Data Science and Digital Business
This book chapter applies data science methods to analyze storm surge induced flood risks along the Mississippi Gulf Coast by presenting the spatial risk distribution of the study area using the Geographic Information System (GIS) based visualization and quantifying the flood risk in statistical relationships with the risk related factors using multiple linear regression analysis models. The data are retrieved and visualized for the residential blocks. The maximum surge elevation data are collected and validated against representative historical hurricane wind and storm surge data recorded by the Federal Emergency Management Agency (FEMA) and National Hurricane Center (NHC). The maximum surge height above the land surface is calculated based on the elevations and tide level in the Mississippi Gulf Coast Basin. The statistics models using the multiple regression analysis method characterize the significant relationships among these risk related variables. The direct loss coverage can be estimated using the models.
List of Abbreviations
Geographic Information System
North American Vertical Datum
Sea, Lake and Overland Surges from Hurricanes
National Oceanic and Atmospheric Administration
Federal Emergency Management Agency
National Hurricane Center
Hurricane Protection System
Average Daily Traffic
Digital Elevation Model
Mississippi Department of Transportation
Variance Inflator Factor
University Transportation Center
The project was partially funded by the Institute for Multimodal Transportation (IMTrans) at Jackson State University through the UTC program of the US Department of Transportation (USDOT).
- 1.Mississippi Gulf Coast. (2016). Retrieved from January, 2016, from https://en.wikipedia.org/wiki/Mississippi_Gulf_Coast.
- 2.Wiki. (2015). Effects of Hurricane Katrina in Mississippi. Retrieved December 1, 2015, from http://en.wikipedia.org/wiki/Effects_of_Hurricane_Katrina_in_Mississippi.
- 3.United States Census Bureau. (2016). Retrieved March 3, 2016, from http://www.census.gov.
- 4.National Hurricane Center. (2016). Retrieved February 13, 2016, from http://www.nhc.noaa.gov.
- 6.Bates, P., Trigg, M., Neal, J., & Dabrowa, A. (2013). User Manual for LISFLOOD-FP Code Release 5.9.6. University of Bristol, UK.Google Scholar
- 7.Jelesnianski, C. P., Chen, J., & Shaffer, W. A. (1992). SLOSH: Sea, lake, and overland surges from hurricanes. NOAA Technical Report NWS 48, National Oceanic and Atmospheric Administration, U.S. Department of Commerce, 71 pp.Google Scholar
- 9.Kent, J. D. (2013, January). Quantifying the key factors that create road flooding. Center for GeoInformatics (C4G), Louisiana State University. LTRC Project Number: 11-6GT.Google Scholar
- 10.Savonis, M. J., Burkett, V. R., & Potter, J. R. (2008, March). Impacts of climate change and variability on transportation systems and infrastructure: Gulf Coast study, Phase I. In U.S. Climate Change Science Program, Synthesis and Assessment Product 4.7.Google Scholar
- 11.Hyman, R., Lupes, R., & Perlman, D. (2011). Federal highway administration activities related to the adaptation of transportation infrastructure to climate change impacts. Chapter of adapting transportation to the impacts of climate change: State of the practice 2011. Transportation Research Board, 12–18.Google Scholar
- 12.Baker, E. J. (1991). Hurricane evacuation behavior. International Journal of Mass Emergencies and Disasters, 9(2), 234–245.Google Scholar
- 13.Humphrey, N. P. (2008). TRB Special Report: Potential impacts of climate change on U.S. transportation. Transportation Research Board, 256, 21–24.Google Scholar
- 16.Bian, R. J., & Wilmot, C. G. (2016). Measuring the vulnerability of disadvantaged populations during Hurricane evacuation. In Transportation Research Board 95th Annual Meeting, Washington DC, 10–14 January 2016.Google Scholar
- 18.Choate, A., Evans, C., Rodehorst, B., Saavedra, R., Snow, C., Snyder, J., et al. (2014, June). Impacts of climate change and variability on transportation systems and infrastructure: The Gulf Coast study, phase 2. US Department of Transportation. Report No.: FHWA-HEP-14-033.Google Scholar
- 19.U.S. Department of Transportation (USDOT). (2014). Maritime Administration, U.S. Waterborne Foreign Container Trade by U.S. Custom Ports. Retrieved November 10, 2014, from https://www.marad.dot.gov/resources/data-statistics/.
- 20.Louisiana State University (LSU). (2016). Global Peak Surge Map. SURGEDAT. Retrieved January 15, 2016, from http://surge.srcc.lsu.edu.
- 21.The Federal Emergency Management Agency. (2016). Retrieved January 15, 2016, from https://www.fema.gov/.
- 22.National Hurricane Center. (2016). Retrieved February 4, 2016, from http://www.nhc.noaa.gov.
- 23.U.S. Geological Survey (USGS). (2016). Retrieved January 15, 2016, from https://www.usgs.gov/.
- 24.Mississippi Insurance Department. (2015, December). Analysis and interpretation of the clarity act data call.Google Scholar
- 25.National Weather Service. (2016). Retrieved January 17, 2016, from http://www.weather.gov/.
- 26.Belsley, D. A. (1991). Conditioning diagnostics: Collinearity and weak data in regression (1 st ed.). Wiley.Google Scholar