individual
What campus are you from?
Daytona Beach
Authors' Class Standing
Jordan Rezende De Lucia, Junior
Lead Presenter's Name
Jordan Rezende De Lucia
Faculty Mentor Name
Dr. Kocaman
Abstract
How do natural disasters impact different socioeconomic portions of society, and what spatial patterns emerge in disaster vulnerability, economic recovery, and aid distribution? Natural disasters aren’t felt equally by everyone. This study aims to take a closer look at how pre-existing socioeconomic conditions shape the way different communities are affected and how they recover. I argue that lower-income areas get more adversely affected by natural disasters and recover slower in comparison with wealthier areas. I tested these hypotheses using geospatial data from Hurricane Ian, which hit Florida in September 2022. For the geospatial analysis, I used ArcGIS Pro to map Ian’s path and overlay it with county-level data on income and poverty from before and after the hurricane. Data sources include the U.S. Census Bureau, FEMA, NOAA, and USGS. My analysis aimed to see whether lower-income areas were hit harder or recovered more slowly and whether wealthier areas benefited more from post-disaster aid or recovery resources. I also performed Hot Spot Analysis (Getis-Ord Gi*) to identify patterns and statistically significant clusters in the data that might not be immediately obvious. The results showed that while the hurricane caused serious physical damage, it didn’t drastically shift poverty levels. What did change, though, was income. Many areas, especially already affluent ones, saw somewhat noticeable increases in median household income, which raises questions about how resources were distributed and who actually benefited from recovery programs.
Did this research project receive funding support from the Office of Undergraduate Research.
No
Mapping the Socioeconomic Impact of Hurricane Ian
How do natural disasters impact different socioeconomic portions of society, and what spatial patterns emerge in disaster vulnerability, economic recovery, and aid distribution? Natural disasters aren’t felt equally by everyone. This study aims to take a closer look at how pre-existing socioeconomic conditions shape the way different communities are affected and how they recover. I argue that lower-income areas get more adversely affected by natural disasters and recover slower in comparison with wealthier areas. I tested these hypotheses using geospatial data from Hurricane Ian, which hit Florida in September 2022. For the geospatial analysis, I used ArcGIS Pro to map Ian’s path and overlay it with county-level data on income and poverty from before and after the hurricane. Data sources include the U.S. Census Bureau, FEMA, NOAA, and USGS. My analysis aimed to see whether lower-income areas were hit harder or recovered more slowly and whether wealthier areas benefited more from post-disaster aid or recovery resources. I also performed Hot Spot Analysis (Getis-Ord Gi*) to identify patterns and statistically significant clusters in the data that might not be immediately obvious. The results showed that while the hurricane caused serious physical damage, it didn’t drastically shift poverty levels. What did change, though, was income. Many areas, especially already affluent ones, saw somewhat noticeable increases in median household income, which raises questions about how resources were distributed and who actually benefited from recovery programs.