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Abstract
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BACKGROUND: The research of climate change examines social vulnerability by looking at hazard exposure and susceptibility to that hazard; however, disaster-related data are not factored into vulnerability.
Methods: Using Hazus® Hurricane Model, disaster losses are calculated using data from the Houston metropolitan area and the 2008 historical storm event, Hurricane Ike. 2010 U.S. Census indicators quantify socioeconomic factors. GeoDa 1.14 open source software investigates nonrandom spatial clusters with exploratory spatial data analysis local Moran's I score to identify census tracts with high associated disaster losses and vulnerability.
Results: We demonstrate the importance of adding disaster loss data with the spatial analysis of vulnerability factors, including race, median income, and poverty. A nonrandom spatial component was found within and between these variables, confirming place matters. The average loss rate shows an increase of the number of census tracts that had a higher proportion of loss regardless of income.
Discussion: Incorporating historical disaster loss data into the model provides a better picture of vulnerable populations in the Houston metropolitan area. Disaster loss data is a crucial performance assessment technique that can effectively assess current approaches and compare the accuracy of other methods for identifying high-risk areas.
Conclusion: Previous social vulnerability studies in metropolitan areas focus on disaster impacts and recovery operation outcomes or on susceptibility to natural hazards. Our study investigates both vulnerabilities: social and biophysical. This average loss rate shows loss in relation to income, highlighting the importance of standardizing data to compare census tracts that are disproportionately affected.
Language: en |