Spatiotemporal Analysis of Land Use/Land Cover and Its Effects on Surface Urban Heat Island Using Landsat Data: A Case Study of Metropolitan City Tehran (1988–2018)

dc.contributorHáskóli Íslandsen_US
dc.contributorUniversity of Icelanden_US
dc.contributor.authorRousta, Iman
dc.contributor.authorSarif, Md
dc.contributor.authorGupta, Rajan
dc.contributor.authorOlafsson, Haraldur
dc.contributor.authorRanagalage, Manjula
dc.contributor.authorMurayama, Yuji
dc.contributor.authorZhang, Hao
dc.contributor.authorMushore, Terence
dc.contributor.departmentRaunvísindadeild (HÍ)en_US
dc.contributor.departmentFaculty of Physical Sciences (UI)en_US
dc.contributor.schoolVerkfræði- og náttúruvísindasvið (HÍ)en_US
dc.contributor.schoolSchool of Engineering and Natural Sciences (UI)en_US
dc.date.accessioned2019-08-20T13:20:49Z
dc.date.available2019-08-20T13:20:49Z
dc.date.issued2018-11-27
dc.descriptionPublisher's version (útgefin grein)en_US
dc.description.abstractThis article summarized the spatiotemporal pattern of land use/land cover (LU/LC) and urban heat island (UHI) dynamics in the Metropolitan city of Tehran between 1988 and 2018. The study showed dynamics of each LU/LC class and their role in influencing the UHI. The impervious surface area expanded by 286.04 (48.27% of total land) and vegetated land was depleted by 42.06 km2 (7.10% of total land) during the period of 1988–2018. The mean land surface temperature (LST) has enlarged by approximately 2–3 °C at the city center and 5–7 °C at the periphery between 1988 and 2018 based on the urban–rural gradient analysis. The lower mean LST was experienced by vegetation land (VL) and water body (WB) by approximately 4–5 °C and 5–7 °C, respectively, and the higher mean LST by open land (OL) by 7–11 °C than other LU/LC classes at all time-points during the time period, 1988–2018. The magnitude of mean LST was calculated based on the main LU/LC categories, where impervious land (IL) recorded the higher temperature difference compared to vegetation land (VL) and water bodies (WB). However, open land (OL) recorded the highest mean LST differences with all the other LU/LC categories. In addition to that, there was an overall negative correlation between LST and the normal difference vegetation index (NDVI). By contrast, there was an overall positive correlation between LST and the normal difference built-up index (NDBI). This article, executed through three decadal change analyses from 1988 to 2018 at 10-year intervals, has made a significant contribution to delineating the long records of change dynamics and could have a great influence on policy making to foster environmental sustainability.en_US
dc.description.sponsorshipThis study was funded by the Original and Innovatory Research Program (2017–2019) of Fudan Universityen_US
dc.description.versionPeer Revieweden_US
dc.format.extent4433en_US
dc.identifier.citationRousta I, Sarif MO, Gupta RD, Olafsson H, Ranagalage M, Murayama Y, Zhang H, Mushore TD. Spatiotemporal Analysis of Land Use/Land Cover and Its Effects on Surface Urban Heat Island Using Landsat Data: A Case Study of Metropolitan City Tehran (1988–2018). Sustainability. 2018; 10(12):4433. doi:10.3390/su10124433en_US
dc.identifier.doi10.3390/su10124433
dc.identifier.issn2071-1050
dc.identifier.journalSustainabilityen_US
dc.identifier.urihttps://hdl.handle.net/20.500.11815/1223
dc.language.isoenen_US
dc.publisherMDPI AGen_US
dc.relation.ispartofseriesSustainability;10(12)
dc.relation.urlhttp://www.mdpi.com/2071-1050/10/12/4433/pdfen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectLU/LC dynamicsen_US
dc.subjectSUHIen_US
dc.subjectLSTen_US
dc.subjectNDVIen_US
dc.subjectNDBIen_US
dc.subjectTehranen_US
dc.subjectLandnýtingen_US
dc.subjectBorgiren_US
dc.subjectMannfjöldien_US
dc.titleSpatiotemporal Analysis of Land Use/Land Cover and Its Effects on Surface Urban Heat Island Using Landsat Data: A Case Study of Metropolitan City Tehran (1988–2018)en_US
dc.typeinfo:eu-repo/semantics/articleen_US
dcterms.licenseThis is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).en_US

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