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Statistical analysis for digital processing of pelagic fish echoes

Statistical analysis for digital processing of pelagic fish echoes



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Specyfikacja książki
Ilość stron
Rok wydania
2005 - wyd. I



15,00 zł

Sonar has for a long time been a tool used to study the ocean. Among its many applications, sonar is employed to help remotely classify distributions of biological organisms such as pelagic fish populations and plankton. Species, location, size distribution and behavior are among the important properties of the marine organisms. Knowledge of those properties aids in fish supply management and ecological study [149].
The amount of discussion about so-called sustainable fisheries is increasing worldwide. The crisis in a lot of big fisheries, e.g. salmon fisheries along the Pacific coast of the USA and Canada and cod fishery on the Grand Banks, must lead to different management regimes [22]. Moreover, natural phenomena have also taken their toll on the marine fisheries environment. El Nińo - a disruption of the ocean and atmosphere in the tropical Pacific -- has ravaged both Chilean and Peruvian fisheries. Similarly, some fishers in the North West Atlantic blame warmer waters and pollution for the scarcity and erratic migration patterns of coldwater fish like cod. But it is inadequate fisheries management and policies that are mostly to blame [l34]. The FAO reported in 2000 [28] that, globally, an estimated 25% of the fish stocks are under or moderately exploited, 50% of stocks are fully exploited, 15% are over exploited and about 10% have been depleted or are recovering from depletion. As a result of international cooperation a number of conventions are signed to prevent further overfishing of marine resources. In particular, the countries of the Baltic Sea commit themselves to take all appropriate measures to counter and prevent pollution to control the environment of the Baltic Sea in a sustainable way. The Convention on the Protection of the Marine Environment of the Baltic Sea Area (Helsinki Convention), originally signed in 1974 and later updated in 1992 is administered by the Helsinki Comission (HELCOM).
In fishery research, acoustical techniques have been increasingly important over the years [85]. Following the pioneering work of Sund [155], acoustical technology has had a major impact on fishing. With sonar it is possible to search a substantial volume of water at great speed. Alternative sampling methods as trawl fishing are
vary -low by comparison [80]

Spis treści:

List of symbols and acronyms

1. Introduction
1.1.   Introduction into acoustic methods of fish population estimation
1.2.   The objectives of the dissertation
1.3.   Chapters overview

2.   Scattering of sound from underwater objects
2.1.   Wave equation
2.2.   Helmholtz-Kirchhoff integral
2.3.   Scattering from geometrical objects
2.3.1.    Scattering from sphere
2.3.2.    Scattering from cylinder
2.4.   Fish acoustic scattering properties
2.4.1.    Target strength and scattering cross section
2.4.2.    Fish target strength
2.5.   Fish scattering models
2.5.1.    Resonant frequency model
2.5.2.    Tilted cylinder model of swimbladdered fish
2.5.3.    Finite bent cylinder model
2.5.4.    Low-resolution acoustic model
2.5.5.    Kirchhoff-Ray-Mode model
2.5.6.    Boundary-element model

3.   Fish target strength estimation
3.1.   Analysis and the model of hydroacoustic fish echo
3.1.1.    The model of the echo formation process
3.1.2.    Echo counting
3.1.3.    Echo integration
3.1.4.    Scattering analysis for fish schools
3.2.   Overview of fish target strength estimation methods
3.2.1.    Ex situ fish target strength estimation methods
3.2.2.    In situ fish target strength estimation methods
3.3.   Direct fish target strength estimation methods
3.3.1.    Dual-beam method
3.3.2.    Split-beam method
3.4.   Indirect target strength estimation methods
3.4.1.    Craig-Forbes method
3.4.2.    Ehrenberg method
3.4.3.    Deconvolution method.
3.4.4.    Single beam integral equation formulation

4.   Inverse techniques applied to fish target strength estimation
4.1.   Exact solutions of integral equations
4.2.   Regularization methods
4.2.1.    Tichonov regularization
4.2.2.    Maximum entropy regularization
4.3.   Decomposition methods
4.3.1.    Singular Value Decomposition method
4.3.2.    Wavelet-Vaguelette Decomposition method
4.4.   Expectation Maximization methods
4.4.1.    Expectation Maximization and Smoothing method
4.4.2.    Adaptive Expectation Maximization and Smoothing method

5.   Determination of the kernel for inverse problems in fishery acoustics
5.1.   Fish angular position in the transducer beam
5.2.   Transducer beam pattern PDF
5.3.   Influence of threshold on the beam pattern kernel
5.4.   Fish directivity pattern PDF

6.   Statistical analysis of acoustic survey data
6.1.   Targets strength single beam estimation vs dual beam estimation
6.1.1.    Direct dual beam estimation
6.1.2.    Indirect single beam estimation
6.1.3.    Comparison of inverse techniques
6.2.   Fish length estimation
6.2.1.    Single frequency approach
6.2.2.    Dual frequency approach
6.3.   Conclusions

7.   Non-signal methods in fishery research
7.1.   2D visualization techniques in fishery acoustics
7.2.   Modern hydroacoustic data processing
7.3.   Virtual reality modeling
7.4.   3D fish data visualization in VRML

Summary in English
Summary in Polish




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