A comparison of urban heat islands mapped using skin temperature, air temperature, and apparent temperature (Humidex), for the greater Vancouver area

Ho, Hung Chak; Knudby, Anders; Xu, Youtao; Hodúl, Matúš; Aminipouri, Mehdi

doi:10.1016/j.scitotenv.2015.12.021

Cited by 166 publications

(88 citation statements)

References 74 publications

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“…For the regression, the average prediction for all trees are considered; for classification, predictions are considered the 'vote' for the most popular class among all trees [40][41][42]. RF has been used with satellite-derived predictors to map air temperature distributions [21,37]. We used RF to test variables for both selected buffer sizes and all buffer sizes.…”

Section: Resultsmentioning

confidence: 99%

“…Based on the correlations found between buffer size and temperature, we selected the most influential buffer sizes for each date/time by determining the buffer distances with the largest positive or negative effects on temperatures (Table 3). The maximum buffer size of 600 m was selected based on previous studies, which commonly employed several hundred meters [36] and 500 m/1000 m [37] We employed three statistical approaches to model air temperatures using these relevant predictors: ordinary least squares (OLS), regression tree analysis (RTA), and random forest (RF). OLS is the most commonly employed approach to understand the strength of independent variables in order to explain dependent variables [12][13][14].…”

Section: Discussionmentioning

confidence: 99%

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Daytime Variation of Urban Heat Islands: The Case Study of Doha, Qatar

Makido

Shandas

Ferwati

et al. 2016

Climate

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Recent evidence suggests that urban forms and materials can help to mediate temporal variation of microclimates and that landscape modifications can potentially reduce temperatures and increase accessibility to outdoor environments. To understand the relationship between urban form and temperature moderation, we examined the spatial and temporal variation of air temperature throughout one desert city-Doha, Qatar-by conducting vehicle traverses using highly resolved temperature and GPS data logs to determine spatial differences in summertime air temperatures. To help explain near-surface air temperatures using land cover variables, we employed three statistical approaches: Ordinary Least Squares (OLS), Regression Tree Analysis (RTA), and Random Forest (RF). We validated the predictions of the statistical models by computing the Root Mean Square Error (RMSE) and discovered that temporal variations in urban heat are mediated by different factors throughout the day. The average RMSE for OLS, RTA and RF is 1.25, 0.96, and 0.65 (in Celsius), respectively, suggesting that the RF is the best model for predicting near-surface air temperatures at this study site. We conclude by recommending the features of the landscape that have the greatest potential for reducing extreme heat in arid climates.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Daytime Variation of Urban Heat Islands: The Case Study of Doha, Qatar

Makido

Shandas

Ferwati

et al. 2016

Climate

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“…All three maps have a spatial resolution of 60 m and were derived from cloud-free Landsat images of greater Vancouver retrieved on hot summer days with maximum air temperatures ≥ 25°C at YVR (Table 1). The methods used to create each map are described in detail elsewhere (Barsi et al 2003; Coll et al 2010; Ho et al 2014, 2016) and are described briefly below.…”

Section: Methodsmentioning

confidence: 99%

“…The mean absolute error between the observed and predicted air temperatures was 1.82°C. A similar approach was used for the humidex map (see Figure S3), with a mean absolute error of 1.67°C (Ho et al 2016). These errors are small compared with those in similar studies in the remote sensing literature (Benali et al 2012; Ho et al 2014; Xu et al 2014).…”

Section: Methodsmentioning

confidence: 99%

Delineation of Spatial Variability in the Temperature–Mortality Relationship on Extremely Hot Days in Greater Vancouver, Canada

Knudby

Walker

et al. 2017

Environ Health Perspect

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Background:Climate change has increased the frequency and intensity of extremely hot weather. The health risks associated with extemely hot weather are not uniform across affected areas owing to variability in heat exposure and social vulnerability, but these differences are challenging to map with precision.Objectives:We developed a spatially and temporally stratified case-crossover approach for delineation of areas with higher and lower risks of mortality on extremely hot days and applied this approach in greater Vancouver, Canada.Methods:Records of all deaths with an extremely hot day as a case day or a control day were extracted from an administrative vital statistics database spanning the years of 1998–2014. Three heat exposure and 11 social vulnerability variables were assigned at the residential location of each decedent. Conditional logistic regression was used to estimate the odds ratio for a 1°C increase in daily mean temperature at a fixed site with an interaction term for decedents living above and below different values of the spatial variables.Results:The heat exposure and social vulnerability variables with the strongest spatially stratified results were the apparent temperature and the labor nonparticipation rate, respectively. Areas at higher risk had values ≥ 34.4°C for the maximum apparent temperature and ≥ 60% of the population neither employed nor looking for work. These variables were combined in a composite index to quantify their interaction and to enhance visualization of high-risk areas.Conclusions:Our methods provide a data-driven framework for spatial delineation of the temperature-–mortality relationship by heat exposure and social vulnerability. The results can be used to map and target the most vulnerable areas for public health intervention.Citation:Ho HC, Knudby A, Walker BB, Henderson SB. 2017. Delineation of spatial variability in the temperature–mortality relationship on extremely hot days in greater Vancouver, Canada. Environ Health Perspect 125:66–75; http://dx.doi.org/10.1289/EHP224

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“…Although many UHI mitigation strategies have been proposed lately [4][5][6], UHIs still occur in almost all urban areas-independently of city size and climate zone-and their study, as well as the assessment of their impact, is of great importance. This is because the UHI effect has been associated with a range of issues, such as increased energy demand and human health problems (such as thermal discomfort and increased mortality during heatwaves) [7][8][9][10][11][12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

An Online System for Nowcasting Satellite Derived Temperatures for Urban Areas

et al. 2016

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Abstract:The Urban Heat Island (UHI) is an adverse environmental effect of urbanization that increases the energy demand of cities and impacts human health. The study of this effect for monitoring and mitigation purposes is crucial, but it is hampered by the lack of high spatiotemporal temperature data. This article presents the work undertaken for the implementation of an operational real-time module for monitoring 2 m air temperature (TA) at a spatial resolution of 1 km based on the Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI). This new module has been developed in the context of an operational system for monitoring the urban thermal environment. The initial evaluation of TA products against meteorological in situ data from 15 cities in Europe and North Africa yields that its accuracy in terms of Root Mean Square Error (RMSE) is 2.3˝C and Pearson's correlation coefficient (Rho) is 0.95. The temperature information made available at and around cities can facilitate the assessment of the UHIs in real time but also the timely generation of relevant higher value products and services for energy demand and human health studies. The service is available at

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A comparison of urban heat islands mapped using skin temperature, air temperature, and apparent temperature (Humidex), for the greater Vancouver area

Cited by 166 publications

References 74 publications

Daytime Variation of Urban Heat Islands: The Case Study of Doha, Qatar

Daytime Variation of Urban Heat Islands: The Case Study of Doha, Qatar

Delineation of Spatial Variability in the Temperature–Mortality Relationship on Extremely Hot Days in Greater Vancouver, Canada

An Online System for Nowcasting Satellite Derived Temperatures for Urban Areas

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