Heat exposure assessment based on individual daily mobility patterns in Dhaka, Bangladesh. (September 2019)

• Record Type: Journal Article
• Authors: Yasumoto, Shinya; Jones, Andrew P.; Oyoshi, Kei; Kanasugi, Hiroshi; Sekimoto, Yoshihide; Shibasaki, Ryosuke; Comber, Alexis; Watanabe, Chiho
• Is Part Of: Computers, environment and urban systems. Volume 77(2019)
• Publication Date: 2019-09
• Subjects: Population mobility -- Heat exposure assessment -- Geographic information systems -- Remote sensing -- Bangladesh; City planning -- Data processing -- Periodicals; Regional planning -- Data processing -- Periodicals; 303.4834
• DOI: 10.1016/j.compenvurbsys.2019.101367
• Languages: English
• ISSNs: 0198-9715

Abstract

Abstract: Despite a growing body of evidence indicating increasing health impacts from heat exposure secondary to climate change, previous studies have assessed heat exposure based only on the residential locations of individuals. Such assessments may be imprecise as they do not reflect the impact of people's daily mobility patterns. Furthermore, most studies have focused on urban areas in developed countries, whilst relatively little is known about the situation in developing nations, particularly a tropical climate region where heat exposure is severe for residents. As a case study in Dhaka, Bangladesh, we conducted a heat exposure assessment by integrating individual mobility data which was obtained from a questionnaire survey. Estimates of heat exposure were made using remotely sensed land surface temperature data. Population exposures based on residential locations were compared to a dynamic exposure model that incorporated mobility. Especially for people in suburban areas, we found the traditional assessment method based on the static residential model underestimated exposure compared to the dynamic model owing to the fact that some residents migrate into the city center each day where they tend to experience higher temperatures. We found small differences in heat exposure levels between social groups stratified by gender, age, and income based on the dynamic and static models. These results demonstrate that integration of mobility patterns may be important when comparing exposure levels between urban and suburban populations. Our findings may raise issues regarding new remediation measures against urban heat islands, such as reviewing the distribution of health resources or generating a risk map. Highlights: This is a new application of GIS-based mobility data for a dynamic heat exposure assessment in Dhaka, Bangladesh. Population exposure based on a static residential model was compared to a dynamic exposure model that incorporated mobility. We found the static assessment underestimated heat exposure compared to the dynamic assessment for some suburb populations. Mobility data have the potential for a more precise exposure assessment of adverse environmental risks.