2018
DOI: 10.3390/urbansci2020038
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Assessing Vulnerability to Heat: A Geospatial Analysis for the City of Philadelphia

Abstract: Urban heat island (UHI) effect is an increasingly prominent health and environmental hazard that is linked to urbanization and climate change. Greening reduces the negative impacts of UHI; trees specifically are the most effective in ambient temperature reduction. This paper investigates vulnerability to heat in the Philadelphia, Pennsylvania and identifies where street trees can be planted as a public intervention. We used geospatial information systems (GIS) software to map a validated Heat Vulnerability Ind… Show more

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Cited by 13 publications
(6 citation statements)
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References 38 publications
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“…Kershaw et al [62] took apparent temperature intensity, exposure duration, and humidity into consideration, only focusing on the natural environment without any demographic and socioeconomic properties. Barron et al [16] employed 5 commonly used indicators, i.e., age, race, economic status, education level, and social isolation, incorporating demographic characteristics and socioeconomic properties but without environment-related considerations. On the other hand, the same circumstance also occurred in the assessment studies with many indicators.…”
Section: Findings and Discussionmentioning
confidence: 99%
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“…Kershaw et al [62] took apparent temperature intensity, exposure duration, and humidity into consideration, only focusing on the natural environment without any demographic and socioeconomic properties. Barron et al [16] employed 5 commonly used indicators, i.e., age, race, economic status, education level, and social isolation, incorporating demographic characteristics and socioeconomic properties but without environment-related considerations. On the other hand, the same circumstance also occurred in the assessment studies with many indicators.…”
Section: Findings and Discussionmentioning
confidence: 99%
“…This review found EW and PCA were the most frequently used weighting methods in heat vulnerability studies. Substantial studies [16,85,99] asserted that they decided to allocate all indicators or components with equal weights by referring to literature reviews on previous heat-related research. They assumed that each element is independent and represented a separate dimension of vulnerable targets to heat exposure.…”
Section: Findings and Discussionmentioning
confidence: 99%
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“…Urban freight dynamics significantly influence infrastructure utilisation and, therefore, transport externalities, companies (shippers and receivers) size, temporal patterns, fleet types, infrastructure conditions, assistive technologies, and freight types typically emerge as essential planning variables for freight operations [21][22][23][24] but are rarely considered for government-led infrastructure planning and management. Spatial analysis of companies' locations through the lens of economic geography principles provides a framework for defining FTZ, facilitating the application of UFI through a spatial and operational conditions-based analysis [25].…”
Section: Of 15mentioning
confidence: 99%
“…(Inostroza, Palme, & de la Barrera, 2016) (Bao, Li, & Yu, 2015) (Romero-Lankao, Qin, & Dickinson, 2012) (Nayak, et al., 2018) (Wolf & McGregor, 2013) (Stangl, 2018)(Macintyre, et al(Inostroza, Palme, & de la Barrera, 2016) (Pincetl, Chester, & Eisenman, 2016) (Weber, Sadoff, Zell, & de Sherbinin, 2015)(Swart, et al, 2012) (Barron, Ruggieri, & Branas, 2018)(Stangl, 2018) (Apreda, D'Ambrosio, & Di Martino(Pincetl, Chester, & Eisenman, 2016) (Wilhelmi & Hayden, 2010)(Reid, et al, 2009) (Romero-Lankao, Qin, & Dickinson, 2012)(Nayak, et al, 2018) (Wolf & McGregor, 2013) (Wolf & McGregor, 2013) (Mendez-Lazaro, Muller- Karger, Otis, McCarthy, & Rodriguez, 2017 (Stangl, 2018) (Savic, et al, 2018 Population Density % population per Km 2(Bao, Li, & Yu, 2015) (Romero-Lankao, Qin, & Dickinson, 2012 …”
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confidence: 99%