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.
Spatiotemporal Population Distribution Method for Emergency Evacuation
Case Study of New Orleans, Louisiana
Transportation Research Record: Journal of the Transportation Research Board
Transportation Research Record: Journal of the Transportation Research Board ; 2532 , 1 ; 99-106
01.01.2015
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Spatiotemporal Population Distribution Method for Emergency Evacuation
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