Comparison of different spatial temperature data sources and resolutions for use in understanding intra-urban heat variation

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dc.contributor.authorKianmehr, Aydaen
dc.contributor.authorLim, Theodore C.en
dc.contributor.authorLi, Xiaojiangen
dc.date.accessioned2023-06-30T13:40:15Zen
dc.date.available2023-06-30T13:40:15Zen
dc.date.issued2023-09en
dc.description.abstractIn this study, we investigate the compatibility of specific vulnerability indicators and heat exposure data and the suitability of spatial temperature-related data at a range of resolutions, to represent spatial temperature variations within cities using data from Atlanta, Georgia. For this purpose, we include various types of known and theoretically based vulnerability indicators such as specific street-level landscape features and urban form metrics, population-based and zone-based variables as predictors, and different measures of temperature, including air temperature (as vector-based data), land surface temperature (at resolution ranges from 30 m to 305 m), and mean radiant temperature (at resolution ranges from 1 m to 39 m) as dependent variables. Using regression analysis, we examine how different sets of predictors and spatial resolutions can explain spatial heat variation. Our findings suggest that the lower resolution of land surface temperature data, up to 152 m, and mean radiant temperature data, up to 15 m, may still satisfactorily represent spatial urban temperature variation caused by landscape elements. The results of this study have important implications for heat-related policies and planning by providing insights into the appropriate sets of data and relevant resolution of temperature measurements for representing spatial urban heat variations.en
dc.description.notesThis material is partially supported by the National Science Foundation under Grant Number 1735139. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Theodore Lim's time was partially supported by a seed grant from Virginia Tech 's Institute for Society, Culture, and Environment. We would also like to thank Meng Qi (School of Public and International Affairs at Virginia Tech) for providing technical support and Temple University High-Performance and Scientific Computing Cluster for providing the computing resources. We also thank four anonymous reviewers of the Sustainable Cities and Society journal for their insightful comments and suggestions.en
dc.description.sponsorshipNational Science Foundation [1735139]; Virginia Tech 's Institute for Society, Culture, and Environmenten
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1016/j.scs.2023.104619en
dc.identifier.eissn2210-6715en
dc.identifier.issn2210-6707en
dc.identifier.other104619en
dc.identifier.urihttp://hdl.handle.net/10919/115605en
dc.identifier.volume96en
dc.language.isoenen
dc.publisherElsevieren
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectSpatial resolutionen
dc.subjectUrban heat variationen
dc.subjectVulnerability indicatorsen
dc.subjectStreet -level featuresen
dc.titleComparison of different spatial temperature data sources and resolutions for use in understanding intra-urban heat variationen
dc.title.serialSustainable Cities and Societyen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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