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Article: A new method to quantify surface urban heat island intensity

TitleA new method to quantify surface urban heat island intensity
Authors
KeywordsFootprint of remote sensing observation
Impervious surface area
Kernel density estimation
Land surface temperature
Surface urban heat island
Issue Date2018
Citation
Science of the Total Environment, 2018, v. 624, p. 262-272 How to Cite?
AbstractReliable quantification of urban heat island (UHI) can contribute to the effective evaluation of potential heat risk. Traditional methods for the quantification of UHI intensity (UHII) using pairs-measurements are sensitive to the choice of stations or grids. In order to get rid of the limitation of urban/rural divisions, this paper proposes a new approach to quantify surface UHII (SUHII) using the relationship between MODIS land surface temperature (LST) and impervious surface areas (ISA). Given the footprint of LST measurement, the ISA was regionalized to include the information of neighborhood pixels using a Kernel Density Estimation (KDE) method. Considering the footprint improves the LST-ISA relationship. The LST shows highly positive correlation with the KDE regionalized ISA (ISA KDE ). The linear functions of LST are well fitted by the ISA KDE in both annual and daily scales for the city of Berlin. The slope of the linear function represents the increase in LST from the natural surface in rural regions to the impervious surface in urban regions, and is defined as SUHII in this study. The calculated SUHII show high values in summer and during the day than in winter and at night. The new method is also verified using finer resolution Landset data, and the results further prove its reliability.
Persistent Identifierhttp://hdl.handle.net/10722/329481
ISSN
2023 Impact Factor: 8.2
2023 SCImago Journal Rankings: 1.998
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, Huidong-
dc.contributor.authorZhou, Yuyu-
dc.contributor.authorLi, Xiaoma-
dc.contributor.authorMeng, Lin-
dc.contributor.authorWang, Xun-
dc.contributor.authorWu, Sha-
dc.contributor.authorSodoudi, Sahar-
dc.date.accessioned2023-08-09T03:33:06Z-
dc.date.available2023-08-09T03:33:06Z-
dc.date.issued2018-
dc.identifier.citationScience of the Total Environment, 2018, v. 624, p. 262-272-
dc.identifier.issn0048-9697-
dc.identifier.urihttp://hdl.handle.net/10722/329481-
dc.description.abstractReliable quantification of urban heat island (UHI) can contribute to the effective evaluation of potential heat risk. Traditional methods for the quantification of UHI intensity (UHII) using pairs-measurements are sensitive to the choice of stations or grids. In order to get rid of the limitation of urban/rural divisions, this paper proposes a new approach to quantify surface UHII (SUHII) using the relationship between MODIS land surface temperature (LST) and impervious surface areas (ISA). Given the footprint of LST measurement, the ISA was regionalized to include the information of neighborhood pixels using a Kernel Density Estimation (KDE) method. Considering the footprint improves the LST-ISA relationship. The LST shows highly positive correlation with the KDE regionalized ISA (ISA KDE ). The linear functions of LST are well fitted by the ISA KDE in both annual and daily scales for the city of Berlin. The slope of the linear function represents the increase in LST from the natural surface in rural regions to the impervious surface in urban regions, and is defined as SUHII in this study. The calculated SUHII show high values in summer and during the day than in winter and at night. The new method is also verified using finer resolution Landset data, and the results further prove its reliability.-
dc.languageeng-
dc.relation.ispartofScience of the Total Environment-
dc.subjectFootprint of remote sensing observation-
dc.subjectImpervious surface area-
dc.subjectKernel density estimation-
dc.subjectLand surface temperature-
dc.subjectSurface urban heat island-
dc.titleA new method to quantify surface urban heat island intensity-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.scitotenv.2017.11.360-
dc.identifier.pmid29253774-
dc.identifier.scopuseid_2-s2.0-85037983565-
dc.identifier.volume624-
dc.identifier.spage262-
dc.identifier.epage272-
dc.identifier.eissn1879-1026-
dc.identifier.isiWOS:000426355900028-

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