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FOREDUNE CLASSIFICATION AND STORM RESPONSE: AUTOMATED ANALYSIS OF TERRESTRIAL LIDAR DEMS

    https://doi.org/10.1142/9789814689977_0041Cited by:6 (Source: Crossref)
    Abstract:

    Accurate predictions of foredune response and recovery to storms are critical for understanding coastal vulnerability at a variety of time-scales. Foredune morphology and storm response were investigated using terrestrial lidar data along a 10-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-day Nor'Easter (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.