The multibeam echosounder (MBES) has been widely used in seabed mapping, considering its ability to collect continuous and broad-scale seabed measurements efficiently. The presence of shellfish or dead shell material can alter the geophysical properties of the sediment and thus affect the MBES backscatter intensity, making acoustic surveys with the MBES a potential non-invasive solution for regularly monitoring the benthic habitats of shellfish aggregations. Although there exists an increasing interest in mapping marine benthos with MBES measurements recently, the use of multi-spectral backscatter data is still limited. Thus, this research aims to enhance the acoustic mapping of benthic habitats using multi-spectral MBES data, with a focus on a shell bed region in the Dutch North Sea. With backscatter measurements from three frequencies, 90, 300, and 450 kHz, we achieved seabed classification in two steps. First, a semi-supervised backscatter completion was conducted to generate full-coverage backscatter data for each incident angle, mitigating the limited overlap between adjacent survey lines. We then classified the multi-Angle backscatter data from each individual frequency using the Gaussian Mixture Model. Our results indicate an improved seabed classification performance compared to the classical Bayesian method. Comparisons of classification maps across frequencies also show their different abilities to distinguish the shell bed region from other coarse sediments, demonstrating the value of leveraging multi-spectral backscatter data in seabed habitat mapping.

Natural and man-induced coastal erosion endanger life and environment in coastal areas worldwide. For sedimentary barrier coasts, beach and underwater nourishments are an efficient coastal protection strategy. To optimize nourishments and to understand their impact on the marine environment, monitoring strategies are required. In this study, we investigate the potential of multibeam echosounder (MBES) data, providing both bathymetry and backscatter (BS), for monitoring the evolution of the nourished sediment and morphodynamics over time. A time series of seven MBES measurements, as well as two sets of box cores, vibrocores and seismic data were acquired of a channel-side nourishment near the Wadden Sea island Ameland (The Netherlands), between April 2017 and May 2019. In general, a high confidence of the acoustic reliability of the BS time series measurements is demonstrated. The unsupervised Bayesian classification method, supported by ground-truthing, is employed to produce a time series of sediment maps, revealing sediments ranging from sandy mud to sand with varying amounts of shell fragments. Based on the sediment maps, the nourished sediment could be distinguished from the natural sediment. Within one year, the shell-rich pre-nourishment seabed is recreated by washing out finer sediments, which are deposited towards the main tidal channel. Using the seismic data and vibrocores, the shell-rich pre-nourishment seabed could be identified in the subsurface after being buried by the nourishments, supporting the general findings. Furthermore, a rapid development of steep bedforms with increasing sediment sorting is observed in parts of the nourished areas. This study shows that high-resolution sediment maps obtained from a time series of MBES BS together with bathymetry reveal morphodynamic and sedimentary processes of nourishment evolution and can advance underwater nourishment strategies.

Multi-frequency backscatter data collected from multibeam echosounders (MBESs) is increasingly becoming available. The ability to collect data at multiple frequencies at the same time is expected to allow for better discrimination between seabed sediments. We propose an extension of the Bayesian method for seabed classification to multi-frequency backscatter. By combining the information retrieved at single frequencies we produce a multispectral acoustic classification map, which allows us to distinguish more seabed environments. In this study we use three triple-frequency (100, 200, and 400 kHz) backscatter datasets acquired with an R2Sonic 2026 in the Bedford Basin, Canada in 2016 and 2017 and in the Patricia Bay, Canada in 2016. The results are threefold: (1) combining 100 and 400 kHz, in general, reveals the most additional information about the seabed; (2) the use of multiple frequencies allows for a better acoustic discrimination of seabed sediments than single-frequency data; and (3) the optimal frequency selection for acoustic sediment classification depends on the local seabed. However, a quantification of the benefit using multiple frequencies cannot clearly be determined based on the existing ground-truth data. Still, a qualitative comparison and a geological interpretation indicate an improved discrimination between different seabed environments using multi-frequency backscatter.