Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/113848
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorRamsay, EEen_US
dc.creatorWang, Yen_US
dc.creatorMasoudi, Men_US
dc.creatorChai, MWen_US
dc.creatorYin, Ten_US
dc.creatorHamel, Pen_US
dc.date.accessioned2025-06-25T08:30:37Z-
dc.date.available2025-06-25T08:30:37Z-
dc.identifier.issn2210-6707en_US
dc.identifier.urihttp://hdl.handle.net/10397/113848-
dc.language.isoenen_US
dc.publisherElsevier BVen_US
dc.rights© 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Ramsay, E. E., Wang, Y., Masoudi, M., Chai, M. W., Yin, T., & Hamel, P. (2025). Assessing a decision-support tool to estimate the cooling potential and economic savings from urban vegetation in Singapore. Sustainable Cities and Society, 125, 106337 is available at https://doi.org/10.1016/j.scs.2025.106337.en_US
dc.subjectGreen spaceen_US
dc.subjectHeat mitigationen_US
dc.subjectInVESTen_US
dc.subjectTropicalen_US
dc.subjectUrban heat islanden_US
dc.subjectUrban planningen_US
dc.titleAssessing a decision-support tool to estimate the cooling potential and economic savings from urban vegetation in Singaporeen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume125en_US
dc.identifier.doi10.1016/j.scs.2025.106337en_US
dcterms.abstractTo mitigate the growing threat of urban heat, cities are implementing greening strategies such as tree planting or the development of parks. Effectively integrating these solutions into planning requires quantitative information on the cooling effect of urban vegetation. Here we examined the performance of an open-source decision-support tool, the Integrated Valuation of Ecosystem Services and Tradeoffs Urban Cooling model, to estimate the cooling effect and economic benefits from urban vegetation in a tropical city context, using Singapore as an exemplar case study. Using observed temperature data, we calibrated the model to estimate the spatial distribution of annual average day- and night-time temperature at 10 m spatial resolution and validated the results using leave-one-out cross validation. The calibrated models performed well to estimate annual average daily mean and maximum (day), and minimum (night) temperatures (R2 of 0.78, 0.65, and 0.52, respectively). We estimated that urban cooling in Singapore provides economic savings of $47.14 million SGD annually from reduced energy consumption in public residential buildings, based on the relationship between energy consumption and mean temperature. Our results give confidence in the model as a decision-support tool to estimate urban heat island effects and evaluate heat mitigation strategies in tropical cities.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationSustainable cities and society, 1 May 2025, v. 125, 106337en_US
dcterms.isPartOfSustainable cities and societyen_US
dcterms.issued2025-05-01-
dc.identifier.scopus2-s2.0-105001802428-
dc.identifier.eissn2210-6715en_US
dc.identifier.artn106337en_US
dc.description.validate202506 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumbera3797a-
dc.identifier.SubFormID51128-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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