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Title: Population as a proxy for infrastructure in the determination of event response and recovery resource allocations

Research into modeling of the quantification and prioritization of resources used in the recovery of lifeline critical infrastructure following disruptive incidents, such as hurricanes and earthquakes, has shown several factors to be important. Among these are population density and infrastructure density, event effects on infrastructure, and existence of an emergency response plan. The social sciences literature has a long history of correlating the population density and infrastructure density at a national scale, at a country-to-country level, mainly focused on transportation networks. This effort examines whether these correlations can be repeated at smaller geographic scales, for a variety of infrastructure types, so as to be able to use population data as a proxy for infrastructure data where infrastructure data is either incomplete or insufficiently granular. Using the best data available, this effort shows that strong correlations between infrastructure density for multiple types of infrastructure (e.g. miles of roads, hospital beds, miles of electric power transmission lines, and number of petroleum terminals) and population density do exist at known geographic boundaries (e.g. counties, service area boundaries) with exceptions that are explainable within the social sciences literature. Furthermore, the correlations identified provide a useful basis for ongoing research into the larger resource utilizationmore » problem.« less
Authors:
 [1] ;  [1] ;  [1] ;  [2] ;  [2] ;  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  2. Geo-Relational Information Systems, Albuquerque, NM (United States)
Publication Date:
OSTI Identifier:
1333864
Report Number(s):
SAND--2015-2436J
Journal ID: ISSN 2194-6361; 579682
Grant/Contract Number:
AC04-94AL85000
Type:
Accepted Manuscript
Journal Name:
Journal of Homeland Security and Emergency Management
Additional Journal Information:
Journal Volume: 13; Journal Issue: 1; Journal ID: ISSN 2194-6361
Research Org:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org:
DHS; USDOE
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 58 GEOSCIENCES disaster response; infrastructure density; modeling; population density; resource organization; resource quantification