313
toring techniques can investigate large sea areas
quickly and thus is an effective method; this
technique was also used for the monitoring of
seamounts (Kloser 1996 ; Komatsu et al. 2002b ).
However, seaweed beds may have been formed
around the sea- hills in the shallow sea areas, such
as offshore natural reefs, and for these sea-hills,
there is the need to develop new techniques
taking into account the estimation of larvae and
juveniles distributed in and around the seaweed
beds. Therefore, in this study, we summarized the
problems facing the development of these new
methods to provide an example of the solutions.
3.2
Measuring Technique
Proposal for Offshore
Seaweed Beds
Seaweed beds play a very important part in the
coastal ecosystem because they provide larvae
and juveniles with places for growing and hiding
and fi sh and seaweed-eating animals with feeding points and also have such functions as CO 2
fi xation and the purifi cation of water quality (e.g.,
Mann 1973 ; Komatsu et al. 2005 ). The main
methods for studying the distribution of seaweed
beds in coastal shallow water areas include visual
inspection from a vessel, diving inspection by
quadrate survey, and image analysis using aerial
photos or satellite images (e.g., Norris et al. 1997 ;
Komatsu et al. 2002a , c ). However, these methods are not appropriate because much time and
labor are required, and there will be effects of
waves and ocean conditions in offshore hills far
away from land. One of the possible techniques
for estimating the distribution and quantity of
seaweed beds in these areas is an acoustic method
using a quantitative echo sounder. An acoustic
method is an underwater remote sensing method
by which an ultrasonic wave is sent to an object
in the sea and information about the sea can be
obtained from the refl ected intensity of the wave
returned from the object (MacLennan and
Simmonds 1992 ).
Because seaweeds are distributed along the
seabed, there are some problems when they are
used as the objects of an acoustic study. First of
all, there will be cases where the echo reaction of
the seabed and that of seaweeds is overlaid, and
thus these echo reactions must be distinguished
from each other. Next, it should be noted that a
large number of fi sh, especially larvae, juveniles,
and plankton, exist in and around seaweeds.
Therefore, in this study, we introduce a method to
separate and distinguish the seaweed bed by a
three-stage method. In the fi rst stage, seafl oor
discrimination will be made by obtaining the
standard values for seafl oor discrimination using
the discriminatory analysis method, which is
used in the process of binarized image processing. In the second stage, the adult fi sh and larvae
and juveniles swimming in and around the seaweed bed will then be separated and distinguished by the frequency difference method
using multiple frequencies. In addition, the
examination of the method for identifying the
seaweed bed from acoustic data based on
the optimum combinations obtained will be
conducted. The outcome will be used to make
space interpolation by kriging in order to estimate the distribution of seaweeds. Examples of
the application of the measuring technique at
Hachiri-ga- se in 2012 and 2013 will be described
below:
First stage: seafl oor discrimination using the
binarized discriminatory analysis method
To avoid the overestimation of echoes from the
seafl oor based on the sound intensity obtained
by a quantitative echo sounder, there is a need
to separate and discriminate the echoes from
the seabed by fi xing a threshold value for
sound intensity in the post-processing. In the
past, this threshold value was empirically
fi xed on the basis of an echogram (echographic data). Thus in the Hachiri-ga-se survey, we adopted a mathematical method
involving the discriminatory analysis by
binarized image processing, which was developed by Hamano et al. ( 2005 ) for sound intensity, thereby excluding empirical judgments at
the time of conducting the separation and discrimination (see Fig. 4 : example results in
Hachiri-ga-se).
New Monitoring Method to Assess the Marine Algae Distribution and Fish School…
toring techniques can investigate large sea areas
quickly and thus is an effective method; this
technique was also used for the monitoring of
seamounts (Kloser 1996 ; Komatsu et al. 2002b ).
However, seaweed beds may have been formed
around the sea- hills in the shallow sea areas, such
as offshore natural reefs, and for these sea-hills,
there is the need to develop new techniques
taking into account the estimation of larvae and
juveniles distributed in and around the seaweed
beds. Therefore, in this study, we summarized the
problems facing the development of these new
methods to provide an example of the solutions.
3.2
Measuring Technique
Proposal for Offshore
Seaweed Beds
Seaweed beds play a very important part in the
coastal ecosystem because they provide larvae
and juveniles with places for growing and hiding
and fi sh and seaweed-eating animals with feeding points and also have such functions as CO 2
fi xation and the purifi cation of water quality (e.g.,
Mann 1973 ; Komatsu et al. 2005 ). The main
methods for studying the distribution of seaweed
beds in coastal shallow water areas include visual
inspection from a vessel, diving inspection by
quadrate survey, and image analysis using aerial
photos or satellite images (e.g., Norris et al. 1997 ;
Komatsu et al. 2002a , c ). However, these methods are not appropriate because much time and
labor are required, and there will be effects of
waves and ocean conditions in offshore hills far
away from land. One of the possible techniques
for estimating the distribution and quantity of
seaweed beds in these areas is an acoustic method
using a quantitative echo sounder. An acoustic
method is an underwater remote sensing method
by which an ultrasonic wave is sent to an object
in the sea and information about the sea can be
obtained from the refl ected intensity of the wave
returned from the object (MacLennan and
Simmonds 1992 ).
Because seaweeds are distributed along the
seabed, there are some problems when they are
used as the objects of an acoustic study. First of
all, there will be cases where the echo reaction of
the seabed and that of seaweeds is overlaid, and
thus these echo reactions must be distinguished
from each other. Next, it should be noted that a
large number of fi sh, especially larvae, juveniles,
and plankton, exist in and around seaweeds.
Therefore, in this study, we introduce a method to
separate and distinguish the seaweed bed by a
three-stage method. In the fi rst stage, seafl oor
discrimination will be made by obtaining the
standard values for seafl oor discrimination using
the discriminatory analysis method, which is
used in the process of binarized image processing. In the second stage, the adult fi sh and larvae
and juveniles swimming in and around the seaweed bed will then be separated and distinguished by the frequency difference method
using multiple frequencies. In addition, the
examination of the method for identifying the
seaweed bed from acoustic data based on
the optimum combinations obtained will be
conducted. The outcome will be used to make
space interpolation by kriging in order to estimate the distribution of seaweeds. Examples of
the application of the measuring technique at
Hachiri-ga- se in 2012 and 2013 will be described
below:
First stage: seafl oor discrimination using the
binarized discriminatory analysis method
To avoid the overestimation of echoes from the
seafl oor based on the sound intensity obtained
by a quantitative echo sounder, there is a need
to separate and discriminate the echoes from
the seabed by fi xing a threshold value for
sound intensity in the post-processing. In the
past, this threshold value was empirically
fi xed on the basis of an echogram (echographic data). Thus in the Hachiri-ga-se survey, we adopted a mathematical method
involving the discriminatory analysis by
binarized image processing, which was developed by Hamano et al. ( 2005 ) for sound intensity, thereby excluding empirical judgments at
the time of conducting the separation and discrimination (see Fig. 4 : example results in
Hachiri-ga-se).
New Monitoring Method to Assess the Marine Algae Distribution and Fish School…