Authors: Yanzhe Yin*, University of Georgia, Andrew Grundstein, University of Georgia, Deepak Mishra, University of Georgia, Lakshmish Ramaswamy, University of Georgia, Navid Hashime, College of Charleston
Topics: Hazards and Vulnerability, Medical and Health Geography, Geographic Information Science and Systems
Keywords: ambient air temperature, thermal comfort, foot traffic, crowdsourcing, Volunteered geographic information (VGI)
Session Type: Virtual Paper
Start / End Time: 1:30 PM / 2:45 PM
Room: Virtual 48
Presentation File: No File Uploaded
Extreme heat in light of climate change is increasingly threatening the health and safety of urban residents. Understanding geographic patterns of heat exposure is a critical way to identify at-risk populations and direct mitigation measures. Current heat exposure provides insight into heat sensitivities within given communities but does not account for the human movement's dynamic nature. A broadly adopted approach is to generate an index to map varying heat exposure within an urban environment. Our research developed a dynamic hyperlocal heat exposure index to understand human heat hazard by incorporating the human movement pattern from mobility data and heat hazard data from the smart sensor network data. The exposure index was developed by combining the standard deviation classified index of the two parameters above. The final output maps show that several high-temperature spots associated with a large volume of foot traffic are successfully identified via our index. Places that used to be the main target of heat mitigation plans such as the downtown and popular parks do not show significantly higher exposure. Therefore, combining the mobility data and extensive sensor network data generates rich details on the most heat-exposed areas due to the human congregation. This proposed index provides dynamic heat monitoring capability to facilitate heat mitigation strategies for the urban environment.