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Data Science and Digital Business

  • Lei Bu
  • Feng WangEmail author
Chapter

Abstract

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

GIS

Geographic Information System

NAVD88

North American Vertical Datum

SLOSH

Sea, Lake and Overland Surges from Hurricanes

NOAA

National Oceanic and Atmospheric Administration

FEMA

Federal Emergency Management Agency

NHC

National Hurricane Center

HPS

Hurricane Protection System

ADT

Average Daily Traffic

DEM

Digital Elevation Model

MDOT

Mississippi Department of Transportation

CI

Condition Index

VIF

Variance Inflator Factor

UTC

University Transportation Center

Notes

Acknowledgements

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).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Civil and Environmental EngineeringInstitute for Multimodal Transportation, Jackson State UniversityJacksonUSA
  2. 2.Ingram School of EngineeringTexas State UniversitySan MarcosUSA

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