Identifying Areas Prone to Complicated Evacuations: Austin, Texas
|dc.contributor.author||Soules, Jeremy A. ( )|
|dc.identifier.citation||Soules, J. A. (2010). Identifying areas prone to complicated evacuations: Austin, Texas (Unpublished thesis). Texas State University-San Marcos, San Marcos, Texas.|
As urban populations grow, and transportation networks are pushed to their limits, both the potential for disaster and the difficulty of preparing for and responding to crises increase. Among the problems associated with increased urban density is the challenge of evacuating citizens to safety when disaster strikes. Threats of terrorism, chemical spills, fire storms, and the like are not likely to necessitate evacuations of entire cities. Instead, these urban extreme events threaten relatively isolated portions of these spaces. The spatial variation of the urban socio-demographic and infrastructural landscape, coupled with the wide range and severity of different types of urban hazards, make the comprehensive planning of evacuations of urban areas difficult, if not impossible.
A complicated evacuation occurs in an urban area that, for a variety of reasons, has a significantly slower rate of egress than in surrounding areas. Areas affected by complicated evacuation form the weakest links in an evacuation process. A way to help mitigate the potential effects of complicated evacuation is to identify those areas and populations that are at greatest risk for complicated evacuation (Lu et al. 2005). Armed with this knowledge, emergency planners can prioritize their planning efforts so that the needs of more vulnerable areas are addressed effectively.
This thesis offers a method to identify areas that are vulnerable to complicated evacuations through a system-wide analysis of a transportation network’s characteristics and its ability to effectively move people out of harm’s way. This method determines the evacuation capability of census block groups through the examination of four variables: (1) bulk lane demand, which compares the number of people in an area to the length of road available to them, (2) intersection occurrence frequency, which reflects the impedance of traffic flow caused by intersections, (3) distance to arterials, which measures the time-cost added by distance and (4) vulnerable facilities, which is a count of people housed in facilities such as hospitals and prisons in an area. The identified areas with potential for complicated evacuation are further evaluated to determine if social injustice is an issue in urban evacuation. Analyses were conducted to examine if minorities, the elderly, and the poor are at a greater risk for complicated evacuations.
This study found that the risk for complicated evacuation is not uniform across the City of Austin. Bulk lane demand negatively impacts block groups with high population density, especially those containing multi-family residences and large student populations. Block groups most affected by the distance to arterial roads metric are found to be in the suburban/exurban areas at the city fringe and in the central urban core between the two north-south arterials. High rates of intersection occurrence has detrimental effects on block groups in the urban core, where the road network is characterized by dense, tightly configured city blocks, and in suburban areas with high numbers of cul-de-sacs. Vulnerable facilities are found to affect block groups across the study area, with no apparent pattern, and to varying degrees.
Inequitable risk for complicated evacuations is found for vulnerable populations in Austin. Specifically, minority populations and households with low income are more likely to experience slower egress during an evacuation due to high bulk lane demand. Low-earning households are also more likely to experience higher rates of intersection occurrence while evacuating, though they are more likely to reside near arterial roads.
|dc.format.medium||1 file (.pdf)|
|dc.subject||Evacuation of civilians|
|dc.title||Identifying Areas Prone to Complicated Evacuations: Austin, Texas|
|thesis.degree.grantor||Texas State University--San Marcos|
|thesis.degree.name||Master of Science|
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