Southeastern Section - 68th Annual Meeting - 2019

Paper No. 48-3
Presentation Time: 2:40 PM


SUNDIN, Gary1, LUCIANO, Katherine2, ARRINGTON, Tanner3, STONE, Benjamin1, CALLOWAY, Joshua4 and KINGSLEY-SMITH, Peter1, (1)South Carolina Department of Natural Resources, Marine Resources Division, 217 Fort Johnson Road, Charleston, SC 29412, (2)South Carolina Department of Natural Resources, Geological Survey, 217 Fort Johnson Road, Charleston, SC 29412, (3)South Carolina Department of Natural Resources, Land, Water & Conservation Division, 5 Geology Road, Columbia, SC 29212, (4)Colleton County, Technology Department, 31 Klein Street, Walterboro, SC 29488

Remotely-sensed imagery and elevation data are often used to detect geomorphological changes and to estimate rates of erosion and accretion of coastal shorelines. Understanding such changes is critical for management of human infrastructure and natural resources in coastal areas. Traditional methods of producing these datasets are expensive and time consuming. Furthermore, the relatively low resolution of these datasets can limit the effectiveness of some analytical approaches. By comparison, unmanned aerial vehicle (UAV) technology has improved in the last decade, and relatively inexpensive mapping-capable platforms are available ‘off-the-shelf’. Used with accurate ground control methods, these platforms can produce accurate, high resolution imagery and elevation products. Moreover, for small spatial extents, UAV products are more affordable and customizable than traditional alternatives.

We used a consumer-grade UAV to measure short-term geomorphological changes to dynamic coastal shorelines in South Carolina, USA. We flew pre-programmed grid patterns to capture overlapping photo series of shorelines at low tide. Using survey-grade ground control, we processed the photos to orthomosaics and digital surface models (DSMs). We empirically demonstrated that our UAV products had horizontal and vertical errors in the centimeter range. We used these UAV datasets and other remotely-sensed data to delineate shoreline features. We used Digital Shoreline Analysis (DSAS) software, Analyzing Moving Boundaries Using R (AMBUR) software, and other GIS methods to determine rates and direction of shoreline migration.

We showed that consumer grade UAVs can produce datasets useful for accurately measuring shoreline changes at fine spatial and temporal scales. These approaches will prove especially useful in coastal areas experiencing rapid geomorphological change. Within a broad context of monitoring landscape scale change using remotely sensed data, UAV methods may be useful for validating larger datasets and for providing fine detail for ‘hot-spots’. UAVs will also be useful for detailed research in highly dynamic areas, allowing for the detection of geomorphological changes on the order of centimeters in scale over periods as short as weeks or months.