Abstract
Extreme heat events, exacerbated by climate change, present significant risks to human health and disproportionately affect vulnerable populations. Traditional assessments of heat exposure often rely on static residential data, which fails to account for the dynamic human mobility pattern of the population in space and time. Recent work utilizes mobility data to explore exposure dynamics in heat-related studies. However, these studies are primarily focused on the general population or the differences in human mobility across varying income levels in response to heat exposure. Unlike previous studies, this research employs a Monte Carlo simulation that integrates mobility data with American Community Survey (ACS) data to estimate the social composition of populations by race, income, and education and to examine mobility differences across social groups exposed to heat in Greater Austin, Texas. Our findings reveal that during extreme heat (caution) events, movements in the higher-income neighborhoods significantly reduce outdoor mobility, particularly for Whites and Asians, while lower-income communities exhibit limited adjustments. The young population (ages 15–29) across all income levels decreases their movement during heat caution periods. Notably, within high-income areas, only those with a college degree tend to reduce mobility, whereas individuals with a high school education or less tend to increase their movement. The findings highlight key strategies for policymakers, including enhancing access to cooling centers, shade infrastructure, green space, and urban resilience plans, supporting vulnerable communities, and protecting outdoor workers to mitigate health risks associated with heat.
Keywords
heat, human mobility, social composition, Monte Carlo simulation
Document Type
Paper
Start Date
18-6-2025 1:30 PM
End Date
18-6-2025 2:30 PM
DOI
10.5703/1288284317901
Recommended Citation
Gu, Xin; Han, Su Yeon; Myint, Soe Win; Cho, Eunsang; Zhu, Yuanhui; and Kim, Joonseok, "Exploring Dynamic Human Mobility of Diverse Social Groups Under Heat Conditions: A Simulation-Based Approach" (2025). I-GUIDE Forum. 1.
https://docs.lib.purdue.edu/iguide/2025/presentations/1
Exploring Dynamic Human Mobility of Diverse Social Groups Under Heat Conditions: A Simulation-Based Approach
Extreme heat events, exacerbated by climate change, present significant risks to human health and disproportionately affect vulnerable populations. Traditional assessments of heat exposure often rely on static residential data, which fails to account for the dynamic human mobility pattern of the population in space and time. Recent work utilizes mobility data to explore exposure dynamics in heat-related studies. However, these studies are primarily focused on the general population or the differences in human mobility across varying income levels in response to heat exposure. Unlike previous studies, this research employs a Monte Carlo simulation that integrates mobility data with American Community Survey (ACS) data to estimate the social composition of populations by race, income, and education and to examine mobility differences across social groups exposed to heat in Greater Austin, Texas. Our findings reveal that during extreme heat (caution) events, movements in the higher-income neighborhoods significantly reduce outdoor mobility, particularly for Whites and Asians, while lower-income communities exhibit limited adjustments. The young population (ages 15–29) across all income levels decreases their movement during heat caution periods. Notably, within high-income areas, only those with a college degree tend to reduce mobility, whereas individuals with a high school education or less tend to increase their movement. The findings highlight key strategies for policymakers, including enhancing access to cooling centers, shade infrastructure, green space, and urban resilience plans, supporting vulnerable communities, and protecting outdoor workers to mitigate health risks associated with heat.