Modeling heat island exposure and vulnerability utilizing earth observations and social drivers: A case study for Alabama, USA. (December 2022)

• Record Type: Journal Article
• Authors: Sabrin, Samain; Karimi, Maryam; Nazari, Rouzbeh
• Is Part Of: Building and environment. Volume 226(2022)
• Publication Date: 2022-12
• Subjects: Alabama -- Environmental exposure -- Landsat 8 TIRS -- Social vulnerability -- Risk index -- Risk mitigation -- UHI -- Cities; Buildings -- Environmental engineering -- Periodicals; Building -- Research -- Periodicals; Constructions -- Technique de l'environnement -- Périodiques; Electronic journals; 696
• DOI: 10.1016/j.buildenv.2022.109686
• Languages: English
• ISSNs: 0360-1323

Abstract

Abstract: Alabama currently experiences an above-average threat from extreme heat events compared to the remaining states in the USA. More than 160, 000 people living in the state (infants, elderly age groups, or poverty-ridden populations) remain vulnerable to heat events. The risk of heat-related mortalities and morbidities disproportionately impacts the growing Alabama cities due to increasing hot-weather episodes and several underlying social vulnerability factors. The exposure threat in 2050 is projected to increase by more than 90 average heat days a year and the number of heat-wave days is predicted to increase from 15 to more than 70 days a year. Although the state's hazard mitigation plan covers extreme heat issues and heat emergency plans, Alabama lacks heat adaptation plans and is conducting heat vulnerability assessments from time to time. This study focused on determining the social drivers of heat vulnerability and identifying regions within the state that experienced intense heat island effects over the course of five years (2015–2019). 15 sociodemographic factors data from the 2018 American Community Survey (ACS), and 6 health outcome variables (asthma, obesity, stroke, high blood pressure, diabetes) were analyzed to assess cumulative social vulnerability using principal component analysis (PCA). Using Spatial Autoregression (SAR) model, exposure risk was measured as a function of environmental parameters including proportional vegetation, normalized difference water index (NDWI), digital elevation model (DEM), and percent imperviousness of land surface. A heat risk index calculated as a product of social vulnerability and exposure risk was analyzed for Alabama's eight largest and growing cities (Birmingham, Huntsville, Hoover, Montgomery, Mobile, Tuscaloosa, Auburn, and Dothan) at the block-group census resolution. Spatial data depicting the physical landscape characteristics across the cities revealed differing levels of and factors in exposure to urban heat effects across the city. Highlights: Environmental and social drivers of heat vulnerability were explored. A heat risk index was calculated with exposure risk and social vulnerability. Fifteen demographic and six health factors were used to analyze social vulnerability. Exposure risk is calculated with Spatial Autoregression of environmental factors. Vulnerability, along with the heat risk index, were mapped for 8 Alabama cities.