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Investigation and Prediction of the Land Use/Land Cover (LU/LC) and Land Surface Temperature (LST) Changes for Mashhad City in Iran during 1990–2030

2023-04-19Artigo científico Acesso aberto
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dc.contributor.authorMansourmoghaddam, Mohammad
dc.contributor.authorRousta, Iman
dc.contributor.authorCabral, Pedro
dc.contributor.authorAli, Ashehad A.
dc.contributor.authorOlafsson, Haraldur
dc.contributor.authorZhang, Hao
dc.contributor.authorKrzyszczak, Jaromir
dc.contributor.institutionNOVA Information Management School (NOVA IMS)
dc.contributor.institutionInformation Management Research Center (MagIC) - NOVA Information Management School
dc.contributor.pblMDPI - Multidisciplinary Digital Publishing Institute
dc.date.accessioned2023-04-26T22:21:07Z
dc.date.available2023-04-26T22:21:07Z
dc.date.issued2023-04-19
dc.descriptionMansourmoghaddam, M., Rousta, I., Cabral, P., Ali, A. A., Olafsson, H., Zhang, H., & Krzyszczak, J. (2023). Investigation and Prediction of the Land Use/Land Cover (LU/LC) and Land Surface Temperature (LST) Changes for Mashhad City in Iran during 1990–2030. Atmosphere, 14(4), 1-21. [741]. https://doi.org/10.3390/atmos14040741 --- Funding: This study was supported by the Shanghai Municipal Science and Technology Commission within the international cooperation framework of the Youth Scientists from the “One Atmosphere 2023, 14, 741 18 of 21 Belt and One Road” countries (2020–2023), and partially supported by the FCT (Fundação para a Ciência e a Tecnologia) under the project UIDB/04152/2020—Centro de Investigação em Gestão de Informação (MagIC).
dc.description.abstractStudies on how cities are affected by urban heat islands (UHI) are critical nowadays for a better understanding of the connected effects and for providing helpful insights for sustainable city development planning. In this study, Landsat-5 Thematic Mapper (TM), Landsat-7 Enhanced Thematic Mapper+ (ETM+), and Landsat-8 Operational Land Imager (OLI) images were used to assess the dynamics of the spatiotemporal pattern of land use/land cover (LU/LC) and land surface temperature (LST) in the metropolitan city of Mashhad, Iran in the period between 1990 and 2019. The Markov chain model (MCM) was used to predict LU/LC and LST for 2030. In the analyzed LU/LC maps, three LU/LC classes were distinguished, including built-up land (BUL), vegetated land (VL), and bare land (BL) using the maximum likelihood (ML) classification method. The collected data showed different variations in the geographical pattern of Mashhad LST during the research period that impacted the LST in this metropolis. The study evaluated the variations in LU/LC classes and evaluated their impact on the LST. The value of the LST was positively correlated with the occurrence of the built-up land (BUL), and with the bare land areas, while it was negatively correlated with the occurrence of the VL areas. The analysis of changes observed over three decades with 10-year intervals and the prediction of the LU/LC and LST for 2030 constitute an important contribution to the delineation of the dynamics of long LU/LC and LST records. These innovative results may have an important impact on policymaking fostering environmental sustainability, such as the control and management of urban expansion of Mashhad in connection with UHI.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent21
dc.format.extent4661309
dc.identifier.doi10.3390/atmos14040741
dc.identifier.issn2073-4433
dc.identifier.otherPURE: 59395477
dc.identifier.otherPURE UUID: ed8f593a-b21c-4be6-8f1c-cc387afa7a65
dc.identifier.othercrossref: 10.3390/atmos14040741
dc.identifier.otherScopus: 85156197254
dc.identifier.otherWOS: 000979469500001
dc.identifier.otherORCID: /0000-0001-8622-6008/work/151423457
dc.identifier.urihttp://hdl.handle.net/10362/152171
dc.identifier.urlhttps://www.scopus.com/pages/publications/85156197254
dc.identifier.urlhttps://www.webofscience.com/wos/woscc/full-record/WOS:000979469500001
dc.identifier.urlhttps://www.mdpi.com/2073-4433/14/4/741
dc.language.isoeng
dc.peerreviewedyes
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04152%2F2020/PT
dc.relationInformation Management Research Center
dc.subjectMaximum Likelihood Classification
dc.subjectMarkov chain
dc.subjectLand-cover change forecast
dc.subjectland surface temperature change forecast
dc.subjectpopulation shift
dc.subjectMashhad City
dc.subjectEnvironmental Science (miscellaneous)
dc.subjectAtmospheric Science
dc.subjectSDG 11 - Sustainable Cities and Communities
dc.subjectSDG 15 - Life on Land
dc.titleInvestigation and Prediction of the Land Use/Land Cover (LU/LC) and Land Surface Temperature (LST) Changes for Mashhad City in Iran during 1990–2030en
dc.typejournal article
degois.publication.firstPage1
degois.publication.issue4
degois.publication.lastPage21
degois.publication.titleAtmosphere
degois.publication.volume14
dspace.entity.typePublication
oaire.awardNumberUIDB/04152/2020
oaire.awardTitleInformation Management Research Center
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04152%2F2020/PT
oaire.fundingStream6817 - DCRRNI ID
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccess
relation.isProjectOfPublication3274bdb3-4dd3-4bbe-8f74-d34190081f87
relation.isProjectOfPublication.latestForDiscovery3274bdb3-4dd3-4bbe-8f74-d34190081f87

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