Seafloor classification using a multibeam echo sounder: a new rugosity index coupled with a pixel-based process to map Mediterranean marine habitats
Viala, C.; Lamouret, M.; Abadie, A. (2021). Seafloor classification using a multibeam echo sounder: a new rugosity index coupled with a pixel-based process to map Mediterranean marine habitats. Applied Acoustics 179: 108067. https://dx.doi.org/10.1016/j.apacoust.2021.108067
Multibeam echo sounders (MBES) have been commonly used over the last decades in hydrography to perform bathymetric measurements with high precision and provide backscatter imagery of the seafloor. Although seafloor classification techniques have been recently developed using MBES backscatter imagery, few semi-automated or completely automated methods joining acoustic imagery and bathymetric data to map marine habitats exist today. In order to fill this gap, a pixel-based data treatment process was designed to provide map of marine habitats coupling the rugosity computed from bathymetry and the backscattering data. In this way, a specific rugosity index, called Bathymetric Automated Treatment for the Classification of the Seafloor (BATCLAS), was developed by computing the least square fitting on the bathymetric soundings in order to obtain a metric value of the seascape unevenness. The whole process relies on a software suite specifically created to treat and edit acoustic data from MBES, using classification algorithms based on customisable decision trees. Tested on an acoustic data set acquired along the French Mediterranean coast with a R2Sonic 2022 MBES and validated with field observations, this method allowed to detect and map with accuracy marine habitats such as complex rocky substrates, Posidonia oceanica (L.) Delile seagrass meadows and artificial structures.
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