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Conference Paper: Temporal statistical analysis of urban heat islands at the microclimate level

TitleTemporal statistical analysis of urban heat islands at the microclimate level
Authors
Wong, PYPLai, PCHart, MA
KeywordsMicroclimate variation
Urban heat islands
Automatic linear regression
Issue Date2015
PublisherElsevier BV.
Citation
The 2015 Spatial Statistics Conference, Avignon, France, 9-12 June 2015. In Procedia Environmental Sciences, 2015, v. 26, p. 91-94 How to Cite?
DOI: http://dx.doi.org/10.1016/j.proenv.2015.05.006
AbstractUrban Heat Islands (UHI) represent the air temperature difference between urban and rural areas. This study deployed a network of miniature sensors to capture road-side microclimate data in both summer and winter. Temporal variations indicated UHI were evident for all time scales, with daily highest and lowest UHI at around midnight and noon/early afternoon respectively. Meteorological and environmental factors influencing UHI were also statistically analyzed by automatic linear regression models. Regression results suggested solar radiation and greenery density were the most important factors with a negative association with UHI intensities in both seasons.
DescriptionConference Theme: Emerging Patterns
This journal vol. entitled: Spatial Statistics Conference 2015
Persistent Identifierhttp://hdl.handle.net/10722/218234
ISSN
1878-0296
ISI Accession Number ID
WOS:000380492800018

 

DC FieldValueLanguage
dc.contributor.authorWong, PYP-
dc.contributor.authorLai, PC-
dc.contributor.authorHart, MA-
dc.date.accessioned2015-09-18T06:31:17Z-
dc.date.available2015-09-18T06:31:17Z-
dc.date.issued2015-
dc.identifier.citationThe 2015 Spatial Statistics Conference, Avignon, France, 9-12 June 2015. In Procedia Environmental Sciences, 2015, v. 26, p. 91-94-
dc.identifier.issn1878-0296-
dc.identifier.urihttp://hdl.handle.net/10722/218234-
dc.descriptionConference Theme: Emerging Patterns-
dc.descriptionThis journal vol. entitled: Spatial Statistics Conference 2015-
dc.description.abstractUrban Heat Islands (UHI) represent the air temperature difference between urban and rural areas. This study deployed a network of miniature sensors to capture road-side microclimate data in both summer and winter. Temporal variations indicated UHI were evident for all time scales, with daily highest and lowest UHI at around midnight and noon/early afternoon respectively. Meteorological and environmental factors influencing UHI were also statistically analyzed by automatic linear regression models. Regression results suggested solar radiation and greenery density were the most important factors with a negative association with UHI intensities in both seasons.-
dc.languageeng-
dc.publisherElsevier BV.-
dc.relation.ispartofProcedia Environmental Sciences-
dc.rights© 2015. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/-
dc.subjectMicroclimate variation-
dc.subjectUrban heat islands-
dc.subjectAutomatic linear regression-
dc.titleTemporal statistical analysis of urban heat islands at the microclimate level-
dc.typeConference_Paper-
dc.identifier.emailWong, PYP: paulinaw@connect.hku.hk-
dc.identifier.emailLai, PC: pclai@hku.hk-
dc.identifier.emailHart, MA: mhart@hku.hk-
dc.identifier.authorityLai, PC=rp00565-
dc.identifier.authorityHart, MA=rp00645-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1016/j.proenv.2015.05.006-
dc.identifier.hkuros252343-
dc.identifier.volume26-
dc.identifier.spage91-
dc.identifier.epage94-
dc.identifier.isiWOS:000380492800018-
dc.publisher.placeNetherlands-
dc.customcontrol.immutablesml 151216-
dc.identifier.issnl1878-0296-

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