Assessing the Effectiveness of Seagrass Detection Using Drone and Sonar Based Methods

Seagrasses and other submerged aquatic vegetation (SAV) provide critical nearshore habitats. Information on the location, extent, and condition of SAV resources in Mississippi (MS) and Alabama (AL) is often crucial in coastal management decision-making, like permitting for dock or pier construction, sediment dredging for navigation, living shoreline construction, and others. We are evaluating the benefit and challenges of using drones and sonar for detecting and mapping SAV in nearshore, shallow, and optically complex waters to support coastal management and permitting needs in the region. We are researching these technologies to determine the conditions under which each method is most cost-effective, maximizes efficiency, and yields high-accuracy data that can improve management strategies and outcomes. Results indicate that drone platforms can detect most SAV in shallow waters at low tide. Sonar data is more difficult to extract and process, and further sampling is required to provide a sufficient database with which to compare against aerial imagery. Regression and ordination techniques will be needed to cross-validate aerial imagery with sonar maps. Having recommendations under which conditions each method is most suited can provide easier decision-making for natural resource managers.