Post on 07-Jul-2018
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
1/25
US Army
Corps
of
Engineers®
Engineer
Research
and
Development
Center
Aquatic
Plant Control Research
Program
Advanced
Digital Processing
of
Echo
Sounder
Signals
for
Characterization
of
Very
Dense
Submersed
Aquatic
Vegetation
Bruce M .
Sabol,
Janusz
Burczynski,
and
Joel Hoffman September
2002
Approved fo r publ ic
release; distribution
is
unl imited.
2 0 0 3 0 1 0 9
6 6
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
2/25
Th e ontents
of
this eport re
ot o e se d
or dvertising,
publication,
r romotional
urposes. itation
of
trade
ames
does
no t
constitute
an
official endorsement or
approval
of
the us e
of such
commercial
products.
Th e indings
of this
report
ar e no t to
be
construed
as
an
official
Department of
the
Army position,
unless
so designated
by
other
authorized
documents.
®
PRINTED ON RECYCLED PAPER
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
3/25
Aquatic
Plant
Control RDC/EL TR-02-30
Research Program eptember
2002
Advanced
Digital
Processing
of
Echo
Sounder
Signals for
Characterization
of
Very
Dense
Submersed
Aquatic
Vegetation
by
Bruce M . Sabo l
Envi ronmental Laboratory
U.S . Army Engineer
Research and
Development
Center
3909
Halls
Ferry Road
Vicksburg,
M S
9180-6199
Janusz
Burczynsk i
Biosonics, Inc.
4027 Leary Way
Seatt le, WA 8107
Joel Hoffman
Virginia
Institute
of
M ar ine
Science
RO .
Box
1346
Gloucester
Point, VA 3062
Final
report
Approved
fo r
public release;
distribution
is unlimited
Prepared
for
U.S .
Army
Corps
of Engineers
Washington,
DC
0314-1000
Under ork
Unit 33118
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
4/25
Contents
Preface
v
1—Introduction
2—Methods
Site
Description
Analyses
3—Results
—Discussion 6
SF298
in
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
5/25
Preface
The work reported herein was conducted jointly by th e U.S.
Army Engineer
Research and
Development
Center
(ERDC), Environmental
Laboratory
(EL),
Vicksburg,
M S,
and
Biosonics,
Inc., Seattle, W A , under the
provisions
of
th e
Cooperative
Research
and
Development
Agreement
(CRDA-Ol-EL-01)
between
ERDC and Biosonics,
Inc.
unding fo r this work
was
provided b y th e
Aquatic
Plant Control
Research
Program (APCRP), ERDC, work unit
number
33118.
The
APCRP
is
sponsored
b y
Headquarters ,
U.S.
Army
Corps
of
Engineers ,
(HQUSACE),
and is assigned to
ERDC
under
purview
of
th e
EL .
he
APCRP
is
managed
under th e Center
fo r
Aquatic
Plant
Research
and
Technology
(CAPRT) ,
Dr.
John
W .
Barko,
Director.
M r. Robert
C.
Gunkel,
Jr., EL , was
Associate
Director
fo r
the CAPRT. rogram Monitor
during
this
study
was
Mr.
Timothy
R.
Toplisek,
HQUSACE.
This paper was
originally
presented at th e
Symposium
fo r
Acoustics
in
Fisheries
and
Aquatic
Ecology,
Montpel l ier ,
France, June 10-14, 2002.
This report was prepared
by
M r.
Bruce
M.
Sabol,
Environmental
Systems
Branch (ESB), Ecosystem Evaluation
and
Engineering
Division
(EEED), EL ,
ERDC;
Dr.
Janusz
Burczynski,
Biosonics,
Inc.;
and
Mr.
Joel
Hoffman,
Virginia
Institute
of
Marine
Science.
This
investigation
was
performed
under
th e
general supervision
of
Dr.
Edwin
A. Theriot,
Director,
EL ;
Dr.
David
J. Tazik,
Chief,
EEED;
and
Mr.
Harold
W.
West,
Chief, ESB.
A t
th e t ime
of
publicat ion
of
this report, Director
of
ERDC was Dr.
James R.
Houston.
omma nder
and
Executive
Director
was
COL.
John
W .
Morris
III,
EN .
This report
should
be
cited
as follows:
Sabol,
B.
M .,
Burczynski, J. ,
and Hoffman, J.
2002).
Advanced digital
processing of echo
sounder signals
fo r
characterization
of
very dense
submersed aquatic vegetation, ERDC/EL TR-02-30,
U.S.
Army Engineer
Research and Development Center, Vicksburg,
MS.
Th e contents ofthis
report
are
not
to be usedfor advertising
publication
or
promotional
purposes.
itation
of
trade names
does
no t
constitute an
official
endorsement
or
approval
for
th e us e ofsuch commercial products.
I V
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
6/25
1
Introduction
Characterizing
submersed
aquatic
vegetation (SAV)
is
important
fo r
a
variety
of
purposes
including
ecological
assessments,
impact
analyses
of
huma n
activities,
and
planning
control
operations
to
manage
nuisance
aquatic
plants.
Until
recently,
th e
standard
techniques
for
characterizing
SA V
distribution
and
conditions
were
b y
manual
means (grab
and
rake samples,
and
diver
observation
and
collection)
and
remote
optical
techniques
(aerial
photography
and digital
satellite
image
analysis).
Manual
techniques
provided
detailed
and
accurate
information, but
only
fo r
very
l imited
areas.
Remote
optical
techniques
provide
a
large-area
synoptic view of SA V
distr ibution
but only in
l imited
detail. These
techniques
are l imited b y water clarity,
commonly
underestimating
extent
of
SA V in
deeper
waters.
Recently,
an automated digital
technique
was
developed
that
employs
a
digital
echo sounder,
global
positioning
system, and digital signal
processing
on
a
PC in near
real
time.
1
'
2
This
technique
fills th e
void
in
methodology
b y rapidly
providing
high-resolution
information
on SA V
canopy
geometry from
a small survey
boat.
The
boat-based
system
consists of
a
digital
echo
sounder
and
a
real-time
differentially
corrected
global
positioning
system
(GPS)
l inked
to a laptop
PC .
The
hydroacoustic
component
is
a Biosonics
DT4000
digital
echo
sounder
(Biosonics, Inc.,
Seattle,
W A ,
3
with
a 420-kHz,
6-deg,
single-beam transducer
that
generates
short
(0.1-ms) monotone
pulses
(pings) at
a user-set
rate.
Return
echoes
are
digitized
at
high
frequency
and
dynamic
range
(122
dB).
These
data
are
stored
on
th e
hard
drive
of
th e
PC
that
operates
th e
system.
Interspersed
with
these
signal
data are GPS position
reports
(latitude
and
longitude)
recorded
at a
slower
rate (0.5 to 1.0
s
1
) from a real-time differentially
corrected
GPS, using
broadcasted
corrections.
The system
is
typically operated b y
traversing
preselected
transects
in
a small
survey boat, using GPS navigation guidance.
Operating speed
is
l imited
to
approximately
2.5
m
s
1
to avoid
cavitation
around th e transducer.
Transects are
B.
M.
Sabol,
and
J.
Burczynski.
(1998).
Digital echosounder
system fo r characterizing
vegetation in
shallow
water
environment ,
Proceedings
of
European
conference
on
underwater acoustics A.
Alippi
and
G. B.
Canelli,
ed., Rome,
165-171.
2
B.
M .
Sabol,
R.
E. Melton,
R.
Chamber la in , P.
Doering,
an d
K . Haunert . (2002).
Evaluation
of a digital echo
sounder
fo r
detection
of submersed aquatic
vegetation,
Estuaries 25(1),
133-141.
3
W .
C.
Acker,
J.
Burczynski,
J.
Dawson,
J.
Hedgepeth ,
and D.
Wiggins.
(1999).
Digital
transducers:
A new sonar technology, Se a Technology
40 , 31-35.
Chapter
Introduction
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
7/25
selected perpendicular to
th e
depth contours (if
known)
or the
local
shoreline
and
are
roughly
parallel
to
each
other
a t a fixed spacing. Under
typical
operations
(2.5-m
s
1
boa t speed
and
5
pings
s
1
)
in
2-m-deep
water,
a
circular
bottom
area
0.2
m
in
diameter
is
sampled every
0.5 m
along th e
transect. While this
is
less
than complete coverage, th e speed and/or ping rate m ay be adjusted
to
achieve
more complete coverage,
if
desired.
High spatial
resolution
mapping can
b e
performed
at
around
10
ha
hr
1
.
Higher
or
lower
rates,
with
associated
lo w and
higher
spatial
resolution,
can be
achieved
b y
adjusting
transect spacing.
The signal
fo r
a
typical
transect
containing
SA V is
illustrated
in
Figure 1 .
The
transducer
provides
information
on
th e
vertical distribution
of
echo intensity
within
th e water
column.
Motion
of
th e
survey
boa t
along
a
l inear
path
yields
a
two-dimensional
(2-D)
picture of echo
intensity.
The
bottom
usually
generates
th e strongest echo return and
is
characterized by th e sharpest rise
in
signal echo
intensity and typically by very l imited change in depth from
ping
to
ping.
A
flat,
unvegetated
bottom exhibits a strong return, with a signal thickness
roughly
equal to th e
pulse
width of
each
ping
(pulse
duration
[0.1
m s]
x speed of sound in
water
[1,500 m
s
1
] = 0.15
m ).
A t th e frequency used,
penetration
into th e bottom
is
negligible,
approximately
2
cm fo r
medium-grained
sand.
Figure
1.
Typical echogram with SAV
Vegetation usually exhibits a contiguous vertical echo return immediately
above th e bottom
that
is
weaker than th e
bottom
return but
stronger
than
ambient
water column noise. The depth of th e
to p
of th e vegetation canopy
is
much
more variable, from ping to ping, than that of th e bot tom,
because
of
patchiness
ofvegetation and local
variability
in
canopy height.
A signal mirroring th e
vegetation appears below th e bot tom, presumably th e result of reverberation
(multiple scattering)
of
th e signal
within
th e
vegetation.
When
vegetation or
large-scale bottom roughness occurs, th e signal around th e bottom appears
to
grow thicker,
indicating
a
wider
range of
time
fo r
which echoes
are
returning.
The signal
processing algorithm utilizes these features
to
detect and track th e
bottom,
and then to detect and characterize vegetation.
Chapter Introduction
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
8/25
The bottom depth
fo r
a
local
region (~ 2 to 3) is
estimated
b y
determining
th e
mode
of th e
depth
of
th e
primary
peak in
echo
intensity
within
th e
pings
situated
between
sequential
GPS
reports.
Once
th e
bottom is determined, th e
algori thm
searches
upward
from th e
detected
bottom
fo r plant-like
features. These
features
include a
contiguous
echo return
exceeding
a
user-set
threshold and
found
below
a quiet zone
attributed
to open water. The height
of
this feature closely matches
in
situ plant
canopy
height.
This
heuristic
algorithm
proceeds
through
a
se t
of
tests
to
sequentially
classify
each
ping
into one of
th e
following
classes:
NOISY,
OUT_OF_WATER,
TOO_DEEP,
UNCLASSIFIED,
BARE, and PLANT. The
first
four
classes
represent
pings
rejected
fo r
data
quality
reasons or
unvegetated
pings.
The
last
tw o
classes
are
arrived
at b y
processing
remaining
UNCLASSIFIED
pings
through
a
series of
tests
to
definitively
identify
unvegetated or
vegetated
conditions.
The
processor
outputs depth, plant
height,
and plant coverage at th e GPS
data rate. Plant
height
is
th e average plant height
of PLANT
pings
within
a
reporting
cycle
and
plant
coverage
is
th e
port ion
of
PLANT pings within a reporting cycle. The logic within this algorithm is
hardcoded,
al though
th e user m ay set th e intensity and depth thresholds to
optimize fo r site-specific conditions.
Initial development and testing of th e algorithm was performed in a
southwest
Florida
estuary
system
containing
bladed
grass
species of
SA V
and
a
hard
sandy
bot tom.
The
technology
fo r
th e
patented
processor,
originally
developed
b y
th e
U.S.
A r m y
Engineer
Research
and
Development
Center
(ERDC),
Vicksburg,
M S,
has
been
l icensed
to
Biosonics,
Inc.,
which
markets
th e
hardware
and
processor as
EcoSAV
version 1.0.
ince
initial
development,
th e
system
has
been used
in
a
wide
variety
of
locations
with
varying
conditions and
SA V species. It h as worked
well
under
ma ny
conditions
common
to SAV-
colonized
areas.
1
'
2
SA V
detection
performance
begins
to
deteriorate
when
conditions
severely
depart
from th e
original
testing
site
and
th e
inherent
assumptions
within
th e
logic.
Problems
m ay result
from
inappropriate
selection ofprocessing
parameters ,
occurrence
of conditions
that
violate
one or more of th e
inherent
assumptions
of
th e
processor,
or
insufficient information content
within
th e
signal to extract th e desired attributes.
Observed problem conditions
are
listed
in
Table
1,
along
with
probab le
causes
fo r
the problem
within
th e
algorithm,
th e
impact
on
th e
data,
and
possible
approaches
to
correct
th e
problem.
Fo r
any
deficiency
in
meeting
a processing objective,
it
must
b e
determined
whether there is
sufficient
information
content
in
th e
signal
to
extract
th e
desired
information
or, if not, to
determine
what type of
sensor
is
required
to
generate
a
signal containing th e extractable information. Obviously, it is desirable to
extract
as
much
information
as
possible
from an
existing
sensor
before
investing
in
new
sensors. Several approaches have
been
contemplated fo r
resolving
these
B.
Sabol
an d J. Burczynski, 1998, op. cit.
2
B Sabol, R. E. Melton, R. Chamberlain, P. Doering,
an d
K.
Haunert,
2002,
op . cit.
Chapter
Introduction
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
9/25
c
a
Q.
O
C O
8 O
GO'S
o>J2
3
O
toco
S
£5
ft
< p
o
*1? £
ft
O
i.
£
a -
S.g
01
i- 5
W-fflö
Si
to
3
£
c v
E
o
s
£
0>£
c r
-
8
o
2
e n
t
c »
£
u
o
.
O
g >
£
o
O)
3
Z TJ
to
f t
2
a
u
S5 3
is
_ o
O fc
«
$ c
o o
C O 0)
Jr
fl
ff
as
>
Q
o
o
to
3
(0
U
of
tg
°1&
»
T J
J O
Q.
C O
C
.1-5 I
Ä
o
to£
u
O
«-
||
: 8
W
c o
Ä
E
-1
O
D
|5
a
~
c
»
c
»
t:
o
>•
c
5
S
o
>
m
Q
E a
2
to
b o
i*S
o o S
c
E
c8
o
.
'S
ff
c o
O)
>
§
Iss
0.
c
o
♦ 5
N
u
2
«0
o
c
n
c
o
^t3
Ü
0)
Q
L.
o
o
O L
Ö)
JC
+3
3
1 0
0)
D C
1 0
c
o
i = 5
5S
B
n
Q
e
o
u
a
E
S
o
O
)
.2 „-c o
(0 Ä ♦ - to
t
t
S o
»
ö
5
S ..E
c
to
D
c
o c
(0
c
to
Q.P o
co
tn
to o
to
to O
to
U. J
u.
c
JS o
*l
o
5
S ff
Ü5
c
JO
c o
c o 5
£ c
Q, C O
*-
.2
1
ft
o
t
a
111
JS o
ft
S
to
s
|1
TJ
c
JS o
ft
>
to
«I
T J
si §
si? >
u
S^ C
«
Q.
Off
to
D
O
to o
E
c
S-8 §
c
o
i2S
Sff
Q- TJ
S
ff
£
ff
0-
J
8
I
ff
< °
§
>.TJ »
g-ff
its.
3
PS
JS
TJ
f t
TJ
C O
Ol
TJ
ID
E'
m
t
C O
to a
to
^
^
c
o o
J3 S 2
„-£
9-.2
E
W J
tO
1
. 2
« it
O Q.
§
s
S3
TJ
«0
c
J S
a
og
r a
O
S
I.
I
s
5
jo
•81
t
s
ft
s
C O
c
ss
ft
D
I*
C O
fil
fc-6
S-2
c
jo
Q.
C 0 0)
2 E
1 g
a. c
o
o
Z£
jo
Q.
2c5
f
°
8
S
I»
c
o
to
>
F
o
o
t3
«1
5
C £
r a
't ö
5
(A
o
O
ft
1
2»
c
8
Chapter
1
Introduction
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
10/25
limitations (Table 1 ) . These include developing different
processing approaches
using different or
multifrequency transducers an d split-beam
transducers.
To
improve performance of
the
processor
and
make it more effective under
a
wider
range ofconditions, we will examine each condition in light of these alternatives
to determining th e
best
approach fo r enhancing
the system's performance.
This
report examines
the
dense
canopy
problem
(conditions
6
an d
7
in
Table
1 )
by
using
multifrequency
acoustical
data
from
a dense
Myriophyllum
spicatum (milfoil)
site
collected over
th e
course of
a
growing season. Processor
outputs over
the growing season
are
examined
and
th e
signals
associated with
successful an d
unsuccessful
processing are characterized. In
particular, the results
ofusing a lower-frequency
transducer
in addition
to the frequency customarily
used are examined,
with
the expectation
that
the
lower frequency would
be
less
sensitive to th e vegetation and
thereby
have
better
ability to penetrate
the
vegetated
canopy an d correctly track the
bottom.
Specific recommendations ar e
offered
fo r
means to improving
processing
under
th e
dense canopy
condition.
Finally, a
concept fo r
a
configurable
logic
software processor is described in
which
the
user
would
define
th e logical
tests
performed
in
addition
to defining
the
features
an d
threshold
levels
used,
thereby
enabling
greater flexibility
in
tailoring
the
processor
to
specific
site conditions.
Chapter Introduction
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
11/25
2
Methods
Site
Description
A
site
seasonally
colonized
b y
extremely
dense
patches
of milfoil was chosen
near
th e
Montlake
C ut
(Seattle, WA), a
boating
channel
that
connects
Lake
Washington
to
th e
Puget
Sound.
A t
this
site,
a fixed
t ransect
was
selected
that
included a shallow beach with sparse milfoil, a deep channel lacking vegetation,
and
a
shallow
flat where
milfoil
canopies
had
been
observed
to
reach
th e
surface
during
late summer .
Sampling
fo r species
composition
and
regions
of
dense
plant
colonization
was
completed
during
th e
previous
summer ,
1
when
plants
could
be
easily
observed
from
th e surface.
Sampling was completed with a
128-kHz,
6-deg,
single-beam BioSonics D E
transducer, a 418-kHz,
6-deg,
single-beam BioSonics D E transducer, and a
JR C
2000 differential
GPS.
The
transducers were deployed
at
th e surface
on
a
pole-mount
attached to th e research vessel. The
transducers
were
not
operated
simultaneously;
one
pass
of th e transect was completed
with
each
transducer.
Both
transducers
were
set to
operate
at 5
pings
s
1
with
a
pulse-width
of
0.1
msec
and
threshold
of-130 dB , verified settings.
2
The transect was
sampled
on
four
different
dates
throughout
th e growing
season,
representing
late winter
growth
(27 Mar 2001), early
growth
(15 Ju n
2001),
midsummer
growth (13
July 2001), and peak
summer
growth
(16
A ug
2001).
On-board
navigation
was completed using a commercia l navigational
software package.
Transects were not
perfectly
replicated
because of weather
conditions and presence of recreational boaters;
at mos t transects differed by
15
m. In
th e analysis, we did not assume that th e exact same plant locations were
sampled
on
repeated surveys, and
we
therefore did
not
a t tempt
any one-to-one
matching
between
surveys.
Rather,
regions
within
th e
t ransect
were
considered
to
represent
th e
same
general
location,
which
probab ly
has
similar plant
conditions.
J. Burczynski
an d
J. Hoffman,
unpublished
data.
2
B. Sabol, R. E. Melton, R. Chamberlain, P.
Doering,
and
R. Haunert.
2002,
op. cit.
Chapter
2 M e thods
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
12/25
Analyses
Th e
path ofeach
transect
was
plotted
an d
clipping
points
were
selected
to
form
a common beginning
an d
ending
point fo r
al l
transects.
Echograms of
the
clipped
transects were
plotted
using common
scales
an d colorization to visualize
the
signal.
Parameters
fo r
signal processing were
selected
by
iteratively
processing the data to achieve maximum detection rates in al l areas except th e
unvegetated
channel (a list
of
specific parameters
used
in this processing may be
obtained
from
th e
first
author).
The
focus
of
this
analysis
is
on
bottom
detection,
which
is th e prerequisite
fo r
correct vegetation detection an d characterization.
Plots of th e detected
bottom
were generated fo r each
transducer
and survey to
detect successful versus
unsuccessful
processing.
Th e
echo intensity ofadjoining
pings
in
an area subject to late summer
processor
failure are
plotted
and
compared
with those from
the same location
taken
earlier
in
the growing season
during
which
th e
processing
was successful. Finally, output vegetation height
an d
bottom
depth
within this region
were
also
plotted
to identify specific modes
ofprocessor
failure.
Chapter
2
M e thods
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
13/25
3
Results
The
echograms (Figure
2)
representing th e 2-D distribution of echo
intensity
indicate that
similar
plant
regions
were
sampled in
repeated
surveys. Note that
echograms fo r th e 128- and
428-KHz
transducers
represent
horizontal
mirror
images
of each
other since they
were
ru n
in
opposite
directions
(128
K Hz
south
to north; 428 K Hz north to south).
Similar bathymetric condit ions are
evident
between t ransducer and
sampling month,
indicating no great depth differences
between
repeated
transects.
Canopy
development
is
evident
through th e growing season (Figure 2) .
In
March, th e milfoil is already quite tall
toward
th e south end of
th e transect; in
other areas,
it
is
evident
but relatively
short.
Fo r
subsequent
samplings in M ay
and July, th e milfoil
gets taller
and
apparently increases
in density.
Only th e
dredged channel
area
consistently
shows
little
to
no
plant growth.
T he Augus t
survey shows
a
considerably
different
condition.
The canopy
has
reached
maximum
height and
th e
bottom
is
not
evident
in
ma ny
locations,
particularly
with
th e 128-KHz
transducer.
Unlike
earlier
months,
echo
intensity
between
th e
canopy
to p and th e bottom has decreased.
The
detected
bottom
depth
fo r
a
280-m
segment
of
th e
transect
is
illustrated
(Figure
3) .
This
segment
is ru n
in a
northerly
or
southerly
direction
so that depth
is
plotted
against
latitude.
Slight
global
depth
adjustments
were
made
to
achieve
a
better
match
because
of
slight
variations
in water level and
depth
of t ransducer
mounting
from survey
to
survey.
Detected
depths ar e in close
agreement
fo r
March
and
M ay
surveys
fo r
both
transducers .
In
July,
th e
detected
bottom
is
occasionally
more
shallow
in areas of
dense
vegetation.
By
August,
th e
detected
depth
is
much more shallow
fo r
vegetated
areas,
particularly
fo r th e 128-KHz
transducer.
Within a
region
of
failed
bottom
detects
in th e August
survey
(around
latitude
47.64466
deg
N ),
th e
echo
intensities
fo r
four
adjoining
pings
are
plotted
(Figure
4)
fo r both
frequencies
and
March
and
August
surveys.
There
is
not
a
one-to-one
correspondence
between
pings from each
survey,
but
they
should be
representative
of
th e
same
approximate
location. A t
this
location
both
transducers
successfully
detected
th e
bottom
(around
3 m ) in
th e
March
survey
b ut
failed
in
th e
Augus t
survey
(Figure
3) . While
even
March
vegetation was
dense,
th e
bottom
mos t
often
generated
th e
largest
echo
returns
(typically
around
-4 7 dB
fo r
th e
128-KHz t ransducer
and
around
-4 0 dB
fo r
th e
428-KHz
transducer) .
By
August,
th e
canopy
to p
consistently
generates
th e
largest
echo
intensity.
A
minor
peak
corresponding
to
th e
bottom
is
evident
in th e August data,
but
it
is
typically
Chapter 3
esults
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
14/25
a. arch
survey,
128-KHz t ransducer
I
:
t
Ü
S M S
u
11
Bflraft?
jfUju^H
ji |jl i |jL,||(
,
.
~
~
^vr |ii i
w î^wp
V
WTfWgl
--:
:
b. ay survey,
128-KHz
t ransducer
c.
u ly
survey,
128-KHz t ransducer
d. ugus t survey,
128-KHz
t ransducer
Figure 2. Echograms
fo r
each sampl ing month and t ransducer used
Chapter
3
Resul ts
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
15/25
e. arch survey, 428-KHz t ransducer
f.
ay
survey,
428-KHz
t ransducer
g. u ly survey, 428-KHz t ransducer
h.
ugus t
survey,
428-KHz
t ransducer
Figure
2 . (Concluded)
1 0
Chapter 3 Resul ts
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
16/25
_ 4
onth
of
Survey
arch
M ay
- 4 - 8 ly
ugust
.5.6
47.644
7.6445
7.645
7.6455
Lat i tude
47.646
47.6465
a. 28-KHz
t ransducer
47.644
7.6445
7.645
7.6455
Lat i tude
47.646
47.6465
b.
28-KHz
t ransducer
Figure
3. Detected bottom depth
by
month and
t ransducers
Chapter
3 Resul ts
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
17/25
a. arch
survey
128-KHz
t ransducer;
depth approximately
3. 3
m
b.
arch
survey,
428-KHz
t ransducer; depth approximately 3. 2 m.
Figure 4. scil loscope view
of
four adjoining pings in
region
of
dense
milfoil
12 Chapter 3 Resul ts
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
18/25
c. ugus t
survey, 128-KHz
t ransducer; depth approximately
3. 2
m
d.
ugus t
survey,
428-KHz
t ransducer;
depth
approximately
3.0m
Figure
4.
Concluded)
Chapter
3
Resul ts
13
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
19/25
around
10 dB
below
that
of
th e
canopy
top.
For
the 428-KHz
transducer, this
bottom
peak
is
typically
th e second largest peak
after
th e canopy
top.
For
th e
128-KHz transducer, th e
bottom
peak
is less obvious,
frequently
being
th e
third
or
fourth
largest peak after
canopy
top.
Processor
outputs
within
this
problematic
region,
including
detected
depth
and to p
of
canopy,
are
illustrated
fo r the
March
and
August
surveys
(Figure
5).
The processor
generated
reasonable
values
fo r
th e
March
survey, based
on
comparison
with
th e
corresponding
echograms (Figure
2) .
Outputs fo r
th e
Augus t
survey show
tw o modes of
processor
failure.
The first
type
is failure
to
correctly
detect
th e
true
bottom
depth
(approximately
3.0
to 3.3
m).
This
subsequently
results
in
artificially lo w estimates of plant
height
and coverage because th e
algorithm looks upward from the detected bottom (actually canopy top) and
finds little additional vegetation.
A second mode of failure
is
evident when th e
bottom depth is correctly detected, but no vegetation
is
detected in spite of
obvious
vegetation
within
th e
echogram
at
that
location
(Figure
2) . This
is
specifically evident
fo r
th e
128-KHz t ransducer
at
location
47.64455
de g
in
August.
14
hapter
3 Results
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
20/25
-0.8
-4.8
-5.6
128 KH z detected
bottom
128 KH z detected
canopy
top
42 8 KH z detected bottom
42 8 KH z
detected
canopy
top
47.6445
7.6446
7.6447
7.6448
Latitude
47.6449
47.645
a.
arch
survey
-4.8
-5.6
120 KH z detected bottom
120 KH z detected canopy top
42 0 KH z detected bottom
42 0
KH z
detected canopy
top
47.6445
47.6446 7.6447 7.6448
Latitude
47.6449
47.645
b.
ugus t
survey
Figure
5. Processor
detected bottom
depth
and
canopy
height
within
dense
milfoil area
Chapter
3
Results
15
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
21/25
4
Discussion
Plants
exhibited
rapid
vertical
growth
during
th e
first
half
of th e
growing
season. Strong
contiguous
echo
signals
were
evident
from
th e
to p
of
th e
plants
to
th e bot tom,
indicating a fairly uniform distribution of scatterers
over
th e length of
th e stem. The
bottom
was
still
th e strongest acoustic target during this part of th e
season.
Later
in
th e
season, a
highly
reflective
canopy
developed
at th e to p of
th e
fully elongated stems and echo intensity below th e canopy
diminished
significantly.
This
would
b e
caused
either b y
a
reduct ion
of
b iomass
density
below
th e
fully
developed
canopy or
b y
reduced
acoustic
energy
penetrating
th e
canopy
to
measure
scatterers
below.
Frequently
th e
bottom
was
not
acoustically
visible
below
th e dense
canopy.
These
observations
are in
general
agreement
with
morphological
descriptions
of
milfoil
growth
and
canopy
formation
over
the
course
of
a
growth
season.
1
Early
in
th e
season, th e processing
algorithm
appeared
to perform well.
Bottom depths were consistent and reasonable,
and vegetation
showed
a steady
increase
in
height and density. A s th e canopy formed
later
in th e season, th e
bottom
tracking function progressively failed, resulting
in
subsequent failure
to
correctly detect and characterize vegetation.
Additional ly,
decreased signal from
plant
material
below
th e
canopy,
possibly
th e
result
of
sloughing
of
leaf
material
below th e
canopy,
1
frequently
resulted
in
no
detection of plants even
when
th e
true
bottom
was
successfully detected.
The authors originally hypothesized that th e lower-frequency
t ransducer
(128-KHz) would have better canopy penetration ability and would exhibit better
bottom tracking performance.
This was clearly not th e
case.
Between th e two, th e
higher-frequency t ransducer (428-KHz) exhibited a more
distinct
bottom
signal
under dense canopy conditions
and,
consequently, better bottom detection
performance.
This appears counterintuitive, since th e lower
frequency
is
less
sensitive
to
small
objects
(scattering b y plant material). Either way,
we
conclude
that lower
frequency
is
not
th e
direction
to
improved
performance. A sensor
option
not tested
as
part
of
this
study
is
th e
use
of
a
428-KHz
t ransducer
with
a
narrower beam width.
It m ay
be
possible fo r a narrower beam to more easily find
gaps in th e canopy and thus detect the bottom
with
greater
regularity.
J.
W .
Barko an d
R. M.
Smart.
(1981). Comparat ive
influences
of
l ight and
temperature
on
th e growth an d
metabolism
of selected
submersed
freshwater
macrophytes ,
cological Monographs
51(2),
219-235.
16 hapter 4 Discussion
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
22/25
The
modes
of
failure
point
to
directions fo r
seeking
performance
improvement.
Of
th e
two, th e second
is
most
easily addressed.
Here th e
processor
fails
to
detect vegetation represented b y a canopy reflectance but no contiguous
echo
signal above th e selected
threshold
between
th e canopy and
th e correctly
detected bot tom. The oscilloscope graphic (Figure 4) reveals that there is
in
fact a
contiguous signal, around
-80
to
-75
dB, depending
on
th e frequency,
below
th e
canopy top,
which is typically greater than that from the
open
water
quiet
zone.
The solution
is
simply
to
lower th e
noise and
plant
detection
threshold
to
that
level
(-70
dB and -65
dB were originally used fo r processing th e
128-KHz and
428-KHz
signals, respectively).
This
problem
originated from th e assumption
that
there must be a contiguous signal
between
th e
to p
and bottom of
th e
plants
to
generate a detection.
This
requirement
serves to
reject
suspended
and swimming
objects (fish)
within
th e water column, and it works
well
fo r
grass-like
SAV,
which
exhibit more uniform b iomass distribution
over
the height of
th e plants.
The
first
mode
of
failure
is more problematic.
Correct
bottom
tracking
fails
because
th e bottom is
obscured
b y
vegetation
and
represents
only
a
minor peak
within
th e signal. Several algorithm improvements m ay
b e
possible. Since th e
bottom
is
still
evident below
th e
canopy
(Figure
4)
as
a
secondary
or
tertiary
peak,
it
m ay be possible
to
histogram the depth of multiple peaks, weighting each
by
it s
ranking
within
th e
return signal,
or
b y
its
distance
to
th e
previously
estimated bottom depth. Another modification would be easier
to
implement but
would
have an
operational
requirement
in
th e ma nner
surveys are
performed.
The
depth
of
th e
first
object
encountered
above
a
se t
intensity
threshold is
easily
detected
and
is typically
th e
to p
of
th e
SA V canopy.
Multi temporal
surveys
of
a
fixed transect, designated b y
GPS
waypoints , could
be
performed.
Bottom
depths
could
accurately
b e
determined
based
on
processor
output
from
surveys
during
periods
of
lo w
vegetation.
These
could b e
combined
with
later
surveys
to
estimate
plant
height,
giving careful
attention
to
transect
navigation,
changes
in
water
level, and t ransducer mounting
depth.
These modifications and others yet
to
b e
identified
would require basic
coding
changes
to
th e
current
algorithm.
This
is
a
costly
operation
requir ing
t ime
to
make th e modifications
and
t ime
to
verify and
val idate
th e changes
with
testing.
It would
be fa r
superior
to
define specific
logic
tests
required
within
th e
algorithm
using an
input
configuration
file. This
has
given
rise
to
th e
concept
of
a
configurable
logic
processor.
Currently,
we
use
a
configuration
file
to
specify
all
intensity
and
depth/distance
thresholds
within
th e
algori thm,
al though
th e
logical
tests are hardcoded. Configurable logic would allow th e user to :
a.
dentify
channels to be used within a
multifrequency,
multiplexed signal.
b.
efine
th e
specific
features
to
be
extracted
and used.
c.
pecify filters and processors to
b e
ru n on
these
features, such
as
th e
moda l filter currently
used
fo r
bottom
tracking.
d.
pecify
th e
sequence of
logical
tests
performed
to
detect
and
quantify
attributes
of
th e
shallow
water
environment.
Chapter
4 Discussion 7
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
23/25
e.
Specify outputs and formats, and final postprocessing data quality
checks.
Such
a
capabil i ty
would
end
th e
need
fo r
recoding
to
achieve
specific detection
objectives and
would serve a
very flexible research
tool.
This capabil i ty would
have tw o components . The first would be th e configurable logic processing
engine.
The
second
would
be
a
l ibrary
of
configuration
files
that
could
be
used
to
achieve specific processing objectives.
EcoSAV
1.0 would be one
configuration
file
representing
a
good
general-purpose
processor. Specialized conditions,
such
as
dense canopy-forming
SAV,
rocky bottoms,
low-density
SAV,
etc. would
each be represented in a specialized configuration file developed fo r
processing
these conditions.
Biosonics,
Inc.,
is currently developing th e
configurable
logic
processing
engine.
Biosonics
and their associated user communi ty
are
developing
specifications
fo r
th e various
specialized configuration
files.
18 hapter 4 Discussion
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
24/25
REPORT
DO CU ME N TATI O N
PAGE
Form Approved
OM B
No.
0704-0188
reporting
burden for this collection
of information
is estimated to
average
ou r pe r response,
including the t ime for reviewing
instructions,
searching existing
data
sources ,
gathering
an d
maintaining
data
needed,
an d completing
an d
reviewing this collection
of information. en d
comments regarding this
burden
estimate
or
an y
other aspec t of this collection of information,
including
suggestions for
this burden to
Depar tment
of Defense, Washington
Headquar ters Services,
Directorate for Information
Opera t ions
an d
Reports
(0704-0188),
1215 Jefferson
Davis Highway,
Sui te
1204, Arlington,
2202-4302 .
espondents
shou ld
be aware
that
notwithstanding an y other provision
of
law, no person shall be sub ject
to
an y penal ty
for
fail ing to comply with a collection
of
information
if
it does no t
a currently
valid OM B
control
number . LEASE DO NO T RETURN YOUR FORM
TO TH E
ABOVE
ADDRESS .
R E P O R T DA TE
DD-MM-YYYY
September
2002
2.
R E P O R T
T Y PE
Final
report
3. DA TES C O V E R E D
From
-
To
AN D SU BT IT L E
5a .
C O N T R A C T N U M BE R
Advanced
Digital
Processing of
Echo
Sounder
Signals
fo r
Characterization
of
Very Dense
Submersed Aquatic Vegetation
5b .
G R A N T
N U M B E R
5c . P R O G R A M E L E M E N T N U M B E R
A U T H O R ( S )
Bruce
M.
Sabol,
Janusz
Burczynski,
Joel
Hoffman
5d .
P R O J E C T N U M B E R
5e .
T A S K
N U M B E R
5f. W O R K
UNIT
N U M B E R
33118
. P E R F O R M I N G O R G A N I Z A T I O N N AM E ( S) AN D ADDRESS(ES)
reverse.
8.
P E R F O R M I N G
O R G A N I Z A T I O N R E P O R T
N U M B E R
ERDC/EL TR-02-30
S P O N S O R I N G
/
M O N I T O R I N G A G E N C Y N AM E ( S) AN D ADDRESS(ES)
Army Corps of
Engineers
DC
0314-1000
10 .
S P O N S O R / M O N I T O R ' S A C R O N Y M ( S )
11. S P O N S O R / M O N I T O R ' S R E P O R T
N U M BE R( S)
DISTRIBUTION
/
AVAILABILITY
STATEMENT
for
public release; distribution is unlimited.
3 SUPPL M NT RY NOTES
4
STR CT
n algorithm
has
been
developed
an d
previously
described fo r
detecting
and characterizing
submersed
aquatic
vegetation
using
the
signal of
a
vertically oriented, single-beam, single-frequency echo
sounder.
It
ha s
performed well under most conditions fo r
of submersed vegetation
in
shallow
fresh
an d estuarine
waters.
Several
types
of
conditions
have
proven
to
be
These include detection ofextreme low-density
vegetation (
8/18/2019 Advanced Digital Processing of Echo Sounder Signals for Characterization of Very Dense Submersed Aquatic Veget…
25/25
7.
Concluded).
U.S. Army Engineer
Research and
Development
Center
Environmental Laboratory
3909
Halls
Ferry
Road
Vicksburg,
MS
9180-6199;
Biosonics,
Inc.
4027 Leary W ay
Seattle, W A 8107;
Virginia
Institute
of
Marine
Science
P.O.
Box
1346
Gloucester
Point, VA 3062