Model-based sediment classification using single-beam echosounder signals

Abstract

Acoustic remote sensing techniques for mapping sediment properties are of interest due to their low costs and high coverage. Model-based approaches directly couple the acoustic signals to sediment properties. Despite the limited coverage of the single-beam echosounder (SBES), it is widely used. Having available model-based SBES classification tools, therefore, is important. Here, two modelbased approaches of different complexity are compared to investigate their practical applicability. The first approach is based on matching the echo envelope. It maximally exploits the information available in the signal but requires complex modeling and optimization. To minimize computational costs, the efficient differential evolution method is used. The second approach reduces the information of the signal to energy only and directly relates this to the reflection coefficient to obtain quantitative information about the sediment parameters. The first approach provides information over a variety of sediment types. In addition to sediment mean grain size, it also provides estimates for the spectral strength and volume scattering parameter. The need to account for all three parameters is demonstrated, justifying computational expenses. In the second approach, the lack of information on these parameters and the limited SBES beamwidth are demonstrated to hamper the conversion of echo energy to reflection coefficient.

Technical note: Bathymetry observations of inland water bodies using a tethered single-beam sonar controlled by an unmanned aerial vehicle

“…Detailed bathymetry maps of inland water bodies are essential for simulating flow dynamics and forecasting flood hazard (Conner and Tonina, 2014;Gichamo et al, 2012;Schäppi et al, 2010), predicting sediment transport and streambed morphological evolution (Manley and Singer, 2008;Nitsche et al, 2007;Rovira et al, 2005;Snellen et al, 2011), and monitoring instream habitats (Brown and Blondel, 2009;Powers et al, 2015;Strayer et al, 2006;Walker and Alford, 2016). Whereas exposed floodplain areas can be directly monitored from aerial surveys, riverbed topography is not directly observable from airborne or space-borne methods (Alsdorf et al, 2007).…”

Seafloor monitoring west of Helgoland (German Bight, North Sea) using the acoustic ground discrimination system RoxAnn

“…However, most of the discussion is on the approaches, rather than on the classification itself (Snellen et al 2011). For subsequent classification of RoxAnn data, numerous studies have presented interpolated E1 and E2 maps (e.g., Mielck et al 2012Mielck et al , 2014Henriques et al 2015) and/or transect maps showing the E1 and E2 parameters separately and/or merged together (e.g., Hamilton et al 1999;Serpetti et al 2011).…”

Acoustic scattering from a sandy seabed at the target and reverberation experiment 2013 (TREX13)

“…[1,2] In this study, normal incidence measurements were taken over a frequency range of 5 to 10 kHz at the Target and Reverberation Experiment conducted off the coast of the Florida panhandle in May of 2013. These data were compared with 400 kHz multibeam backscatter measurements and video images to determine the correlation of reflection coefficient measurements and backscattering.…”