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Spatiotemporal Population Distribution Method for Emergency Evacuation: Case Study of New Orleans, Louisiana

Knowing where people are is important in emergency management. This study presents a spatiotemporal method to estimate population distribution by time of day, day of the week, and season of the year. Population is broken into six groups: residents, workers, students, stay-at-homes, shoppers, and tou...

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Published in:Transportation research record 2015-01, Vol.2532 (1), p.99-106
Main Authors: Bian, Ruijie, Wilmot, Chester G.
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Language:English
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description Knowing where people are is important in emergency management. This study presents a spatiotemporal method to estimate population distribution by time of day, day of the week, and season of the year. Population is broken into six groups: residents, workers, students, stay-at-homes, shoppers, and tourists. The last two groups have usually been neglected in studies. However, these groups can be significant portions of the population in certain environments and display unique variations. In this study, population is distributed by using dasymetric mapping; the distribution of the population is based on land use. However, two modifications are made. First, preprocessing of coarse land use categories with residential density and employee data allows the distinction between resident, worker, shopper, and tourist in the distribution process. Second, the relationship between population and land use is based on regression of existing data instead of on subjective judgment or sampling as in current dasymetric methods. The method is demonstrated in an application to downtown New Orleans, Louisiana, to evaluate the population affected by a hypothetical chemical spill. In one case, the spill is assumed to occur on a weekday afternoon during a local festival. About 83,000 people are estimated to be affected, with most being workers and tourists. In the other case, the same spill is considered to occur over the weekend at night during a period when no festival is in progress. In this case, 39,000 people are estimated to be affected, most of them residents and tourists spread throughout the area within the plume.
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source SAGE:Jisc Collections:SAGE Journals Read and Publish 2023-2024:2025 extension (reading list)
subjects Categories
Land use
Population distribution
Preprocessing
Regression
Sampling
Spills
Time of use
title Spatiotemporal Population Distribution Method for Emergency Evacuation: Case Study of New Orleans, Louisiana
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