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| Content Provider | ACM Digital Library |
|---|---|
| Author | Boos, John J. |
| Abstract | Hurricane Katrina showed Americans and the world that disasters can happen wherever there are people and clearly illustrated that being poor, old (or young), a minority, or a female puts one at greater risk to suffer negative short- and long-term impacts, with people with more than one of these characteristics having even an higher risk (Laska and Morrow 2006). In other words, belonging to these groups makes one more vulnerable. Hurricane Katrina also illustrated how actionable information on the degree of vulnerability must be balanced with the numbers of people affected. In other words, in order to maximize the effectiveness of public resources, it may sometimes be necessary to focus on more densely populated areas with lower rates of social vulnerability because, due to the sheer number of people, there are actually more vulnerable people located in these areas than in areas with high rates of vulnerability and lower population densities. This research mathematically weights vulnerability data with 90 meter residential gridded population data from LandScan USA (Bhaduri et al. 2007) to create a dataset that provides more actionable information to local authorities who need to balance rates of need with the number of individuals affected to ensure an efficient use of limited resources. The methods explored by this research successfully integrate vulnerability data with high resolution gridded population data. Based on the analyses it can be stated that the resulting population-weighted vulnerability data is significantly different from the unweighted vulnerability data and selectively different from the population data depending upon population density. More importantly, the method explored by this research allows for the combination of vulnerability and population density (two factors that are often examined separately) to create a surface with very high spatial resolution (90m) that shows where the greatest need is based both upon the levels of vulnerability and the number of people who are affected. |
| Starting Page | 1 |
| Ending Page | 1 |
| Page Count | 1 |
| File Format | |
| ISBN | 9781450306812 |
| DOI | 10.1145/1999320.1999359 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2011-05-23 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Content Type | Text |
| Resource Type | Article |
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