Presenter: Alexander Seymour (United States Geological Survey)

Description:
Large scale dune feature timeseries are uncommon but can provide valuable insight regarding the vulnerability of communities and habitats to coastal hazards. The United States Geological Survey maintains a multi-decadal record of dune crest and toe features along the U.S. Atlantic and Gulf coasts based on point cloud data from state and regional-scale lidar surveys. Dune features are digitized using an automated process and extensive manual quality control as described in Stockdon and Others, 2009. A dune feature timeseries was compiled for North Carolina barrier islands. The data record includes 12 lidar surveys collected between 1996 and 2018, covering all North Carolina barrier coastlines 6-12 times. The compilation of the dune features’ position and elevation records allows for island and sub-island-scale classification of dunes by height, as well as by historical trends in transgression/progradation and accretion/erosion. Regression analysis and K-Medoids clustering was used to classify types of dune morphological change at 500 m alongshore intervals to capture trends at the alongshore scale of smaller coastal communities. Results were then aggregated at the scale of North Carolina state political boundaries and inlet or cape-bounded barrier islands. The three scales of processing were chosen to represent scales at which different types of management activity and physical processes may occur. The classifications can provide a basis for assessing the effectiveness of dune management, determining vulnerability to storm conditions, or quantifying the morphological and evolutionary differences between natural and anthropogenic dunes.