NOAA Technical Memorandum NMFS-AFSC-219

U.S. DEPARTMENT OF COMMERCE

National Oceanic and Atmospheric Administration

National Marine Fisheries Service

Alaska Fisheries Science Center

March 2011

by

D. T. Jones, A. De Robertis, and N. J. Williamson

Statistical Combination of Multifrequency

Sounder-detected Bottom Lines Reduces

Bottom Integrations
NOAA Technical Memorandum NMFS

The National Marine Fisheries Service's Alaska Fisheries Science Center

uses the NOAA Technical Memorandum series to issue informal scientific and

technical publications when complete formal review and editorial processing

are not appropriate or feasible. Documents within this series reflect sound

professional work and may be referenced in the formal scientific and technical

literature.

The NMFS-AFSC Technical Memorandum series of the Alaska Fisheries

Science Center continues the NMFS-F/NWC series established in 1970 by the

Northwest Fisheries Center. The NMFS-NWFSC series is currently used by

the Northwest Fisheries Science Center.

This document should be cited as follows:

Jones, D. T., A. De Robertis, and N. J. Williamson. 2011. Statistical

combination of multifrequency sounder-detected bottom lines reduces

bottom integrations. U.S. Dep. Commer., NOAA Tech. Memo. NMFSAFSC-219, 13 p.

Reference in this document to trade names does not imply endorsement by

the National Marine Fisheries Service, NOAA.
March 2011

NOAA Technical Memorandum NMFS-AFSC-219

by

D. T. Jones, A. De Robertis, and N. J. Williamson

Statistical Combination of Multifrequency

Sounder-detected Bottom Lines Reduces

Bottom Integrations

Alaska Fisheries Science Center

7600 Sand Point Way N.E.

Seattle, WA 98115

www.afsc.noaa.gov

U.S. DEPARTMENT OF COMMERCE

Gary F. Locke, Secretary

National Oceanic and Atmospheric Administration

 Jane Lubchenco, Under Secretary and Administrator

National Marine Fisheries Service

Eric C. Schwaab, Assistant Administrator for Fisheries
This document is available to the public through: 

National Technical Information Service 

U.S. Department of Commerce 

5285 Port Royal Road 

Springfield, VA 22161 

www.ntis.gov 
 iii

ABSTRACT 

Accurate quantification of biological abundance using acoustics requires complete 

removal of the sea floor’s contribution from the echo. Acoustic-trawl surveys often utilize a 

single sounder-detected bottom (SDB) line for bottom determination, but combining bottom 

detections from multiple frequencies could provide a more accurate representation. Using 

bottom detection lines from five different frequencies, 222 nautical miles of trackline from four 

distinct acoustic-trawl survey areas were investigated to determine if the mean or median 

statistical combination of multiple frequency SDB lines resulted in fewer bottom integrations 

compared to a single frequency SDB. The difference in bottom detection depth between the 

statistical combination lines and the 38 kHz SDB was also investigated. The mean statistical 

combination line reduced bottom integrations by an average of 45% and the median produced a 

43% reduction in integrations over all areas. Additionally, bottom depth averaged 5.9 and 6.9 cm

shallower for the mean and median, respectively, compared to the 38 kHz SDB. Overall the 

mean tended to be marginally better at reducing the bad bottom integrations while at the same 

time slightly less divergent from the 38 kHz SDB compared to the median. Based on these 

results, beginning in 2009, the Alaska Fisheries Science Center’s Midwater Assessment and 

Conservation Engineering Program began using the mean statistical combination line to 

represent the true bottom, replacing the 38 kHz SDB line historically used. 

 v

CONTENTS 

Page 

Abstract .......................................................................................................................................... iii 

Introduction ..................................................................................................................................... 1 

Methods........................................................................................................................................... 4 

Results and Discussion ................................................................................................................... 7 

Citations .......................................................................................................................................... 9 

INTRODUCTION 

 Underwater acoustics have been employed since the mid-20th century for determining 

bottom depth and estimating the density of fish aggregations. Acoustic-trawl surveys are used to 

estimate abundance of economically important fish stocks worldwide (Misund 1997). To 

accurately quantify the abundance of fish in the water column, it is crucial to completely remove 

the contribution of the echo returned from the bottom. If the bottom echo is not properly 

excluded, the estimated fish density can be grossly inaccurate (Simmonds and MacLennan 

2005).

 Many fisheries applications utilize a 38 kHz split-beam transducer as a primary source of 

acoustic data and depth determination (Aglen 1996, Misund 1997). Bottom-detection depends 

on echo-amplitude measurements and user-defined thresholds for defining bottom discrimination 

levels (Bourguignon et al. 2009, Ona and Mitson 1996). A vertical offset or backstep from the 

threshold amplitude is also commonly employed to ensure that the bottom is sufficiently 

excluded. 

 Even with an appropriate threshold and backstep, several circumstances can result in 

unsatisfactory bottom detection. Adverse weather conditions can cause missed or dropped pings 

and may also result in the bottom appearing rougher or more variable. Additionally, a dense 

school of fish in close proximity to the bottom may be integrated with the bottom, or a soft, 

poorly reflecting bottom may be misinterpreted as being deeper (Bourguignon et al. 2009, 

MacLennan et al. 2004). In these instances it may be helpful to consult bottom detections from 

additional frequencies to obtain a more accurate determination of the bottom. Using a 
 2

combination of frequencies would also reduce the random variability of a single sounder in areas 

of relatively flat seabed. 

The rationale underlying multifrequency bottom detection is simple: by averaging 

simultaneous estimates of the bottom depth made from a cluster of co-located transducers at 

multiple frequencies, one can arrive at a more precise estimate of the seafloor depth at a 

particular location. If some portion of the error in estimating the range to the seafloor is 

uncorrelated across frequencies, using multiple frequencies will produce a less variable estimate 

of the bottom depth by averaging out stochastic errors. Multifrequency bottom detection will 

therefore result in fewer cases in which the bottom depth is misidentified. This is likely to be the 

case with bottom detections in areas of relatively flat bottom, where a single sounder-detected 

bottom (SDB) line fails to eliminate backscatter from the seafloor, events that are typically 

uncorrelated across frequencies. In contrast, steep or variable bottom terrain can result in 

occasional loss of bottom detection or a shadowing effect that could be misinterpreted as fish. 

Inaccurate bottom detections such as these are caused by interactions of the side lobes of the 

acoustic beam with the seafloor due to the angle of incidence being too large (Bourguignon et al. 

2009). Unfortunately, side-lobe induced errors in areas of high relief are correlated across 

frequency, and multifrequency combinations of bottom detections are unlikely to eliminate the 

problem entirely. 

A combined bottom detection line could approximate bottom depth more accurately and 

potentially reduce the amount of time spent on the post-processing step of manually checking 

bottom integration errors. In addition to reducing bottom integrations, a combined 

multifrequency bottom detection line could help reduce false bottom detections within dense fish 

schools where different frequencies detect the bottom at different depths. Both of these errors 
 3

can significantly impact biomass estimation. Furthermore, a more robust multiple frequency 

bottom detection method would facilitate efforts to use multifrequency combinations for species 

identification, where the need to accomplish bottom exclusion at multiple frequencies 

simultaneously is required (De Robertis et al. 2010). 

Scientists from the Alaska Fisheries Science Center’s (AFSC) Midwater Assessment and 

Conservation Engineering (MACE) Program routinely conduct acoustic-trawl stock assessment 

surveys in the Gulf of Alaska (GOA) and Eastern Bering Sea (EBS). Historically MACE has 

used the 38 kHz SDB line produced by the 38 kHz EK60 echosounder using a -36 dB threshold 

to establish the range to the seafloor. In post-processing, a bottom determination line (defined as 

the SBD with a 0.5 m backstep) is used to remove the contributions of backscatter from the 

seafloor. The exact algorithm for the EK60 SDB, though proprietary, is known to be amplitudebased over multiple pings. With a desire for greater precision and accuracy of data collection 

and less user manipulation through manual correction of the SDB line, MACE scientists worked 

with Myriax, a vendor of echosounder post-processing software, to implement an algorithm for 

use in their Echoview (Myriax Software Pty, Ltd., Hobart, Australia) post-processing software 

that would combine SDB lines from multiple frequencies and output either the mean or median 

as a single statistical combination bottom detection line (see Methods). Similar ideas have also 

been incorporated into alternate hydroacoustic software packages (Korneliussen et al. 2006) used 

by other groups performing acoustic-trawl surveys. 

During EBS surveys, MACE traditionally estimates biomass to within 3 m of the 

seafloor, and in the Gulf of Alaska surveys that is extended to within 0.5 m of the seafloor. If the 

bottom detection depth is altered significantly using a new combination line, the data time series 

could be biased due to inclusion or exclusion of fish within the bottom few meters. Therefore 
 4

before implementing a new bottom detection methodology, the potential for biasing the survey 

time series needed to be considered. 

This document describes the use and functionality of combining sounder-detected 

bottoms from multiple frequencies to generate a more robust estimate of seafloor depth than is 

possible with a single frequency. Specifically, we test if the mean and median sounder-detected 

bottom lines across multiple frequencies result in fewer bottom integrations. The occurrence of 

bottom integrations with the statistical combination lines was compared with that of the 38 kHz 

SDB. The difference in the bottom detection depth is also investigated between the statistical 

combination lines and the 38 kHz SDB. A recommendation is made for the statistical 

combination line that performs best under survey conditions, and it is demonstrated that adopting 

this new method will not bias survey estimates of fish abundance. 

METHODS 

 All survey data were collected aboard the NOAA ship Oscar Dyson, a 64-m stern trawler 

equipped for fisheries and oceanographic research. Acoustic measurements were collected with 

a calibrated Simrad EK60 scientific echo sounding system (Simrad 2004) with five split-beam 

transducers (18, 38, 70, 120, and 200 kHz) clustered close together on the bottom of the vessel’s 

retractable centerboard. Acoustic measurements were analyzed using Myriax Echoview postprocessing software version 4.70. Each frequency transmitted simultaneously at one ping per 

second, with a 1.024 ms pulse length. Nominal half-power beam widths were 11° for the 18 kHz 

transducer, and 7° for the 38, 70, 120, and 200 kHz transducers. For each frequency, the echo 

sounder’s amplitude-based bottom detection as implemented in the echosounder software (ER60 
 5

version 2.1.2) was used with a backstep minimum level set to -36 dB. For each ping, and for 

each frequency, an independent estimate of the range to the seabed was obtained. 

 To ensure performance over a range of bottom types and depths, the statistical 

combination algorithm was evaluated using data from 2007 and 2008 that was representative of 

all survey areas currently monitored by MACE (Fig. 1). Within each region, from 30 to 94 

nautical miles (nmi) of survey trackline data were analyzed ranging in depth from 62 to 479 m 

(Table 1). Tracklines to be analyzed were chosen from periods when wind speeds exceeded 20 

knots to have the greatest possibility of erroneous or bad bottom integrations. 

 Several operators are available within the Echoview software for manipulating lines; the 

current evaluation will focus on the statistical combination and crop options. For higher 

frequencies at greater range, noise becomes limiting, causing erroneous depth estimations, which 

if not removed, would be incorporated into the statistical combination operator. We therefore 

used the crop operator to remove the SDB lines below 500 m for the 120 kHz and 250 m for the 

200 kHz frequencies to reduce erroneous depth entries.

The statistical combination operator includes several options for customizing the lines 

created (Fig. 2). One allows the designation of lines for input into the statistical combination. A 

minimum of two and a maximum of six SDB or other editable lines are available for input. 

Another option allows the user to choose which statistic to work with for the combination: mean, 

median, minimum, or maximum depth. The mean calculates the average bottom detection at 

each ping from the chosen frequencies. The median chooses the bottom detection line that is in 

the ordered middle when there are an odd number of lines being evaluated, or computes the 

average of the two ordered middle lines if the number of lines is even. The minimum and 

maximum statistics choose the line respective to the name designation at each ping. Also in this 
 6

operator is an optional function to systematically exclude any lines that exceed a stated 

divergence limit from the mean. In other words, if an individual sounder-detected bottom line 

does not fall within the range defined by the divergence limit from the mean, it is excluded, the 

mean is recalculated, and the remaining lines are re-evaluated against the new mean. Another 

option allows the user to name the new statistical combination line. The name will display on 

the Echoview window when the cursor is positioned on the line. Finally there is a notes 

documentation window to allow the user to input miscellaneous meta-data. 

 For this study individual pings were scrutinized from the 38 kHz echogram and tallied 

when the bottom was integrated. To quantify bottom integration, an analysis region was created 

from 0.5 m to 1.0 m above the SDB. The mean Sv within this region was displayed as a color 

code, and a visual scan of individual pings was performed. The total number of bottom 

integrations was compared among the 38 kHz SDB, mean, and median statistical combination 

lines. All echograms were scrutinized by the same individual to eliminate any selection bias of 

questionable integrations. Areas of steep relief were not included in counts of bottom integration 

as bottom detection in these areas was poor at all frequencies and did not improve with SDB 

combination. 

 Additionally, the bottom depth detected for each ping was exported and compared among 

candidate lines. If a ping was dropped at any frequency, that ping was removed from bottom 

depth analysis for all frequencies. The difference between the 38 kHz SDB depth and the mean 

and median bottom depths were computed for each ping and an overall average and standard 

deviation of the differences were calculated for each area. Differences between the bottom 

depths detected by the 38 kHz SDB and the statistical combination lines and other frequencies 

were also plotted to examine their distributions. 
 7

RESULTS AND DISCUSSION 

 Results were dependent on the area investigated, but the overall count of bottom 

integrations was lower for both the mean and median statistical combination lines compared to 

the 38 kHz SDB line (Table 2). Results for the mean and median statistical combination lines 

were similar within area but tended to be slightly better for the mean in most cases. Error 

reduction ranged from 3% to 92% with an average of 45% for the mean, and 3% to 87% with an 

average of 42% for the median. The difference in detected bottom depth was consistent between 

the mean and median statistical combination lines compared to the 38 kHz SDB, but the median 

depth was approximately 1 cm shallower than the mean (Table 2). Overall the mean tends to be 

better at reducing bad bottom integrations while at the same time being slightly less divergent 

from the 38 kHz SDB, which has historically been used for the detected bottom depth for MACE 

acoustic-trawl surveys. 

 A total of 222 nmi of trackline were investigated from six distinct survey areas (Table 1). 

Wind speeds ranged from 20 to 40 knots and bottom depth ranged from 62 to 479 m. Wind 

speed, which results in rough sea conditions and increased vessel movement, and water depth 

appear to influence the number of bottom integrations and the depth difference between the 

38 kHz SDB and statistical combination lines differently. The largest difference (20 cm) 

between the bottom depths detected by the 38 kHz SDB and the statistical combination lines was 

in the Bogoslof area where the mean water depth was also greatest (479 m)(Table 2). However, 

in an area with similar wind speed but shallower depth (Renshaw Point) the difference between 

the 38 kHz and statistical combination depths was only 1 cm, but the percent reduction in bottom 

integrations was the highest (92%). 
 8

One reason for the increased difference between lines at greater depth is that there are 

fewer SDB to incorporate into the combination. At depths greater than 500 m, the 120 kHz 

beam is significantly attenuated, and the same is true at depths of greater than 250 m for the 

200 kHz beam. Also, the beams intercepting the seafloor are much larger at depth, and one 

would expect more variance with increased depth. Furthermore, with the divergence limit set at 

1 m, measurements greater than 1 m from the mean were removed and the mean was 

recalculated, resulting in fewer SDB to incorporate. In several instances the 38 kHz bottom 

detection was outside the divergence limit so that the mean and median were calculated from the 

18 kHz and 70 kHz SDB, increasing the difference of the mean and median from the 38 kHz 

SDB. 

 The depth difference between the 38 kHz SDB and statistical combination lines revealed 

no significant positive or negative bias and data were normally distributed around the mean. 

Even in the Bogoslof survey area, this difference was only 0.2 m which equates to less than the 

resolution of one integration cell. Therefore, no bias would be introduced into a survey time 

series due to differential inclusion/exclusion of near-bottom fish, which is a concern for longterm time series used for fisheries management. 

 Even though bottom integrations were reduced when using the mean and median 

statistical combination lines and the time spent performing post-processing integration checks 

can be substantially reduced, the need for scrutinizing the bottom detection line is still 

imperative. This is especially true in areas where the errors in bottom detections are correlated 

across frequencies, for example in areas where a steep slope makes bottom detection difficult. 

Based on our results, beginning in 2009 the MACE Program began using the mean statistical 

combination line to represent the true bottom in place of the 38 kHz SDB line used historically. 
 9

CITATIONS 

Aglen, A. 1996. Impact of fish distribution and species composition on the relationship between 

acoustic and swept-area estimates of fish density. ICES J. Mar. Sci. 53: 501–505. 

Bourguignon, S., L. Berger, C. Scalabrin, R. Fablet, and V. Mazauric. 2009. Methodological 

developments for improved bottom detection with the ME70 multibeam echosounder. 

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empirical multifrequency method for backscatter classification. Can. J. Fish. Aquat. Sci. 

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Misund, O. A. 1997. Underwater acoustics in marine fisheries and fisheries research. Rev. Fish 

Biol. Fish. 7: 1–34. 

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 deadzone revisited. ICES J. Mar. Sci. 53: 677–690. 

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Simrad. 2004. Simrad ER60 scientific echo sounder manual. Base Version Rev. B. Simrad 

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Figure 1. -- The five survey areas from which bottom detection algorithms were tested. 

Eastern 

Bering Sea 

Bogoslof 

Sanak 

Shelikof 

Shumagins 
 12

Figure 2. -- Flow diagram of statistical combination selections within the “New Virtual 

 Line” operation in Echoview V.4.70.

Line Properties - 

Statistical Combination 

1 

Operands:

Choose from 2 to 6 lines 

from which to create a 

statistical combination

Statistical Combination Notes: 

Documentation 

pertaining to 

combination lines 

Statistic: 

Mean Depth 

Median Depth 

Minimum Depth 

Maximum Depth 

Limit allowable 

divergence from mean 

(see text for 

explanation) 
 13

Table 1. -- Trackline distance, approximate wind speed, and mean water depth for each survey 

area used in the evaluation of the statistical combination of sounder detected bottom 

lines. 

Table 2. -- Results of bottom integration counts of 38 kHz sounder detected bottom line, and 

mean and median statistical combination lines. Delta mean or median is the 

difference in depth determined by the statistical combination line and the 38 kHz 

SDB line. Negative values indicate shallower depth determination using the mean 

and median compared to the 38 kHz SDB. 

Area 

Distance 

(nautical miles) 

Wind speed 

(knots) 

Mean water 

depth 

Shumagin trough 15.2 35 161 

Renshaw Point 15.7 20 175 

Sanak trough 14.6 40 113 

Bogoslof T48 and transit 18.5 30-40 135 

Bogoslof T25 11.0 20 479 

Shelikof Strait 53.0 30-40 218 

Eastern Bering Sea 94.0 20-35 62 

Bottom integration counts 

(% reduction from 38 SBD) 

Depth difference 

delta = stat - 38 kHz SDB 

Area 

38 

SDB 

Mean 

(Statistical 

combination)

Median 

(Statistical 

combination) Mean +/- s.d. Median +/- s.d. 

Shumagin trough 66 61 (7.6) 64 (3.0) -3.2 +/- 18 cm -4.1 +/- 19 cm 

Renshaw Point 37 3 (91.9) 5 (86.5) -0.3 +/- 23 cm -1.2 +/- 24 cm 

Sanak trough 48 16 (66.7) 16 (66.7) -4.6 +/- 13 cm -5.3 +/- 13 cm 

Shelikof T22 6 4 (33.3) 4 (33.3) -2.6 +/- 5 cm -2.9 +/- 6 cm 

Shelikof T23 40 8 (80.0) 12 (70.0) -3.2 +/- 8 cm -3.9 +/- 8 cm 

EBS T4-1 40 25 (40.0) 27 (30.0) -6.8 +/- 7 cm -8.4 +/- 8 cm 

EBS T4 33 32 (3.0) 27 (18.1) -6.8 +/- 6 cm -8.4 +/- 7 cm 

Bogoslof T25 45 23 (48.9) 30 (33.3) -19.7 +/- 140 cm -20.6 +/- 140 cm

Bogoslof T48 and 

transit 73 48 (34.2) 45 (38.4) -6.5 +/- 46 cm -7.7 +/- 47 cm 

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