, Enhance vegetation index -EVI, and Evapotranspiration -ET), available on the cloud-based platform Google Earth Engine between 2003 and 2021). We analysed the dynamics of the temporal trend patterns between the LST and local thermal data (from a weather station) by correlations; the trends in LST over time with the Mann-Kendall trend test; and the stability of hot spots and cold spots of LST with Local Statistics of Spatial Association (LISA) tests. The temporal trend patterns between LST and Air Temperature (Tair) data were very similar (& rho; > 0.7). The temperature in the MNP remained stable over time during summer but increased during winter nights. The biophysical indices were strongly correlated with the summer LST at 11am and 1pm. The LISA results identified hot and cold zones that remained stable over time. The remote-sensed data proved to be efficient in measuring changes in temperature over time.por
dc.description.sponsorshipThis research was supported by Portuguese national funds through FCT 􀀀 Foundation for Science and Technology I.P., Portugal under the project MontObEO - Montesinho biodiversity observatory: an Earth Observation tool for biodiversity conservation (FCT: MTS/BRB/0091/2020). This publication is also part of the TED2021-131722B-I00 project, funded by MCIN/AEI/10.13039/ 501100011033 and by the European Union “NextGenerationEU”/PRTR. Recovery, Transformation and Resilience Plan - Funded by the European Union – NextGenerationEU. CRdA was financially supported by Portuguese national funds through FCT - Foundation for Science and Technology I.P. (Grant: PRT/BD/153518/2021). JCC is supported by a contract under the scope of the MontObEO Project (MTS/BRB/0091/2020), funded by FCT. SAC is supported by the María Zambrano program funded by the Spanish Ministry of Universities and the University of Cordoba (Spain) (Next Generation EU fund). NS is supported by a CEEC2017 contract (CEECIND/ 02213/2017) from FCT. NG is supported by a research grant from MontObEO project (MTS/BRB/0091/2020). CIMO is supported through national funds (UIDB/00690/2020 and UIDP/00690/2020) and SusTEC (LA/P/0007/2020).
dc.identifier.citationAlmeida, Cátia Rodrigues de; Garcia, Nuno; Campos, João C.; Alirio, João; Arenas-Castro, Salvador; Gonçalves, Artur; Sillero, Neftali; Teodoro, Ana Cláudia (2023). Time-series analyses of land surface temperature changes with Google Earth Engine in a mountainous region. Heliyon. eISSN 2405-8440. 9:8, p. 1-18por
dc.identifier.doi10.1016/j.heliyon.2023.e18846
dc.identifier.eissn2405-8440
dc.identifier.urihttp://hdl.handle.net/10198/4047
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherElsevier
dc.subjectTemperature seasonality analysispor
dc.subjectAir temperaturepor
dc.subjectMODIS datapor
dc.subjectMontesinho natural park statistical analysispor
dc.subjectVegetation indexespor
dc.titleTime-series analyses of land surface temperature changes with Google Earth Engine in a mountainous regionpor
dc.typejournal article
dspace.entity.typePublication
oaire.citation.titleHeliyonpor
person.familyNameGonçalves
person.givenNameArtur
person.identifier.ciencia-idBC10-99F9-B30E
person.identifier.orcid0000-0002-4825-6692
person.identifier.scopus-author-id57195970669
rcaap.rightsopenAccesspor
rcaap.typearticlepor
relation.isAuthorOfPublication45f8c47c-b6ad-499a-99e7-4057e7aa8c2a
relation.isAuthorOfPublication.latestForDiscovery45f8c47c-b6ad-499a-99e7-4057e7aa8c2a

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