Authors: Mogahid (Mo) Hussein*, Texas State University
Topics: Geographic Information Science and Systems, Hazards and Vulnerability, Human-Environment Geography
Keywords: SoVI, vulnerability assessment, pareto ranking, flood analysis
Session Type: Poster
Start / End Time: 9:55 AM / 11:35 AM
Room: Lincoln 2, Marriott, Exhibition Level
Presentation File: No File Uploaded
Human actions, primarily the burning of fossil fuels, are causing the earth’s climate to change. Extreme weather events that lead to flooding like the Memorial Day Flood in Texas 2015 and wildfires like the Bastrop Fire in Texas 2011 due to climate variability will pose a challenge to the city of Austin and the surrounding communities. Thus, determining where the vulnerable populations to such events are located is important in order to implement effective strategies and programs for mitigation. This research compared two of the most prevalent methods of aggregation to assess the vulnerability of block groups in Travis County, Texas. A quantitative and visual comparison were done using the Spearman’s correlation and ESRI’s ArcMap, respectively. The two methods are different in that the additive aggregation uses the arithmetic mean to compute the index, whereas, Pareto ranking is a multi-objective optimization technique that ranks block groups based on non-domination in the complete data set. . The Spearman correlation result shows that the overall social vulnerability scores using the two different aggregation methods is 0.659, which indicates a moderate, positive monotonic correlation between additive aggregation and Pareto ranking. This research concluded that the additive aggregation method is useful to highlight outliers in the complete dataset, whereas, pareto ranking aggregation is useful to highlight block groups that score high in one or more of the social vulnerability indicators.