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.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 15, 2015
- Accession Number
- AD1007900
Entities
People
- Katherine Brodie
- Nicholas J. Spore