Salt marshes provide important services to coastal ecosystems in the southeastern United States. In many locations, salt marsh habitats are threatened by coastal development and erosion, necessitating large-scale monitoring. Assessing vegetation height across the extent of a marsh can provide a comprehensive analysis of its health, as vegetation height is associated with Above Ground Biomass (AGB) and can be used to track degradation or growth over time. Traditional methods to do this, however, rely on manual measurements of stem heights that can cause harm to the marsh ecosystem. Moreover, manual measurements are limited in scale and are often time and labor intensive. Unoccupied Aircraft Systems (UAS) can provide an alternative to manual measurements and generate continuous results across a large spatial extent in a short period of time. In this study, a multirotor UAS equipped with optical Red Green Blue (RGB) and multispectral sensors was used to survey five salt marshes in Beaufort, North Carolina. Structure-from-Motion (SfM) photogrammetry of the resultant imagery allowed for continuous modeling of the entire marsh ecosystem in a three-dimensional space. From these models, vegetation height was extracted and compared to ground-based manual measurements. Vegetation heights generated from UAS data consistently under-predicted true vegetation height proportionally and a transformation was developed to predict true vegetation height. Vegetation height may be used as a proxy for Above Ground Biomass (AGB) and contribute to blue carbon estimates, which describe the carbon sequestered in marine ecosystems. Employing this transformation, our results indicate that UAS and SfM are capable of producing accurate assessments of salt marsh health via consistent and accurate vegetation height measurements.

Oysters support an economically important fishery in many locations in the United States and provide benefits to the surrounding environment by filtering water, providing habitat for fish, and stabilizing shorelines. Changes in oyster reef health reflect variations in factors such as recreational and commercial harvests, predation, disease, storms, and broader anthropogenic influences, such as climate change. Consistent measurements of reef area and morphology can help effectively monitor oyster habitat across locations. However, traditional approaches to acquiring these data are time-consuming and can be costly. Unoccupied aircraft systems (UAS) present a rapid and reliable method for assessing oyster habitat that may overcome these limitations, although little information on the accuracy of platforms and processing techniques is available. In the present study, oyster reefs ranging in size from 30 m2 to 300 m2 were surveyed using both fixed-wing and multirotor UAS and compared with ground-based surveys of each reef conducted with a real-time kinematic global positioning system (RTK-GPS). Survey images from UAS were processed using structure from motion (SfM) stereo photogrammetry techniques, with and without the use of ground control point (GCP) correction, to create reef-scale measures of area and morphology for comparison to ground-based measures. UAS-based estimates of both reef area and morphology were consistently lower than ground-based estimates, and the results of matched pairs analyses revealed that differences in reef area did not vary significantly by aircraft or the use of GCPs. However, the use of GCPs increased the accuracy of UAS-based reef morphology measurements, particularly in areas with the presence of water and/or homogeneous spectral characteristics. Our results indicate that both fixed-wing and multirotor UAS can be used to accurately monitor intertidal oyster reefs over time and that proper ground control techniques will improve measurements of reef morphology. These non-destructive methods help modernize oyster habitat monitoring by providing useful and accurate knowledge about the structure and health of oyster reefs ecosystems.

Inlet Barrier Islands (IBIs) are infrequently studied, and are often poorly represented in coastal lidar records. The fetch limited barrier island (FLBI) model was introduced to describe geomorphic changes of IBIs over time. The FLBI model predicts that the morphology of IBIs should remain largely static during predominate weather conditions due to sheltering from oceanic wave energy but undergo significant erosion when local and non-local waves magnify during storms, subsequently failing to recover volume and elevation losses. Using three years of high-frequency small unoccupied aircraft systems (sUAS, aka drone) surveys and existing lidar records, we document geomorphic changes on Bird Shoal (a protective IBI near the town of Beaufort, NC) resulting from storms and predominate conditions, testing the FLBI model and documenting island evolution. Our results indicate that Bird Shoal exhibits different spatial trends in erosion, accretion, and shoreline migration across its 4 km length, likely driven by varying shoreline orientation to the Beaufort Inlet and back barrier bathymetry in Back Sound. Our data indicate that the geomorphic behavior of Bird Shoal currently does not adhere to the classic FLBI model. Foreshore storm recovery and growth on Western Bird Shoal and shoreline retreat on Central Bird Shoal occurred during predominate conditions, and beach morphology was not an artifact of past storm events. The Western Bird Shoal shoreline consistently retreated landward in decades of historic imagery, but transitioned to seaward expansion sometime between 2011 and 2014. This shift is likely driven by erosion of the western end of Shackleford Banks and concurrent widening of the Beaufort Inlet, allowing increased wave energy to enter the back-barrier sound and push flood deltas onto Bird Shoal during predominate conditions. Our results suggest that open ocean inlet width and location interact with back-barrier deltas to control sediment supply and wave energy for IBIs, and that IBIs may fall into and out of conformance with the FLBI archetype over time. This study demonstrates sUAS deploying frequently over a municipal scale to fill spatial and temporal gaps in traditional coastal remote sensing datasets.