Locations and Geotagged sea-floor videos collected in May and June 2023 using the SEABOSS 2.0 in Nantucket Sound, Massachusetts, in the vicinity of Horseshoe Shoal, by the U.S. Geological Survey during field activity 2023-001-FA (MP4 video files and polyline shapefile, GCS WGS 84)

STEP 1: COLLECTED DATA.
A marine geophysical and sampling survey (field activity 2023-001-FA) was conducted in Nantucket Sound, Massachusetts, in the vicinity of Horseshoe Shoal in May and June 2023. The ground validation data was collected while the R/V Rafael occupied one of the target sites, and the SEABOSS 2.0 was deployed off the vessel's portside. The SEABOSS was equipped with a modified Van Veen grab sampler, a FLIR Blackfly S BFS-PGE-50S5M-C digital camera with a topside feed, an oblique downward-looking DeepSea Power & Light HD Multi SeaCam video camera with a topside feed, and DeepSea Power & Light LED SeaLites to illuminate the sea floor for video and photograph collection. The elements of this particular SEABOSS were held within a stainless-steel frame that measured ~1 x 1 meter. The frame had a stabilizer fin that oriented the system as it drifted over the seabed. Two red lasers were set 20 centimeters apart (both as they were mounted on the SEABOSS frame and as seen in photographs and video on the seabed) for scale measurements. The red laser dots can usually be seen in the sea-floor photos and videos depending on the bottom type, water clarity, and distance to the sea floor. The winch operator lowered the SEABOSS until the sea floor was observed in the topside live video feed. Generally, the vessel and SEABOSS drifted with wind and current for up to a few minutes to ensure a decent photo with a clear view of the sea floor was acquired. A scientist monitored the real-time bottom video and acquired bottom photographs at points of interest by remotely triggering the FLIR camera shutter. The photographed area is most often within 0.5 to 1.25 meters from left to right. Bottom video was also recorded during the drift from the oblique downward-looking DeepSea Power & Light HD Multi SeaCam video camera directly to a solid-state drive using an Odyssey7 video recorder. Due to equipment overheating issues, the FLIR camera stopped working after site 2023-001-050, so still-image frame grabs were captured from the DeepSea Power & Light bottom videos for the last 10 sites (sites 2023-001-051 through 2023-001-060) described in a subsequent process step.
After drifting for up to a few minutes, the winch operator lowered the SEABOSS sampler until it rested on the sea floor. When the system was raised, the Van Veen grab sampler closed and collected a sample as it was lifted off the sea floor. The sampler was recovered to the deck of the survey vessel where a subsample was taken for grain-size analysis at the sediment laboratory at the USGS Woods Hole Coastal and Marine Science Center.
During the survey, DGPS navigation from a Hemisphere R131 DGPS receiver (see Positional_Accuracy statement above for more info). Dates and times were recorded in UTC. When the FLIR camera shutter was remotely triggered to take a photo, the photo filename and navigation data for that timestamp were saved to a CSV file, which was used to geotag the images in a subsequent process step. The DGPS data were also overlaid onto the video using a Proteus-V Pro video overlay device. A survey log was maintained during the field activity by the technical and scientific staff as an Excel spreadsheet. It contains information about bottom photo and video acquisition, sediment sampling, and other miscellaneous notes from the survey.
A total of 62 videos were collected using the SEABOSS 2.0 at 60 sites during field activity 2023-001-FA.

STEP 2: PROCESSED VIDEO FILES.
A shell script (do_concat.sda) was run on the original video files to concatenate the video clips for each site as needed (the Odyssey7 splits clips into less than 4 GB segments) and convert the video files to MP4 files using FFmpeg.

STEP 3: DETERMINED VIDEO START AND END TIMES FOR THE FIRST SURVEY DAY.
The bottom videos from the first survey day (JD 132; sites 2023-001-001 through 2023-001-006) do not have an overlay of the latitude, longitude, GPS time, and GPS date. The video start and end times, however, are needed to map the bottom video tracklines. To determine the start and end times for the videos from the first survey day, a photo taken during each video drift was matched to a frame in the video. The GPS time of the photo was used along with the video playback time of the matching location to determine the start and end times of each video drift from the first survey day.

STEP 4: TRIMMED VIDEO FILES.
The videos were trimmed to the duration that the camera was within view of the sea floor if more than about 15 seconds of either sampler deployment or retrieval was originally recorded. The videos that needed to be trimmed were identified in the survey log, which included notes if the video clip was extended, and by watching the beginning and end of the videos to see if they included sampler deployment or retrieval. The videos were trimmed using FFmpeg (version 7.0.2).

STEP 5: RENAMED VIDEO FILES.
The videos were renamed using a shell script to include the field activity identifier and site ID, camera, and GPS date and start time in the ISO 8601 standard (YYYYMMDD T [time separator] HHMMSS Z [Zulu/UTC time]) in the filename. For the videos from the two survey days in June (JDs 164 and 165; sites 2023-001-007 through 2023-001-060), the start times were determined using the GPS time overlay from the first frame of each video. The start times for the video drifts from the survey day in May (JD 132; sites 2023-001-001 through 2023-001-006) had already been identified in a previous process step.

STEP 6: CREATED START TIMES/DURATIONS TEXT FILE.
A text file recording the filename, GPS date, start time, and duration in seconds of each video recording was created. The start times for the video drifts from the survey day in May (JD 132; sites 2023-001-001 through 2023-001-006) were already identified in a previous process step. For the videos from the two survey days in June (JDs 164 and 165; sites 2023-001-007 through 2023-001-060), the start times and durations were determined using the GPS time overlay from the first and last frames of each video. To do this, first, a command was run to extract a still-image frame grab of the first and last frames of the videos using FFmpeg (version 7.0.2). Next, a command was run to crop the time from each frame grab. The cropped image of the time was then converted to text using the optical character recognition engine Tesseract (version 5.4.1) and saved as a text file. All the time text files were merged into a single text file, which was then imported and formatted in Microsoft Excel for Mac. The start and end times were used to determine the duration of the videos, and this information for all the videos was saved in a final start times/durations text file.

STEP 7: PROCESSED NAVIGATION.
The DGPS navigation data from the ship's receiver were processed for the survey day in May (JD 132; sites 2023-001-001 through 2023-001-006) since the navigation from the SEABOSS's receiver were not recorded for this day. To do this, the GPRMC navigation strings were extracted from the ship's raw navigation and then formatted in Microsoft Excel for Mac. The latitudes and longitudes were converted from degrees decimal minutes to decimal degrees and rounded to six decimal places. Since the DGPS receiver was set to receive fixes at 4 Hz, or four per second, the first timestamp for each second was extracted and saved to a CSV file. For the two survey days in June (JDs 164 and 165; sites 2023-001-007 through 2023-001-060), the coordinates recorded on the video overlay were used for the navigation data. To obtain the navigation data from the overlay, first, a command was run to extract a still-image frame grab every 1 second from the videos using FFmpeg (version 7.0.2). Next, a command was run to crop the latitude from each frame grab. The cropped image of the latitude was then converted to text using the optical character recognition engine Tesseract (version 5.4.1) and saved as a text file. These commands were repeated to crop the longitude from each frame grab and convert it to text, and then again to crop and convert the time to text. All the latitude, longitude, and time text files were concatenated and merged into a single text file. This text file was then imported and formatted in Microsoft Excel for Mac, creating a processed video overlay navigation CSV file for the survey (videocrop_coords_and_times.csv). The video overlay navigation data were checked to see if any times were missing. Occasionally, frame grabs were not extracted for the first or last second of the video. These missing frame grabs were identified, and the navigation data from the missing frame grabs were obtained and added to the video overlay navigation CSV file. The CSV files of the ship's navigation and video overlay navigation were combined into one file, creating a final navigation file for the survey.

STEP 8: CREATED A CSV FILE OF THE BOTTOM VIDEO TRACKLINE POINTS.
The text file with the start time and duration of each video recording and the final navigation data were prepared for the video trackline script. The fields in the final navigation CSV text file were reordered and formatted to be used with the video trackline script. Then, a Jupyter Notebook Python script (Video_trackline_prep_WORKING_v2.ipynb) was run to create a CSV file of the bottom video trackline points by extracting the navigation data for each video drift using information from the start times/durations text file. The script reads the video start time and duration from the text file, calculates the video end time, extracts the navigation points that fall within those start and end times, and exports the navigation points to a CSV file.

STEP 9: CREATED THE FINAL BOTTOM VIDEO TRACKLINES SHAPEFILE.
A point shapefile was created using the bottom video trackline points CSV files in Esri ArcGIS Pro (version 3.3.1). The Points to Line tool was then run with the video trackline points as the input features and the video filenames as the line field to create a polyline shapefile of the video tracklines. Attributes from the trackline points shapefile were added to the bottom video tracklines shapefile including the start and end times of the video drifts (STARTTIME and ENDTIME, respectively), Julian day of collection (JD), and date of collection (DATE) during the Points to Line processing. The site number (FIELD_NO) of each video trackline was derived from the video file name field carried over from the trackline points shapefile. The trackline length (LENGTH_M) was calculated using the Calculate Geometry Attributes tool (Property=Length; Length Unit=Meters; Coordinate System=WGS 1984 UTM Zone 19N).
In QGIS (version 3.34.7) attribute field cleanup was done to the polyline shapefile, including creating an attribute for the site number of the video trackline (FIELD_NO) and updating the field names for bottom video filename (LINENAME), start time of the bottom video drift in UTC (STARTTIME), end time of the video drift in UTC (ENDTIME), Julian day of collection (JD), date of collection (DATE), year of collection (YEAR), trackline length in meters (LENGTH_M), camera used (CAMERA), field activity identifier (FA_ID), sampling device used to collect the video (DEVICE_ID), and survey vessel (VEHICLE_ID).