From two dimensions to three: the use of multibeam sonar for a new approach in fisheries acoustics

Gerlotto, François; Soria, Marc; Fréon, Pierre

doi:10.1139/cjfas-56-1-6

Cited by 58 publications

(78 citation statements)

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“…Some promising early results have been obtained [2,4], but data processing standards must be developed before the technology will be suitable for standard surveying. In the next section, an approach to data handling is proposed.…”

Section: Multibeam Echosoundingmentioning

confidence: 99%

“…This new functionality is of particular interest to the fisheries acoustics community, for a variety of reasons. Firstly, it is expected that much more detailed information about fish distributions can be derived from multibeam echosounder data, because multibeam systems offer 3-dimensional data compared to the conventional 2-dimensional data sets collected using single beam echosounders [2]. Furthermore, the fact that the same instrument and same data sets can be shared between fisheries researchers and hydrographers offers an interesting new perspective, leading to savings in instrumentation and survey costs.…”

Section: Introductionmentioning

confidence: 99%

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Model inversion for midwater multibeam backscatter data analysis

et al. 2005

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Furthermore, various features can be tagged to each sounding, such as the backscatter energy value and some statistical parameters of the multibeam ping from which the sounding was obtained. The term data node is used to describe the sounding and its associated feature vector. The set of data nodes serves as the basis for further advanced spatio-temporal data mining techniques. Soundings can be clustered into coherent groups, each cluster representing an object in the water column, such as a fish school. Cluster features are obtained from the feature tags of their contained data nodes, giving rise to feature vectors for each cluster. Clusters can be classified into classes of different types, using each cluster's feature vector. When a cluster is thought of as a fish school, it can be classified according to fish species or age group, for example.The concept of a set of data nodes is a versatile concept that can be extended further, enabling the application of more advanced clustering and classification algorithms.

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Section: Multibeam Echosoundingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Model inversion for midwater multibeam backscatter data analysis

et al. 2005

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“…22,30,31) 25) cross-fan beam sonar, 23,24) and omnidirectional sonar, 22) which can scan vertical planes, should be used for this purpose. Since many research vessels install a quantitative echo sounder and such a sonar, 22,32) can use the several beams oriented downward to measure SV vertically and vertical scan to obtain the 3D distribution of fish, so that only by such sonar the proposed method is realizable.…”

Section: Discussionmentioning

confidence: 99%

Section and Total Scattering Strengths of Individual Fish Schools

Furusawa

2011

J. Marine Acoust. Soc. Jpn.

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“…1) (Gerlotto et al 1999;Nøttestad and Axelsen 1999) was pole-mounted on the side of a 6.4 m boat with the transducer submerged to a depth of 1 m (Guillard et al 2006a). The 60 beams (beam dimensions 1.5°a thwartships and 17° along ships) allowed for a 90°a thwartship observation plane, oriented perpendicularly to the bottom and parallel to the surface (sonar was orientated at 45° to the vertical perpendicular to the line of travel-see Fig.…”

Section: Materials and Proceduresmentioning

confidence: 99%

“…Three-dimensional internal spatial structure of young-of-the-year pelagic freshwater fish provides evidence for the identification of fish school species Jean Guillard 1 , Paul Fernandes 2 , Thomas Laloë 3 , and Patrice Brehmer 4 More recently, three-dimensional (3D) observations of entire fish schools (Gerlotto et al 1999;Mayer et al 2002;Paramo et al 2010) or Antarctic krill shoals (Brierley and Cox 2010) have been used in ecological and behavioral studies (Gerlotto et al 2004;Brehmer et al 2006;Guillard et al 2010): however, these have been seldom used for species identification. In this article, we report on investigations into the internal 3D morphological characteristics of pelagic fish schools (Partridge 1982), recorded using a high resolution multibeam sonar, to discriminate between two species of freshwater fish.…”

mentioning

confidence: 99%

Three‐dimensional internal spatial structure of young‐of‐the‐year pelagic freshwater fish provides evidence for the identification of fish school species

Guillard¹,

Fernandes

Laloë

et al. 2011

Limnology & Ocean Methods

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Active acoustic detection and characterization in three dimensions (3D) with multibeam sonars is a powerful technique for ecological studies of schooling fish. The alpine Lake Annecy provides ideal conditions for sampling fish with active acoustic methods: it has calm water, low species diversity, and the density of pelagic fish schools is high. We carried out investigations on the internal 3D morphological characteristics of young-of-theyear (Y-O-Y) pelagic fish schools, using high resolution multibeam sonar in the vertical plane. The objective was to discriminate between the two fish species that school in the lake: perch (Perca fluviatilis) and roach (Rutilus rutilus). To discriminate between these Y-O-Y fish species, we used only one characteristic of their internal spatial structure: the total number of vacuoles, defined as empty volumes inside the school, relative to the school volume. Two distinct linear relationships between school volume and the total number of vacuoles were determined. These two types were consistent with the proportions of the percentage occurrence of the two different species as obtained from pelagic trawl sampling in 2004. In 2008, perch was dominant (93%) in the lake, and only one relationship was detected: this relationship corresponded closely to the one in 2004 attributed to perch. Thus, we assume that the schooling behavior is a phenotypic expression that could be used for remote fish species identification.*Corresponding author: E-mail: patrice.brehmer@ird.fr AcknowledgmentsThis work was supported by the ANSON project (INRA, IRD, IFRE-MER), and we are grateful to the CRH (IRD, IFREMER, UM II; Sète) who provided facilities. The second survey was financially supported by the INRA EFPA department, under the grant 'Innovative Project.' The software used for sonar data extraction was developed during the EU project AVITIS. Special thanks to Yvon Guennegan (IFREMER; Sète) for his help during the first survey, Michel Colon for his help during the two surveys, and Nicolas Givaudan (INRA; Thonon) for previous data analyses. We also thank Marc Taquet (IFREMER; French Polynesia) who attempted to identify species by scuba diving during the 2008 survey. Finally, we are grateful to Keith Mutch of Marine Scotland for producing the 3D graphic.

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From two dimensions to three: the use of multibeam sonar for a new approach in fisheries acoustics

Cited by 58 publications

References 0 publications

Model inversion for midwater multibeam backscatter data analysis

Model inversion for midwater multibeam backscatter data analysis

Section and Total Scattering Strengths of Individual Fish Schools

Three‐dimensional internal spatial structure of young‐of‐the‐year pelagic freshwater fish provides evidence for the identification of fish school species

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