A sidewalk-level urban heat risk assessment framework using pedestrian mobility and urban microclimate modeling
Open accessAbstract
Climate change and the associated increase in heat-related hazards pose a pressing threat to urban residents’ health and well-being. People, when walking in particular, are at risk of experiencing heat stress as they navigate urban environments. This study proposes a novel heat risk assessment framework combining pedestrian mobility modeling with urban microclimate modeling. Using this framework, we assessed pedestrian heat-related exposure and risk in urban areas by integrating the Universal Thermal Climate Index (UTCI) as the hazard and pedestrian trips to critical destinations as exposure. We considered temporal variation, in both hazard and exposure, by examining different time periods during the day—morning peak, midday, and evening peak. In addition to hazard and exposure, we also considered vulnerability by focusing on young children and older adults. We contribute to improving the spatial resolution of heat risk assessment by analyzing the hazard for pedestrian trips between home locations and five critical destinations—bus stops, rail stations, parks, schools, and commercial amenities—at the address-point level and using a pedestrian network comprising sidewalks and crosswalks. Our framework helps identify sidewalks with high heat exposure levels as well as home locations with high cumulative heat risk, accounting for walking trips to critical destinations along feasible routes. We demonstrated the effectiveness of this framework by applying it to a 36-square-kilometer area of central Los Angeles, CA. Our findings offer valuable information to urban planners and policy-makers, supporting evidence-based prioritization of intervention sites, climate adaptation strategies, and policy decisions essential for climate-proof planning. By implementing targeted interventions in areas where heat hazard is expected to affect the most vulnerable pedestrians, planners can create heat-resilient, pedestrian-friendly environments while prioritizing the health and well-being of vulnerable groups. This study contributes to the growing knowledge of robust risk assessment methodologies for climate-proof planning, specifically with regard to addressing outdoor heat-related risks during extreme heat events.
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In urban heat risk mapping, exposure is often represented by population density, pedestrian presence, residential concentration, or other indicators of human activity.
“In urban heat risk mapping, exposure is often represented by population density, pedestrian presence, residential concentration, or other indicators of human activity [30, 32].”
From GPU-Accelerated Deep Learning for Heatwave Prediction and Urban Heat Risk Assessment (2026) · cites this paper as [30]
In climate-risk literature, risk is commonly interpreted through the interaction of hazard, exposure, and vulnerability, and this perspective has also been adopted in urban heat studies.
“In climate-risk literature, risk is commonly interpreted through the interaction of hazard, exposure, and vulnerability, and this perspective has also been adopted in urban heat studies [30, 31].”
From GPU-Accelerated Deep Learning for Heatwave Prediction and Urban Heat Risk Assessment (2026) · cites this paper as [30]
Thermal indicators, including land surface temperature or related heat-stress measures, are used as the hazard component of the risk framework in earlier urban heat risk studies.
“Such an interpretation is consistent with earlier urban heat risk studies in which thermal indicators, including land surface temperature or related heat-stress measures, are used as the hazard component of the risk framework [30, 32].”
From GPU-Accelerated Deep Learning for Heatwave Prediction and Urban Heat Risk Assessment (2026) · cites this paper as [30]
The simplified multiplicative risk formulation is sufficient to show how next-day thermal forecasting can be extended towards interpretable urban heat risk assessment products.
“Although this formulation is simplified, it is sufficient to show how next-day thermal forecasting can be extended towards interpretable urban heat risk assessment products [30, 33].”
From GPU-Accelerated Deep Learning for Heatwave Prediction and Urban Heat Risk Assessment (2026) · cites this paper as [30]
Cites
Lindberg, F., Holmer, B., & Thorsson, S. (2008) · International Journal of Biometeorology · doi:10.1007/s00484-008-0162-7 · Cited by 574 · see citing works
Heat wave impact on morbidity and mortality in the elderly population: a review of recent studies
Oudin Åström, D., Bertil, F., & Joacim, R. (2011) · Maturitas · doi:10.1016/j.maturitas.2011.03.008 · Cited by 547 · see citing works
Amorim-Maia, A. T., Anguelovski, I., Chu, E., & Connolly, J. (2022) · Urban Climate · doi:10.1016/j.uclim.2021.101053 · Cited by 328 · see citing works
McDonald, R. I., Biswas, T., Sachar, C., Housman, I., Boucher, T. M., Balk, D., Nowak, D., Spotswood, E., Stanley, C. K., & Leyk, S. (2021) · PLOS ONE · doi:10.1371/journal.pone.0249715 · Cited by 159 · see citing works
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GPU-Accelerated Deep Learning for Heatwave Prediction and Urban Heat Risk Assessment
Alihodžić, A. (2026) · arXiv · doi:10.48550/arxiv.2605.16435
“Although this formulation is simplified, it is sufficient to show how next-day thermal forecasting can be extended towards interpretable urban heat risk assessment products [30, 33].”
Influential
- Authors
- Colaninno, N., Basu, R., Hosseini, M., Alhassan, A., Liu, L., & Sevtsuk, A.
- Affiliations
- Massachusetts Institute of Technology (US)
- Corresponding author
- Colaninno, Nicola
- Venue
- Environment and Planning B: Urban Analytics and City Science
- Publisher
- SAGE Publications
- Published
- 2024-09-08
- Volume
- 52
- Issue
- 5
- Pages
- 1071-1090
- ISSN
- 2399-8083 (ISSN-L)
- 2399-8091
- OpenAlex
- W4402416030
- Cited by
- 12
- References
- 4
- Citations by year
- 2026: 7 · 2025: 5
- FWCI
- 1.41
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Environment and Planning B Urban Analytics and City Science (publishedVersion, cc-by-nc)
- RePEc: Research Papers in Economics (submittedVersion)
- Virtual Community of Pathological Anatomy (University of Castilla La Mancha) (submittedVersion, other-oa)
- Funders
- H2020 Marie Skłodowska-Curie Actions (101028035)
- Topics
- Physical Sciences › Environmental Science › Environmental Engineering › Urban Heat Island Mitigation
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Climate Change and Health Impacts
- Health Sciences › Medicine › Physiology › Thermoregulation and physiological responses
- Keywords
- heat stress, Universal Thermal Climate Index, pedestrian movement, vulnerable populations, children and elderly, climate change adaptation, Los Angeles
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