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Advances in sonar technology have revolutionized our ability to map the seafloor, however, differences between legacy and modern data pose challenges when analysing multi-source datasets. Acoustic backscatter recorded via multibeam echosounder is commonly used to characterize the seafloor, but a lack of standardized calibration often yields relative rather than absolute backscatter measurements, hindering comparison between surveys. ‘Bulk shift’ methods have been developed for harmonizing legacy backscatter datasets using overlapping survey areas for relative statistical calibration. This becomes increasingly difficult, though, given many datasets collected over extensive time periods. Backscatter data were collected in the Bay of Fundy, Canada, using multiple sonar systems and vessels over an 18-year period. Here, we propose a reproduceable strategy for harmonizing this large volume of disparate backscatter data using the bulk shift method. A final, harmonized map is presented for the entire Bay of Fundy and is validated using in situ observations from seafloor imagery. [ABSTRACT FROM AUTHOR]

Modern multibeam echosounders can record backscatter data returned from the water above the seafloor. These water-column data can potentially be used to detect and map aquatic vegetation such as kelp, and thus contribute to improving marine habitat mapping. However, the strong sidelobe interference noise that typically contaminates water-column data is a major obstacle to the detection of targets lying close to the seabed, such as aquatic vegetation. This article presents an algorithm to filter the noise and artefacts due to interference from the sidelobes of the receive array by normalizing the slant-range signal in each ping. To evaluate the potential of the filtered data for the detection of aquatic vegetation, we acquired a comprehensive water-column dataset over a controlled experimental site. The experimental site was a transplanted patch of giant kelp (Macrocystis pyrifera) forest of known biomass and spatial configuration, obtained by harvesting several individuals from a nearby forest, measuring and weighing them, and arranging them manually on an area of seafloor previously bare. The water-column dataset was acquired with a Kongsberg EM 2040 C multibeam echosounder at several frequencies (200, 300, and 400 kHz) and pulse lengths (25, 50, and 100 μs). The data acquisition process was repeated after removing half of the plants, to simulate a thinner forest. The giant kelp plants produced evident echoes in the water-column data at all settings. The slant-range signal normalization filter greatly improved the visual quality of the data, but the filtered data may under-represent the true amount of acoustic energy in the water column. Nonetheless, the overall acoustic backscatter measured after filtering was significantly lower, by 2 to 4 dB on average, for data acquired over the thinned forest compared to the original experiment. We discuss the implications of these results for the potential use of multibeam echosounder water-column data in marine habitat mapping. [ABSTRACT FROM AUTHOR]