DEVELOPMENT OF A CLASSIFICATION SCHEME AND DIGITIZATION PROTOCOL FOR ARTIFICIAL FEATURES ALONG ESTUARINE SHORELINES IN SOUTH CAROLINA

Estuarine shorelines are mobile coastal features that can impact populated upland areas and adjacent structures due to chronic erosion. Shoreline armoring is frequently used to protect property and other structures such as docks, piers, and bridges from further erosion. Many studies have performed mapping of these stabilized structures using head-up digitization within GIS using aerial imagery. Recently, a project was conducted in the South Carolina ACE Basin to map historical estuarine shorelines and calculate erosion and accretion rates using the R package: Analyzing Moving Boundaries Using R (AMBUR). Additionally, artificial shoreline features were mapped along both upland and tidal channel shorelines in order to determine which structures are most susceptible to shoreline erosion. In order to facilitate the analyses, a new classification scheme was devised by creating a modified hierarchal system from existing schemes developed by researchers in North and South Carolina. This new system catalogues hard structures in a way that is more flexible and expandable to accommodate new or previously unmapped structure types and facilitates GIS-based querying and analysis within AMBUR. Within the GIS, features are attributed by classification type, date of imagery, and quality of imagery used. Features are represented either as polygons, polylines, or points depending on what is most applicable for analysis with shoreline change data. Structures like seawalls and revetments are digitized as polylines, while causeways and docks are digitized as polygons. Furthermore, delineation of these features can also assist with creating hydro-enforced, LiDAR-derived DEMs through the removal of bridges, causeways, and other artificial features that “disrupt” flow in a DEM if they are not removed. A primary goal of the structure mapping phase of the project is to provide a technique that is repeatable and adaptable to include a variety of artificial shoreline features found world-wide. Current efforts are centering on using Pictometry or oblique imagery to further improve the detail and resolution of the mapping of these features. In the future, using these datasets, the studies will focus on providing historical rates of shoreline armoring of these artificial features.