Video transects of the sea floor on Stellwagen Bank on U.S. Geological Survey field activity 2015-062-FA, aboard the R/V Auk, Oct. 21 and 22 and Nov. 3 and 4 2015 (geographic, WGS84, 2015-062-FA_driftlines.shp polyline)

Video methods and data availability:
Seabed video images were collected using a battery-operated, high-definition (1920 x 1080 pixels) GoPro digital video camera mounted on the USGS SEABed Observation and Sampling System (SEABOSS). The SEABOSS system actually had two GoPro cameras attached to it - with the second camera mounted a little higher on the frame which only shows a partial view of the seabed. This second camera was used only to observe obstacles, like gill nets and lobster gear, in order to avoid entanglement. Or, in the case of station 4382, provide a backup system if the primary camera failed.
As the SEABOSS drifted over the seabed, the forward-looking camera imaged the seabed at a rate of 60 frames per second from an altitude of ~1 meter. Lighting was provided by two, battery-operated Keldan LED video lights. Each light provided a light flux of up to 9000 lumens at a correlated color temperature of 5000 kelvins. Two parallel red lasers mounted 20 centimeters apart provided a scale in the video images.
Video imagery includes the launch and recovery of the SEABOSS, transit through the water column, and the drift over the seabed. The duration of individual video files ranges from 4 to 12 minutes. Video files are archived in .MP4 format and range in size from 0.9 to 2.6 gigabytes. These video files are not available as part of this data release.
Video files are archived at the USGS Woods Hole Coastal and Marine Science Center, 384 Woods Hole Road, Woods Hole, MA 02543.
The position (lat/lon) of the start of the video drift was recorded (from the navigation receiver) in the log book at the time of the deployment of the SEABOSS. Video was recorded during the descent through the water column (1-2 minutes), during the drift over the seabed, and during the ascent to the surface. The position (lat/lon) of the end of the video drift was recorded at the beginning of the ascent through the water column. The corresponding times are also recorded.

The original raw $GPGGA navigation (available from the Larger Work citation) was run through an awk script (on a machine running CYGWIN) in order to reformat the latitudes and longitudes into decimal degrees and output the data into a comma-delimited text file with the following columns of information: latitude (decimal degrees), longitude (decimal degrees), hour, minute, second, julian day, year. The julian day was determined by the original start date in the filename of the navigation file as the GPGGA string does not contain any date information. The awk script also made sure that there were not duplicate records in terms of time - such as two navigation points recorded at 16:38:23. However, the script does not check for duplicate coordinate fixes. The individual navigation files were concatenated into a single file - in order of acquisition. This process step and the remaining process steps were performed by the same person - VeeAnn A. Cross.

Another awk script was run on the stations summary csv file to extract the following columns of information: station, julian day of video start, UTC time of video start, julian day of video end, UTC time of video end, year

A python script (driftlog_gui_v5.py) run from python IDLE version 2.7.8 was used to extract all the navigation points from the navigation file based on the start and end time recorded in the log book of the video drift. This was necessary because no time was recorded on the GoPro video, just the time the video file was created. Ideally, there is a match of the same time (with a corresponding navigation fix) in the GPS file to the start video time recorded in the log book. Same thing with the ending time. However, if this situation does not exist, then the closest (in time) navigation record to the start and end time of the video transect is used - along with all the navigation points in between those two times.
The python script also combines the extracted points for each video drift line and combines these points into a polyline within a shapefile. The resulting shapefile has a polyline for every video drift comprised of all the navigation points available corresponding to the start and end time of each drift line. Based on the navigation system, the projection of the dataset was set to geographic, WGS 84.

Added keywords section with USGS persistent identifier as theme keyword.