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• W2797667029 abstract "Abstract Seagrass ecosystems provide a multitude of ecosystem services by acting as a nursery, limiting erosion, improving water clarity, and acting as a globally-significant sink for atmospheric carbon dioxide. Despite the value of these services being estimated at $1.9 trillion, seagrass ecosystems are in global decline. As study of submerged aquatic vegetation (SAV) increase, specialized techniques are needed to map habitat coverage in regions which are largely inaccessible to current methods. Chief among these habitat types are seagrass meadows residing at depths of 1 m or less which are most susceptible to anthropogenic disturbance including physical disturbance. To encourage study of shallow SAV at large spatial scales a side scan sonar array was developed to efficiently map seagrass beds residing in 1 m or less of water. Constructed from consumer-grade sonar components the array cost approximately 10% of commercial units used in previous studies. The horizontal swath of the array in 1 m of water averaged 50 m in total (port plus starboard), allowing efficient study of large areas. Validation with satellite and aerial imagery of a large and highly-disturbed seagrass meadow demonstrates the array's capacity to produce high-resolution imagery (up to 2.5 cm/pixel) with sufficient spatial accuracy to produce detailed maps of seagrass habitat structure in very shallow environments. Results demonstrate operational readiness of the array, including benefits over traditional optical surveys during periods of high algal cover. The implications of an efficient, low-cost alternative to current mapping methods of seagrass habitats are discussed and a schematic for array construction is provided." @default.
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• W2797667029 date "2018-07-01" @default.
• W2797667029 modified "2023-09-27" @default.
• W2797667029 title "Side scan sonar: A cost-efficient alternative method for measuring seagrass cover in shallow environments" @default.
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• W2797667029 doi "https://doi.org/10.1016/j.ecss.2018.04.017" @default.
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