A statistical approach to small area synthetic population generation as a basis for carless evacuation planning

Natural or man-made hazards that require evacuation put already vulnerable populations in a more precarious situation. However, when plans and decisions about evacuation are made, the assumption of access to a private car is typically made and differences in income levels across a community is rarel...

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Bibliographic Details
Published in:Journal of transport geography 2021-01, Vol.90, p.102902, Article 102902
Main Authors: Nejad, Mohammad Motalleb, Erdogan, Sevgi, Cirillo, Cinzia
Format: Article
Language:English
Subjects:
Accessibility
Archimedean copulas
Car-ownership models
Carless
Census
Decisions
Emergency preparedness
Evacuation
Evacuation planning
Geographical locations
Income
Logit models
Low income
Planning
Population (statistical)
Shelters
Synthetic population
Transportation services
Trip surveys
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Summary:Natural or man-made hazards that require evacuation put already vulnerable populations in a more precarious situation. However, when plans and decisions about evacuation are made, the assumption of access to a private car is typically made and differences in income levels across a community is rarely accounted for. The result is that carless members of a community can find themselves stranded. Low income carless residents need alternative transportation means to reach shelters in case of an emergency. Thus, evacuation plans, decisions and models need necessary information that identifies and locates these populations. In this paper, data from the American Community Survey, US Census, Internal Revenue Services and the National Household Travel Survey are used to generate synthetic population for Anne Arundel County, Maryland using the copula concept. Geographic locations of low-income residents are identified within each subarea of the county (census tract) and their car ownership is estimated with a binomial logit model. The developed population synthesis method will allow officials to have a more accurate account of disadvantaged populations for emergency planning and identify locations of shelters, triage points as well as planning carless transportation services.
ISSN:0966-6923
1873-1236
DOI:10.1016/j.jtrangeo.2020.102902