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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. [ABSTRACT FROM AUTHOR]

Very high-resolution satellite imagery (≤5 m resolution) has become available on a spatial and temporal scale appropriate for dynamic wetland management and conservation across large areas. Estuarine wetlands have the potential to be mapped at a detailed habitat scale with a frequency that allows immediate monitoring after storms, in response to human disturbances, and in the face of sea-level rise. Yet mapping requires significant fieldwork to run modern classification algorithms and estuarine environments can be difficult to access and are environmentally sensitive. Recent advances in unoccupied aircraft systems (UAS, or drones), coupled with their increased availability, present a solution. UAS can cover a study site with ultra-high resolution (<5 cm) imagery allowing visual validation. In this study we used UAS imagery to assist training a Support Vector Machine to classify WorldView-3 and RapidEye satellite imagery of the Rachel Carson Reserve in North Carolina, USA. UAS and field-based accuracy assessments were employed for comparison across validation methods. We created and examined an array of indices and layers including texture, NDVI, and a LiDAR DEM. Our results demonstrate classification accuracy on par with previous extensive fieldwork campaigns (93% UAS and 93% field for WorldView-3; 92% UAS and 87% field for RapidEye). Examining change between 2004 and 2017, we found drastic shoreline change but general stability of emergent wetlands. Both WorldView-3 and RapidEye were found to be valuable sources of imagery for habitat classification with the main tradeoff being WorldView’s fine spatial resolution versus RapidEye’s temporal frequency. We conclude that UAS can be highly effective in training and validating satellite imagery. [ABSTRACT FROM AUTHOR]