Acoustic classification of zooplankton

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Date
1998-02Author
Martin Traykovski, Linda V.
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https://hdl.handle.net/1912/5351Location
Georges BankGulf of Maine
DOI
10.1575/1912/5351Keyword
Underwater acoustics; Zooplankton; Endeavor (Ship: 1976-) Cruise EN253; Oceanus (Ship : 1975-) Cruise OC262Abstract
Work on the forward problem in zooplankton bioacoustics has resulted in the identification of
three categories of acoustic scatterers: elastic-shelled (e.g. pteropods), fluid-like (e.g. euphausiids),
and gas-bearing (e.g. siphonophores). The relationship between backscattered energy and animal
biomass has been shown to vary by a factor of —19,000 across these categories, so that to make
accurate estimates of zooplankton biomass from acoustic backscatter measurements of the ocean,
the acoustic characteristics of the species of interest must be well-understood. This thesis
describes the development of both feature based and model based classification techniques to
invert broadband acoustic echoes from individual zooplankton for scatterer type, as well as for
particular parameters such as animal orientation. The feature based Empirical Orthogonal
Function Classifier (EOFC) discriminates scatterer types by identifying characteristic modes of
variability in the echo spectra, exploiting only the inherent characteristic structure of the acoustic
signatures. The model based Model Parameterisation Classifier (MPC) classifies based on
correlation of observed echo spectra with simplified parameterisations of theoretical scattering
models for the three classes. The Covariance Mean Variance Classifiers (CMVC) are a set of
advanced model based techniques which exploit the full complexity of the theoretical models by
searching the entire physical model parameter space without employing simplifying
parameterisations. Three different CMVC algorithms were developed: the Integrated Score
Classifier (ISC), the Pairwise Score Classifier (PSC) and the Bayesian Probability Classifier
(BPC); these classifiers assign observations to a class based on similarities in covariance, mean,
and variance, while accounting for model ambiguity and validity. These feature based and model
based inversion techniques were successfully applied to several thousand echoes acquired from
broadband (-350 kHz - 750 kHz) insonifications of live zooplankton collected on Georges Bank and
the Gulf of Maine to determine scatterer class. CMVC techniques were also applied to echoes
from fluid-like zooplankton (Antarctic krill) to invert for angle of orientation using generic and
animal-specific theoretical and empirical models. Application of these inversion techniques in situ
will allow correct apportionment of backscattered energy to animal biomass, significantly
improving estimates of zooplankton biomass based on acoustic surveys.
Description
Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 1998
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Suggested Citation
Thesis: Martin Traykovski, Linda V., "Acoustic classification of zooplankton", 1998-02, DOI:10.1575/1912/5351, https://hdl.handle.net/1912/5351Related items
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