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of 720x480 pixels. Each of the cameras was calibrated 
to correct for intrinsic optical parameters. Lengths of 
individual targets in the two cameras were calculated 
by identifying the position of individual points (such as 
a fish’s head and tail) in each of the paired images and 
calculating their relative position using triangulation. 
The lens of each camera was keyed to its port so that 
the camera fit in only one position in the housing. This 
ensured consistent relative positioning of the cameras 
among deployments. Illumination was provided by two 
50-watt, high-intensity discharge lights mounted above 
the camera housings inside an aluminum frame. The 
lighting system was powered by 4 rechargeable 4 Ah 12 
V nickel-metal hydride batteries. 
For calibration, the SDC was suspended in the water 
while the research vessel was dockside. The cameras 
were calibrated underwater by using images of a tar- 
get plate with a printed 10x10 square checkerboard 
pattern of 50x50-mm squares (Williams et ah, 2010). 
The approximate depth of the camera was 1 m and the 
approximate distance from the target was 1-2 m. The 
checkerboard target was lowered into the water along 
the vessel until it was plainly visible in both cameras. 
The target was then slowly moved horizontally and 
vertically through the field of view of both cameras and 
up to 15 minutes of calibration video were collected. 
Progressive scan video images were collected at 29.97 
frames/s in each camera, and the videos from each cam- 
era were aligned by using a light-emitting diode (LED) 
synchronization light flashed in front of both cameras at 
the beginning of deployment. This LED synchronization 
was repeated at the end of the deployment to confirm 
that the video frames from the paired cameras were 
still aligned. 
For the calibration procedure, still frame images were 
extracted from the aligned videos at 1-s intervals with 
Adobe Premiere software (Adobe Systems, Inc., San 
Jose, CA). Twenty paired images in which the target 
checkerboard was visible in both cameras were ran- 
domly selected for the calibration of the camera system. 
The calibration parameters were estimated with the 
camera calibration toolbox in Matlab (Mathworks, Inc., 
Natick, MA; Bouguet, 2008). For each image pair, the 
position of the corner points of the checkerboard pattern 
were identified by clicking on the images. The location 
of these points in the still images was computed by the 
calibration software to determine the focal parameters 
of each camera. Intrinsic camera parameters were used 
to correct the individual images for optical distortion 
resulting from the camera lenses. 
The SDC was deployed and retrieved by an electric 
winch with 4-conductor electromechanical armored ca- 
ble. The camera system was suspended 1-2 m off the 
seafloor at an angle of approximately 30° from horizon- 
tal to the seafloor. This position allowed a viewing path 
width of 2.43 m (SE = 0.14) and under normal lighting 
conditions the field of view extended ~3 m in front of 
the SDC, although this varied with the distance of the 
SDC off the seafloor and the volume of light scatter- 
ing particles in the water. The SDC traveled over the 
seafloor at a target speed of 1.9-3. 7 km/h (1-2 knots) 
for transects lasting up to about 1 hour. The overall 
mean speed of the SDC during field deployments was 
2.26 km/h (SE = 0.15). Some steerage of the camera was 
possible by towing the system gently with the vessel, 
and during slack water or low current periods the unit 
was sometimes towed to maintain a constant low speed. 
However, the direction of drifting and towing was with 
the prevailing current, and therefore directed transects 
were generally not possible. The area swept by the SDC 
was calculated as the path width multiplied by the dis- 
tance traveled during a transect. 
Classification of trawlable and untrawlable substrates 
The substrata observed in the underwater video tran- 
sects were classified by using the seafloor substrate clas- 
sification scheme of Stein et al. (1992) and Yoklavich et 
al. (2000). It consists of a two-letter coding of substrate 
type denoting a primary substrate (>50% coverage of 
the seafloor bottom) and a possible secondary substrate 
(20-49% coverage of the seafloor bottom). In this clas- 
sification scheme, there are seven substrate types: mud 
(M), sand (S), pebble (P, diameter <6.5 cm), cobble (C, 
6.5< diameter<25.5 cm), boulder (B, diameter >25.5 cm), 
exposed low-relief bedrock (R), and exposed high-relief 
bedrock and rock ridges (K). For example, a section of 
seafloor covered primarily in sand, but with boulders 
over more than 20% of the surface, would receive the 
substrate code sand-boulder (Sb), where the secondary 
substrate is indicated by the lower-case letter. Because 
the SDC and ROV provided a continuous display of sub- 
strata, the substrate code was only changed if a substrate 
encompassed more than 10 consecutive seconds of video. 
For the purposes of this study, we further classified 
substrata as either untrawlable or trawlable with ref- 
erence to the standard Poly-Nor’Eastern 4-seam bot- 
tom trawl used by the AFSC in biennial bottom trawl 
surveys of the Gulf of Alaska and Aleutian Islands 
(Stauffer, 2004). To define trawlability we used video 
captured from the ROV and SDC. The untrawlable ar- 
eas were defined as any substrate containing boulders 
extending higher than ~20 cm off bottom or with ex- 
posed jagged bedrock that was rugose enough that the 
standard bottom trawl footrope would not pass easily 
over it. The heights of individual boulders and rocks 
were estimated by using the relative positions of the 
lasers from the ROV and measured with the SDC. The 
trawlable grounds, in contrast, were mostly composed 
of small cobble, pebble, sand, and mud without inter- 
spersed boulders or rocks. A single experienced observer 
conducted the substrate classification for both the ROV 
and SDC video transects. 
Identification and measurements of fish 
All rockfish caught with the bottom trawl were identi- 
fied to species. Fish were identified and counted by 
species where possible for the optical methods (ROV 
and SDC). Fish were counted up to a maximum of 4 m 
