Weber et al: Seabed classification for trawlabiiity determined with a multibeam echo sounder 
71 
examination of the predictions of S b shown in Figure 1, 
3 different metrics that describe S b were used, similar 
to those of Fonseca and Mayer (2007): the normal-inci- 
dence S b , the slope of the angle-dependent backscatter 
within 10°of normal incidence (S 6 -slope), and the aver- 
age oblique-incidence S b (30° <0< 60°). 
The acoustic power associated with each bottom de- 
tection also was converted to acoustic backscatter in- 
tensity and used to derive an estimate of the scintilla- 
tion index, SI, which is defined here as 
2 
S/ = -H, ( 1 ) 
P-i 
2 2 
where O/ and Ui = the variance and mean of the 
backscatter intensity, respectively. 
The SI is a measure of how the backscatter inten- 
sity fluctuates: for Rayleigh-distributed backscatter, 
the SI is equal to 1; for heavier tailed distributions 
that are a potential indicator of a relatively few strong 
scatterers contributing to the backscattered echo, the 
SI would be >1. The SI was calculated independently 
for each beam with a minimum of 50 samples (pings) 
and then averaged across beams. One important caveat 
to such SI estimation is that it is dependent on the 
sonar footprint on the seafloor (Abraham and Lyons, 
2004), which changes as a function of incident angle 
and seafloor depth for MBES. To reduce changes in SI 
that were associated with the sonar footprint rather 
than the substrate type, we used only the beam angles 
between 34° and 50° to generate this parameter. This 
restriction of angles essentially reduced the resolution 
to that of a single multibeam swath. 
The MBES data were compared with image data 
(both video and still images) from an SDC and a ROV. 
The SDC contained identical Sony TRD-900 camcorder 
units (Sony Corp., Tokyo, Japan) capable of collecting 
progressive scan video images at a pixel resolution of 
1280x720. Both SDC camcorder units were mounted 
on a sled in an aluminum frame and lowered to the 
seafloor with a dedicated winch, and illumination was 
provided by 2 lights mounted above the camera hous- 
ings inside the aluminum frame (Williams et ah, 2010). 
MBES data also were compared with data collected 
with a Phantom DS4 ROV (Deep Ocean Engineering, 
Inc., San Jose, CA). Video footage was recorded from 
the ROV with a forward-looking color camera (Sony 
FCB-IX47C module with 470 lines of horizontal resolu- 
tion and 18x optical zoom). Two pairs of parallel lasers 
on the ROV were used to estimate substrate size and 
horizontal field of view. 
Data were collected during 3 cruises conducted at 
Snakehead Bank, south of Kodiak Island in the Gulf of 
Alaska (Fig. 2). During the first cruise, the Oscar Dys- 
on and the FV Epic Explorer, a commercial fishing ves- 
sel, visited the study site on 4-12 October 2009. Data 
were collected aboard the Oscar Dyson with the Simrad 
ME70 and ROV, and data were collected with the stereo 
drop camera aboard the Epic Explorer. Several repeat 
large-scale surveys were conducted with The Oscar Dy- 
son along a series of parallel transect lines spaced 2.2 
km (1.2 nmi) apart and 9.3-14.8 km (5-8 nmi) long. 
Three of these surveys were used for this analysis. In 
addition to the large-scale surveys, 4 small-scale, fo- 
cused surveys were conducted in the same area dur- 
ing the first of the 3 cruises. The focused surveys were 
designed to achieve “full coverage” (i.e., no unsampled 
regions of the seafloor) of the seafloor with the Simrad 
ME70 in areas where a relatively strong indication of 
fish had been observed in the acoustic data. For the 
small-scale surveys, transects were 1.9-3. 7 km (1-2 
nmi) long and spaced 0.2-0. 4 km (0. 1-0.2 nmi) apart 
(depending on the water depth). 
The drop camera was deployed 9 times during the 
October 2009 cruise, and locations were chosen where 
the acoustic data indicated that rockfishes were most 
abundant. During each of the drop-camera deploy- 
ments, the camera sled moved over the bottom at 
speeds of <1.5 kn as the Epic Explorer drifted along 
transects that lasted up to 1 h and, as a result, col- 
lected relatively dense data in 9 small regions. The 
horizontal field of view of the drop camera averaged 
2.43 m (standard error of the mean [SE] =0 . 14). 
The ROV was deployed in 5 different areas where 
the acoustic data indicated that rockfishes were most 
abundant. Each deployment lasted for a few hours. The 
horizontal field of view for the ROV averaged 2.61 m 
(SE=0.20). 
During the other 2 cruises in March and June of 
2010, the study site was revisited and the SDC de- 
ployed 51 times aboard the Oscar Dyson. During these 
additional deployments, the seafloor was recorded in 
only 1 of the 2 available stereo cameras, preventing 
collection of stereographic images. Each of these de- 
ployments was short: the drop camera was deployed 
to the bottom for a couple of minutes before it was re- 
trieved to the surface. The resulting images were all 
from single, small patches ( <25 m radius) of seafloor, 
rather than from the drift transects described for the 
first cruise. 
The seafloor substrate observed during the under- 
water video transects was classified with a commonly 
used scheme (Stein et ah, 1992; Yoklavich et ah, 2000). 
The classification consisted of 2-letter codes for sub- 
strate types that denoted a primary substrate with 
>50% coverage of the seafloor bottom and a second- 
ary substrate with 20-49% coverage of the seafloor. 
There were 7 identified substrate types: mud (M), sand 
(S), pebble (P, diameter <6.5 cm), cobble (C, diameter 
6.5-25.5 cm), boulder (B, diameter >25.5 cm), exposed 
low-relief bedrock (R), and exposed high-relief bedrock 
and rock ridges (K). The size of substrate particles was 
measured or estimated from a known horizontal field 
of view (~2.4 m) for the SDC and estimated with a 
paired laser system for the ROV. With this classifica- 
tion scheme, a section of seafloor covered primarily in 
cobble but with boulders over more than 20% of the 
surface would receive the substrate-type code cobble- 
