The Experts below are selected from a list of 15 Experts worldwide ranked by ideXlab platform
Pierre Fréon - One of the best experts on this subject based on the ideXlab platform.
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From two dimensions to three: the use of multibeam sonar for a new approach in Fisheries acoustics
Canadian Journal of Fisheries and Aquatic Sciences, 1999Co-Authors: François Gerlotto, Marc Soria, Pierre FréonAbstract:We present a methodology applying multibeam sonar for three-dimensional (3D) observation of Fish Schools that enhances the conventional use of vertical scientific echo sounders. The sonar we employ has 60 beams of 1.5° each. Its working frequency is 455 kHz. It is applied on a vertical plan normal to the vessel route, observing from the surface line to the bottom with a range set to 100 m. The sampled volume is 14 times larger than the volume observed with vertical echo sounding. The contribution of this new methodology to Fisheries acoustics is detailed for school classification, internal school structure, spatial distribution of Schools, Fish behaviour, and biomass estimates. For each of these points, we present some preliminary results with the aim of defining the real progress in Fisheries acoustics research as a result of 3D acoustics. Finally, we present a list of technical and methodological improvements that we are developing in order to make multibeam sonar fully adapted to Fisheries acoustics.
François Gerlotto - One of the best experts on this subject based on the ideXlab platform.
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From two dimensions to three: the use of multibeam sonar for a new approach in Fisheries acoustics
Canadian Journal of Fisheries and Aquatic Sciences, 1999Co-Authors: François Gerlotto, Marc Soria, Pierre FréonAbstract:We present a methodology applying multibeam sonar for three-dimensional (3D) observation of Fish Schools that enhances the conventional use of vertical scientific echo sounders. The sonar we employ has 60 beams of 1.5° each. Its working frequency is 455 kHz. It is applied on a vertical plan normal to the vessel route, observing from the surface line to the bottom with a range set to 100 m. The sampled volume is 14 times larger than the volume observed with vertical echo sounding. The contribution of this new methodology to Fisheries acoustics is detailed for school classification, internal school structure, spatial distribution of Schools, Fish behaviour, and biomass estimates. For each of these points, we present some preliminary results with the aim of defining the real progress in Fisheries acoustics research as a result of 3D acoustics. Finally, we present a list of technical and methodological improvements that we are developing in order to make multibeam sonar fully adapted to Fisheries acoustics.
Marc Soria - One of the best experts on this subject based on the ideXlab platform.
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From two dimensions to three: the use of multibeam sonar for a new approach in Fisheries acoustics
Canadian Journal of Fisheries and Aquatic Sciences, 1999Co-Authors: François Gerlotto, Marc Soria, Pierre FréonAbstract:We present a methodology applying multibeam sonar for three-dimensional (3D) observation of Fish Schools that enhances the conventional use of vertical scientific echo sounders. The sonar we employ has 60 beams of 1.5° each. Its working frequency is 455 kHz. It is applied on a vertical plan normal to the vessel route, observing from the surface line to the bottom with a range set to 100 m. The sampled volume is 14 times larger than the volume observed with vertical echo sounding. The contribution of this new methodology to Fisheries acoustics is detailed for school classification, internal school structure, spatial distribution of Schools, Fish behaviour, and biomass estimates. For each of these points, we present some preliminary results with the aim of defining the real progress in Fisheries acoustics research as a result of 3D acoustics. Finally, we present a list of technical and methodological improvements that we are developing in order to make multibeam sonar fully adapted to Fisheries acoustics.
Natheer Al Absi - One of the best experts on this subject based on the ideXlab platform.
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Classification of Fish Schools based on evaluation of acoustic descriptor characteristics
Fisheries Science, 2010Co-Authors: Aymen Charef, Seiji Ohshimo, Ichiro Aoki, Natheer Al AbsiAbstract:Acoustic surveys were conducted from 2002 to 2006 in the East China Sea off the Japanese coast in order to develop a quantitative classification typology of a pelagic Fish community and other co-occurring Fishes based on acoustic descriptors. Acoustic data were postprocessed to detect and extract Fish aggregations from echograms. Based on the expert visual examination of the echograms, detected Schools were divided into three broad Fish groups according to their schooling characteristics and ethological properties. Each Fish school was described by a set of associated descriptors in order to objectively allocate each echo trace to its Fish group. Two methods of supervised classification were employed, the discriminant function analysis (DFA) and the artificial neural network technique (ANN). We evaluated and compared the performance of both methods, which showed encouraging and about equally highly correct classification rates (ANN 87.6%; DFA 85.1%). In both techniques, positional and then morphological parameters were most important in discriminating among Fish Schools. Fish catch composition from midwater trawling validated the Fish group classification through one representative example of each grouping. Both methods provided the essential information required for assessing Fish stocks. Similar techniques of Fish classification might be applicable to marine ecosystems with high pelagic Fish diversity.
Aymen Charef - One of the best experts on this subject based on the ideXlab platform.
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Classification of Fish Schools based on evaluation of acoustic descriptor characteristics
Fisheries Science, 2010Co-Authors: Aymen Charef, Seiji Ohshimo, Ichiro Aoki, Natheer Al AbsiAbstract:Acoustic surveys were conducted from 2002 to 2006 in the East China Sea off the Japanese coast in order to develop a quantitative classification typology of a pelagic Fish community and other co-occurring Fishes based on acoustic descriptors. Acoustic data were postprocessed to detect and extract Fish aggregations from echograms. Based on the expert visual examination of the echograms, detected Schools were divided into three broad Fish groups according to their schooling characteristics and ethological properties. Each Fish school was described by a set of associated descriptors in order to objectively allocate each echo trace to its Fish group. Two methods of supervised classification were employed, the discriminant function analysis (DFA) and the artificial neural network technique (ANN). We evaluated and compared the performance of both methods, which showed encouraging and about equally highly correct classification rates (ANN 87.6%; DFA 85.1%). In both techniques, positional and then morphological parameters were most important in discriminating among Fish Schools. Fish catch composition from midwater trawling validated the Fish group classification through one representative example of each grouping. Both methods provided the essential information required for assessing Fish stocks. Similar techniques of Fish classification might be applicable to marine ecosystems with high pelagic Fish diversity.