Theses and Dissertations
LiDAR Data Analysis Strategies to Determine Features Indicative of At-Risk Coastal Sites
Date of Award
5-2022
Document Type
Thesis
Degree Name
M.S.
Department
Civil, Coastal, and Environmental Engineering
Committee Chair
Stephanie, Patch, Ph.D
Abstract
Light detection and ranging (LiDAR) derived volume changes provide both visual and statistical information for how project shorelines change over time. For beach erosion control (BEC) and coastal storm risk management (CSRM) projects, changes across storm events are fundamental to understanding a project’s progress. The Coastal Systems Portfolio Initiative (CSPI) aims to document and track U.S. Army Corps of Engineers (USACE) projects in a holistic systems-based manner. This web based geographic information system currently lacks numerical metrics beyond fill volumes to represent a project’s progress or reliability. This study aims to identify potential reliability metrics using the Joint Airborne LiDAR and Bathymetry Center for Expertise (JALBTCX) Volume Change Toolbox within ESRI’s ArcGIS software. The toolbox was run on the Haulover and Bal Harbour sections of the BEC project to analyze volume change and identify erosional hotspots. Volume change analysis was done between LiDAR derived digital elevation models (DEMs) for before and after Hurricane Matthew as well as DEMs from project design plans. Single transect profiles were also compared between the post-Matthew LiDAR and the designs to use in determining potential metrics. From these comparisons total volume change, shoreline change, beach width difference, change rates, and composite metrics were discussed to potentially include within the CSPI reliability ratings.
Recommended Citation
Elkins, Ashley, "LiDAR Data Analysis Strategies to Determine Features Indicative of At-Risk Coastal Sites" (2022). Theses and Dissertations . 28.
https://jagworks.southalabama.edu/theses_diss/28