Developing an applied extreme heat vulnerability index utilizing socioeconomic and environmental data

Johnson, Daniel P.; Stanforth, Austin; Lulla, Vijay; Luber, George

doi:10.1016/j.apgeog.2012.04.006

Cited by 239 publications

(184 citation statements)

References 72 publications

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“…Although the literature shows that the contribution of social indices differs and that autocorrelation exists among them, there is no commonly acknowledged standard for each index and for this reason, we combined these indices with equal weight (Cutter et al 2003;Reid et al 2009;Johnson et al 2012). Pixels that mean population density is lower than 1/km 2 are excluded from the calculation.…”

Section: Socio-economic Vulnerabilitymentioning

confidence: 99%

“…General vulnerability analysis of sustainability assessments includes exposure, sensitivity, resilience, and adaptive capacity (Turner et al 2003;van Vuuren et al 2012). Several vulnerability indices of environmental hazards have been proposed, such as the SoVI (Cutter et al 2003), EHVI (Johnson et al 2012), and PVI (Adger 2006). A number of social vulnerability factors have been identified in local-or city-level heat health risk assessments, such as age, poverty, social isolation, education, ethnicity, and access to transportation (Schwartz 2005;Semenza et al 1996;Vescovi et al 2005).…”

Section: Vulnerability Of Different Populationsmentioning

confidence: 99%

“…Cutter et al (2003) presented a general index called social vulnerability index (SoVI), which listed 42 variables and reduced them to 11 independent factors that account for 76 % of the variance. Johnson et al (2012) developed an extreme heat vulnerability index (EHVI) that contains the principal components of 25 census data and remotely sensed variables that explain 80 % of the total variance. In this study, a correlation analysis is conducted temporally (using global means from 2010 to 2100 for a given SSP) and spatially (using country values for a given year and an SSP).…”

Section: Influence Of Heat Definitionmentioning

confidence: 99%

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New climate and socio-economic scenarios for assessing global human health challenges due to heat risk

et al. 2015

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Motivated by growing heat-related morbidity and mortality in a warming climate, this paper assesses global heat health risk in order to understand the challenges to sustainability in the 21st century, using four Representative Concentration Pathways (RCPs) of the HadGEM2-ES climate model and five Shared Socio-Economic Pathways (SSPs). Factors influencing global heat health risk were reviewed and risks were estimated based on heat hazard and socio-economic vulnerability. Hazard, vulnerability, risk and in particular, populations at different risk levels, were analyzed quantitatively at both global and regional scales. The results show that under an RCP8.5-SSP3 scenario, the world will be subject to the highest heat health risk, with rapidly increasing hazard levels and vulnerability over the century. Less developed or developing regions, such as Africa and Southeast Asia, are at the highest risk. The heat risk under an RCP2.6-SSP1 scenario will first increase and then fall, resulting in the lowest heat-health-risk pattern. We found that heat health risk will increase during the century under all RCP-SSP scenarios, with a higher frequency, higher intensity, longer duration and Climatic Change (2015) expanding spatial reach. Significant differences were observed across regions. The results make clear that the increasing risk poses significant challenges to sustainable human health. To meet these challenges, more attention and effective actions are urgently needed from both policy makers and individuals.

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Section: Socio-economic Vulnerabilitymentioning

confidence: 99%

Section: Vulnerability Of Different Populationsmentioning

confidence: 99%

Section: Influence Of Heat Definitionmentioning

confidence: 99%

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New climate and socio-economic scenarios for assessing global human health challenges due to heat risk

et al. 2015

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“…However, extensive scale-dependent variation in LST is expected throughout any given day due to different speeds of warming within the complex spatial structure of urban environments (Li et al 2011;Weng et al 2011). Furthermore, the human consequences of urban LST warming are not well characterized at very fine spatial resolutions, such as individual residential parcels, although several studies have found LST variation affects spatial variability in the risk of heatrelated mortality at neighborhood scales (Johnson et al 2009;Buscail et al 2012;Hondula et al 2012;Johnson et al 2012;Harlan et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Micro-scale urban surface temperatures are related to land-cover features and residential heat related health impacts in Phoenix, AZ USA

et al. 2015

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Context With rapidly expanding urban regions, the effects of land cover changes on urban surface temperatures and the consequences of these changes for human health are becoming progressively larger problems. Objectives We investigated residential parcel and neighborhood scale variations in urban land surface temperature, land cover, and residents' perceptions of landscapes and heat illnesses in the subtropical desert city of Phoenix, AZ USA. MethodsWe conducted an airborne imaging campaign that acquired high resolution urban land surface temperature data (7 m/pixel) during the day and night. We performed a geographic overlay of these data with high resolution land cover maps, parcel boundaries, neighborhood boundaries, and a household survey. Results Land cover composition, including percentages of vegetated, building, and road areas, and values for NDVI, and albedo, was correlated with residential parcel surface temperatures and the effects differed between day and night. Vegetation was more effective at cooling hotter neighborhoods. We found -015-0284-3 consistencies between heat risk factors in neighborhood environments and residents' perceptions of these factors. Symptoms of heat-related illness were correlated with parcel scale surface temperature patterns during the daytime but no corresponding relationship was observed with nighttime surface temperatures. Conclusions Residents' experiences of heat vulnerability were related to the daytime land surface thermal environment, which is influenced by micro-scale variation in land cover composition. These results provide a first look at parcel-scale causes and consequences of urban surface temperature variation and provide a critically needed perspective on heat vulnerability assessment studies conducted at much coarser scales.Landscape Ecol (2016) 31:745-760 DOI 10.1007/s10980

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“…Thermal imagery, for example, can be used to distinguish areas of the city that have increased thermal characteristics through calculation of land surface temperature (LST) [ 27 ]. This technique is used to identify the UHI or the hot spots within a city that are disproportionally warmer than the surrounding features.…”

Section: Satellite-based Remote Sensing As a Surveillance Toolmentioning

confidence: 99%

Modeling Vulnerable Urban Populations in the Global Context of a Changing Climate

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Innovating for Healthy Urbanization

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Developing an applied extreme heat vulnerability index utilizing socioeconomic and environmental data

Cited by 239 publications

References 72 publications

New climate and socio-economic scenarios for assessing global human health challenges due to heat risk

New climate and socio-economic scenarios for assessing global human health challenges due to heat risk

Micro-scale urban surface temperatures are related to land-cover features and residential heat related health impacts in Phoenix, AZ USA

Modeling Vulnerable Urban Populations in the Global Context of a Changing Climate

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