Foredune Classification and Storm Response: Automated Analysis of Terrestrial Lidar DEMs

Abstract

Accurate predictions of foredune response and recovery to storms arecritical for understanding coastal vulnerability at a variety of time-scales. Foredune morphology and storm response were investigated using terrestrial lidar data along a10-kilometer stretch of open-coast beach near Duck, NC. An algorithm was developed to classify foredune state from 50-cm bare earth DEMs into four categories: scarped, recovering, healthy, and man-made. The algorithm was based on extraction of morphological features including the slope, volume, and curvature of the foredune face. Preliminary results detailing the response of each foredune state to a 4-dayNorEaster (Hs = 4.8m at 16s in 8m of water) are presented, and suggest that manmade and recovering dunes lost more volume and eroded more rapidly when compared with scarped dunes. The increased erosion may have been due to a combination of slightly lower dune-toe elevations for the man-made dunes and unconsolidated sediment in the foredune.

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Document Details

Document Type
Technical Report
Publication Date
Jun 15, 2015
Accession Number
AD1007900

Entities

People

  • Katherine Brodie
  • Nicholas J. Spore

Tags

Communities of Interest

  • Engineered Resilient Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Barrier Islands
  • Cape Hatteras
  • Climate Change
  • Coastal Engineering
  • Coordinate Systems
  • Engineering
  • Engineers
  • Environmental Management
  • Feature Extraction
  • Geography
  • Infrastructure
  • Marine Geology
  • North Carolina
  • Point Clouds
  • Research Facilities
  • Topography
  • Trajectories

Fields of Study

  • Environmental science

Readers

  • Coastal and Marine Engineering/Sediment Transport/Hydraulic Engineering
  • Emergency Management and Homeland Security.
  • Geotechnical Engineering.