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Seafloor Characterization Using Multibeam Echosounder Backscatter Data: Methodology and Results in the North Sea

1
Acoustics Group, Faculty of Aerospace Engineering, Delft University of Technology, P.O. Box 5058, 2600 GB Delft, The Netherlands
2
Department of Geomatics Engineering, Faculty of Civil Engineering and Transportation, University of Isfahan, 81746-73441 Isfahan, Iran
3
Conservation Ecology Group, Groningen Institute for Evolutionary Life Sciences, University of Groningen, P.O. Box 11103, 9700 CC Groningen, The Netherlands
4
Delft University of Technology, Hydraulic Engineering, 2629 HS Delft, DELTARES, P.O. Box 177, 2600 MH Delft, The Netherlands
*
Author to whom correspondence should be addressed.
Geosciences 2019, 9(7), 292; https://doi.org/10.3390/geosciences9070292
Received: 29 May 2019 / Revised: 24 June 2019 / Accepted: 28 June 2019 / Published: 30 June 2019
(This article belongs to the Special Issue Geological Seafloor Mapping)
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Abstract

Seafloor characterization using multibeam echosounder (MBES) backscatter data is an active field of research. The observed backscatter curve (OBC) is used in an inversion algorithm with available physics-based models to determine the seafloor geoacoustic parameters. A complication is that the OBC cannot directly be coupled to the modeled backscatter curve (MBC) due to the correction of uncalibrated sonars. Grab samples at reference areas are usually required to estimate the angular calibration curve (ACC) prior to the inversion. We first attempt to estimate the MBES ACC without grab sampling by using the least squares cubic spline approximation method implemented in a differential evolution optimization algorithm. The geoacoustic parameters are then inverted over the entire area using the OBCs corrected for the estimated ACC. The results indicate that a search for at least three geoacoustic parameters is required, which includes the sediment mean grain size, roughness parameter, and volume scattering parameter. The inverted mean grain sizes are in agreement with grab samples, indicating reliability and stability of the proposed method. Furthermore, the interaction between the geoacoustic parameters and Bayesian acoustic classes is investigated. It is observed that higher backscatter values, and thereby higher acoustic classes, should not only be attributed to (slightly) coarser sediment, especially in a homogeneous sedimentary environment such as the Brown Bank, North Sea. Higher acoustic classes should also be attributed to larger seafloor roughness and volume scattering parameters, which are not likely intrinsic to only sediment characteristics but also to other contributing factors. View Full-Text
Keywords: multibeam echosounder; seafloor sediment classification; geoacoustic inversion; angular calibration curve; least squares cubic spline approximation multibeam echosounder; seafloor sediment classification; geoacoustic inversion; angular calibration curve; least squares cubic spline approximation
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Amiri-Simkooei, A.R.; Koop, L.; van der Reijden, K.J.; Snellen, M.; Simons, D.G. Seafloor Characterization Using Multibeam Echosounder Backscatter Data: Methodology and Results in the North Sea. Geosciences 2019, 9, 292.

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