31 Undergraduate and Graduate Posters with Lightning Talks (Posters)

Monday, 15 April 2024
1:30 PM - 5:30 PM
Grand Ballroom

ASSESSING EROSION RATES OF WESTMORELAND COUNTY CLIFFS BY INTEGRATING HISTORICAL DATA WITH DRONE-CAPTURED LIDAR, PHOTOGRAMMETRY, AND ARCGIS ANALYSIS

Paper number: 31-15
Program: Theme Sessions
Time: 1:30 PM – 5:30 PM

Authors

Abstract

Coastal cliffs are prominent features of coastal landscapes. Cliffs supply sediment for adjacent beaches; however, cliff retreat may pose hazards to coastal communities. Researchers must document historical retreat rates and investigate the responsible factors to better understand cliff erosion. This information may help local government officials and park staff manage the shoreline more effectively. Innovative drone technology now enables low-cost photogrammetry and LiDAR data collection. This study explores the application of drones for mapping coastal cliffs, particularly those at Westmoreland State Park along the Chesapeake Bay. LiDAR and photogrammetry data were collected using a DJI Matrice 300 drone to document the current condition of the cliffs. This data was used to compare the cliffs’ present state to historical imagery, and LiDAR was used to quantify the change in cliff volume.

In May 2023, one survey collected photogrammetry data, while a second survey in November 2023 collected both photogrammetry and LiDAR data. Orthomosaics were generated with the photogrammetry using Agisoft Metashape. The LiDAR data was used to create a three-dimensional model of the cliffs. A historical analysis was performed using Virginia Base Map Program orthophotos from 2002-2021 and ArcGIS analysis that found areas with emplaced mitigation strategies show accretion rates as high as around 2.5 m/yr, while areas where cliffs are exposed to wave attacks show erosion rates up to 0.56 m/yr on average. An additional survey will be collected in February, and an erosion rate will be calculated between the November and February surveys.

Geological Society of America Abstracts with Programs. Vol. 56, No. 2

doi: 10.1130/abs/2024SE-398205

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