nerc.ac.uk

Identification of Southern Ocean acoustic targets using aggregation backscatter and shape characteristics

Woodd-Walker, Rachel S.; Watkins, Jonathan L.; Brierley, Andrew S.. 2003 Identification of Southern Ocean acoustic targets using aggregation backscatter and shape characteristics. ICES Journal of Marine Science, 60 (3). 641-649. 10.1016/S1054-3139(03)00062-6

Full text not available from this repository. (Request a copy)

Abstract/Summary

Acoustic surveys for biomass estimation require accurate identification of echoes from the target species. In one objective technique for identifying Antarctic krill, the difference between mean volume-backscattering strength at two frequencies is used, but can misclassify small krill and other plankton. Here, we investigate ways to improve target identification by including characteristics of backscattering energy and morphology of aggregations. To do this, multi-frequency acoustic data were collected concurrently with target fishing of Antarctic krill and other euphausiid and salp aggregations. Parameter sets for these known aggregations were collated and used to develop empirical classifications. Both linear discriminant-function analysis (DFA) and the artificial neural network technique were employed. In both cases, acoustic-backscattering energy parameters were most important for discriminating between Antarctic krill and other zooplankton. However, swarm morphology and other parameters improved the discrimination, particularly between krill and salps. Our study suggests that for krill-biomass estimates, a simple DFA based on acoustic-energy parameters is a substantial improvement over current dB-difference acoustic methods; but studies requiring the discrimination of zooplankton other than krill must still be supported by target fishing.

Item Type: Publication - Article
Digital Object Identifier (DOI): 10.1016/S1054-3139(03)00062-6
Programmes: BAS Programmes > Antarctic Funding Initiative Projects
ISSN: 1054-3139
Additional Keywords: acoustics, artificial neural network, Euphausia superba, krill, linear discriminant analysis, South Georgia, Southern Ocean, zooplankton
NORA Subject Terms: Marine Sciences
Zoology
Ecology and Environment
Date made live: 16 Feb 2012 11:36
URI: http://nora.nerc.ac.uk/id/eprint/13078

Actions (login required)

View Item View Item