Measuring the vulnerability of disadvantaged populations during hurricane evacuation
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  • 作者:Ruijie Bian ; Chester G. Wilmot
  • 关键词:Hurricane evacuation ; Disadvantaged population ; Vulnerability ; Transit
  • 刊名:Natural Hazards
  • 出版年:2017
  • 出版时间:January 2017
  • 年:2017
  • 卷:85
  • 期:2
  • 页码:691-707
  • 全文大小:
  • 刊物类别:Earth and Environmental Science
  • 刊物主题:Natural Hazards; Hydrogeology; Geophysics/Geodesy; Geotechnical Engineering & Applied Earth Sciences; Civil Engineering; Environmental Management;
  • 出版者:Springer Netherlands
  • ISSN:1573-0840
  • 卷排序:85
文摘
In this paper, the extent to which the potentially transit-dependent portion of the population is vulnerable to the effects of a hurricane is estimated. The vulnerability of an area is defined as a composite measure of the proportion of disadvantaged persons, distance to transit, and flooding potential of people within an area. Unlike past studies which have focused on the vulnerability of the population in relatively large geographic areas, this study estimates the vulnerability of the population in 30 m × 30 m areas as defined in the National Land Cover Database. Population estimates from the national census at block level are disaggregated to the 30 m × 30 m units using a modified dasymetric mapping method in ArcGIS. The modified mapping method assigns population to each small areal unit using weights estimated by regressing the area of each land use in a census block against the population in that block. The coefficients in the regression analysis are “weights” associating population with each land use, and are used to distribute the population in each census block to the small geographic units based on their land use. In a case study of New Orleans, the results show that some areas are not well served by the existing transit pickup locations, as evidenced by their high vulnerability scores. Reassignment of pickup point locations to cover higher vulnerability score areas was investigated using integer linear programming. The results show that the optimally located pickup points serve areas with a larger average vulnerability score than the current pickup points in the study area. The method appears to be helpful in identifying vulnerable areas that, subsequently, could receive improved hurricane evacuation service in the future.
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