DTEx: A dynamic urban thermal exposure index based on human mobility patterns

Yanzhe Yin; Andrew Grundstein; Deepak R Mishra; Lakshmish Ramaswamy; Navid Hashemi Tonekaboni; John Dowd

doi:10.1016/j.envint.2021.106573

DTEx: A dynamic urban thermal exposure index based on human mobility patterns

Environ Int. 2021 Oct:155:106573. doi: 10.1016/j.envint.2021.106573. Epub 2021 Apr 27.

Authors

Yanzhe Yin¹, Andrew Grundstein², Deepak R Mishra², Lakshmish Ramaswamy³, Navid Hashemi Tonekaboni⁴, John Dowd⁵

Affiliations

¹ Department of Geography, University of Georgia, Athens, GA 30602, USA. Electronic address: yanzhe.yin@uga.edu.
² Department of Geography, University of Georgia, Athens, GA 30602, USA.
³ Department of Computer Science, University of Georgia, Athens, GA 30602, USA.
⁴ Department of Computer Science, College of Charleston, Charleston, SC 29424, USA.
⁵ Department of Geology, University of Georgia, Athens, GA 30602, USA.

PMID: 33930721
DOI: 10.1016/j.envint.2021.106573

Abstract

Background: Extreme heat in light of climate change is increasingly threatening the health and comfort of urban residents. Understanding spatio-temporal patterns of heat exposure is a critical factor in directing mitigation measures. Current heat vulnerability indices provide insight into heat sensitivities within given communities but do not account for the dynamic nature of the human movement as people travel for different activities. Here, we present a new Dynamic urban Thermal Exposure index (DTEx) that captures the varying heat exposure within urban environments.

Methods: We developed the DTEx to understand human heat exposure patterns in a mid-sized city. This index incorporates the human movement pattern and the heat hazard pattern obtained via novel and advanced techniques. We generated the human movement pattern from large-scale, anonymized smartphone location data. The heat hazard patterns were extrapolated via machine learning models from air temperature data measured through vehicle-mounted sensors. The exposure index was then developed by combining the two parameters using their standard-deviation-classified indices.

Results: Our exposure index varied between 2 and 12, indicating low to high thermal exposures. Several high-temperature spots associated with a large volume of foot traffic are successfully identified through this DTEx. We observed the hottest spots at shopping plazas but not specifically in the urban center. During the selected football gameday, the exposure index surged across most places near the football stadium but was reduced considerably further away.

Discussion: The proposed DTEx is novel because it provides dynamic heat monitoring capability to facilitate heat mitigation strategies at vulnerable locations in urban environments. Combining the mobility data and extensive sensor data generates rich details on the most heat-exposed areas due to human congregation. Such information will be critical for risk communication and urban planning for policymakers. DTEx could also help smart route planning in sustainable cities to avoid heat hazards risks.

Keywords: Ambient air temperature; Crowdsourcing; Foot traffic; Thermal comfort; Volunteered geographic information (VGI).

MeSH terms

Cities
Climate Change
Extreme Heat*
Hot Temperature*
Humans
Temperature