Narrowband acoustic identification of monospecific fish shoals

Abstract

The extraction of highly discriminant features is crucial for successful species identification of fish shoals if backscattered narrowband signals do indeed contain discriminant information. Four different methods of feature extraction are described and applied to the same data, providing new descriptors expected to improve species identification. Echograms, amplitude probability density function (PDFs) and spectral features are used to describe acoustic images of single shoals. Image processing is used to improve signal shoal description, by taking into account the shoal structure and species-related spatial distribution. Three pelagic species are considered: sardine (Sardina pilchardus (Walbaum)), anchovy (Engraulis encrasicolus (L.)), and horse mackerel (Trachurus trachurus (L.)) detected during fisheries acoustics surveys conducted in the Bay of Biscay. A correct classification rate of 57% overall was found for data covering a mesoscale oceanographic environment and including seasonal variability. If space and time scales are reduced this value increased to 98%, emphasizing the value of non-acoustic and a priori information.

Preliminary data on horse mackerel (Trachurus spp) landings from Mauritanian waters

“…García Santamaría 24 ÍNDICE cies assessment. But a lot of studies have used techniques to get better knowledge about mixed resources, mainly through acoustic technologies (Massé et al, 1996;Scalabrin et al, 1996;Lawson et al, 2001;Mackinson et al, 2004;Doray et al, 2007;Llambrich and Alvarez, 2009). In other cases, important commercial fisheries occur in mixed shoals, and they are managed together (De Oliveira and Butterworth, 2004).…”

Section and Total Scattering Strengths of Individual Fish Schools

“…As one of the school features for species identification, the following "(school) section scattering strength" has been used 8,16,17) :…”

Accuracy of Acoustic Methods in Fish Stock Assessment Surveys

“…The basic idea for a more objective approach derived in the early 90s, with the development of specific software for automatic extraction of school parameters and by further testing the hypothesis that school features can be used for school species identification (Scalabrin et al, 1992(Scalabrin et al, , 1996Reid & Simmonds 1993;Georgakarakos & Paterakis 1993). This approach triggered the development of sophisticated expert systems for species identification, where the artificial neural networks (ANNs) provided a promising solution (Ramani & Patrick, 1992;Dunne, 2007).…”