Extended Detection of Shallow Water Gas Seeps From Multibeam Echosounder Water Column Data

Abstract

Multibeam echosounder water column data provides a three-dimensional image of features between the water surface and the seafloor. Although this swath of acoustic data can be collected over a wide range of angles, most of the data, at least beyond the range to the first seafloor return, is contaminated by noise created by receiver array sidelobe interference. As a result, the water column data beyond the minimum slant range commonly is excluded from analysis. This paper demonstrates a method to consistently filter and extract targets comprising a gas seep feature across the multibeam swath, including targets within the areas dominated by receiver array sidelobe interference. For each sample range, data are filtered based on the mean plus a certain number (k) of standard deviations of the sample values along that range. The filtering is coupled with a morphological classification to retain only targets of interest while excluding background data and noise. Data were collected over a shallow water artificial gas seep using two different flow rates and at three different vessel speeds. Using the proposed method, 119 of 124 test seeps were identified correctly. Seep targets were identified at all angles across the water column fan up to beam pointing angles of 55°, with 19 of 23 seeps being correctly identified at angles greater than 50°. This method demonstrates that features can be extracted and geolocated in the sidelobe noise when the interference is appropriately filtered. These results will improve the areal extent of multibeam surveys and increase the utility of acoustic data in capturing information on water column targets directly above the seafloor.

Mapping warming reefs—An application of multibeam acoustic water column analysis to define threatened abalone habitat

“…The water column data from the multibeam data record (all and.wcd format) were read into Matlab using the open-source CoFFee toolbox (https://github.com/alexschimel/CoFFee). The water column samples were filtered using subsequent custom Matlab scripts based on Nau et al (2022) to eliminate most of the unwanted noise while retaining targets likely to be signal from vegetation (Figure 1B). Figure 1C shows that the filtering algorithm permitted the assessment of 'targets' close to the seafloor to be retained limiting only those points within 1 m of the seafloor.…”

“…The first steps were to remove the high amplitude signals from the seafloor using a model to estimate the spreading of the seafloor signal across all beams, as well as an amplitude threshold to remove residual spreading from sharp rocky features. The across-track sidelobe noise was filtered using a threshold calculated from the raw sample amplitudes (dB) from each sample range equal to the mean plus two times the standard deviation of all samples along that sample range (Figure 2A) (Nau et al, 2022). A final threshold Frontiers in Remote Sensing frontiersin.org filter of −30 dB was applied to remove remaining low amplitude noise (Figure 2B).…”

“…The water column acoustic record enables the identification of ecological features that extend into the water column. This improved spatial resolution of water column data collected from acoustic multibeam systems has only become possible because of availability of complex computing power that this method relies on, but also in new acoustic methods being developed (Schimel et al, 2020;Nau et al, 2022;Porskamp et al, 2022). One of these developments includes new filtering algorithms to reduce the feature space of acoustic targets in the water column and refine the analysis to the features of interest such as isolating those points that are within 1 m distance of the seafloor, similar to the methods identified by Porskamp et al (2022).…”

Volume Backscattering Strength Estimation of Plankton from Water Column Multibeam Echosounder Data at Alor Strait, East Nusa Tenggara, Indonesia

“…A promising option for researching plankton dynamics in the water column is provided by developments in acoustic technology, notably the use of multibeam echosounders water IOP Publishing doi:10.1088/1755-1315/1276/1/012065 2 column data. A multibeam echosounder (MBES) is a standard acoustic tool for conducting geophysical surveys in marine environments [6]. Multibeam echosounder technology, in particularly water column data, allows us to get comprehensive data on the spatial distribution of suspended matters in the water at various depths.…”

“…Multibeam echosounder technology, in particularly water column data, allows us to get comprehensive data on the spatial distribution of suspended matters in the water at various depths. There are several advantages of water column data use such as: gas seep detection [6] [7], estimation of suspended sediment concentration [8] [9], and detection of fish shoals [10]. Hence, this study investigates the advantages of using multibeam echosounder to detect other suspended matters, plankton abundance.…”