Locations and grain-size analysis results of sediment samples collected in Cape Cod Bay, Massachusetts, in September 2019 by the U.S. Geological Survey during field activity 2019-034-FA (point shapefile and CSV file, GCS WGS 84, MLLW vertical datum)

Step 1: Collected data.
A marine geological survey (field activity 2019-034-FA) was conducted in Cape Cod Bay, Massachusetts, in September 2019. The R/V Tioga occupied one of the target sites, and the MiniSEABOSS was deployed off the vessel's A-frame on the stern of the ship. The MiniSEABOSS was equipped with a modified Van Veen grab sampler, a GoPro HERO4 Black digital camera, an oblique downward-looking SeaViewer 6000 HD Sea-Drop video camera with a topside feed, a Paralenz DiveCamera+ recording backup video, and a dive light to illuminate the sea floor for video and photograph collection. The elements of this particular MiniSEABOSS 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 MiniSEABOSS 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 and distance to the sea floor. The winch operator lowered the MiniSEABOSS until the sea floor was observed in the topside live video feed. Generally, the vessel and MiniSEABOSS 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. The GoPro camera was set to take photos every 2 seconds during a MiniSEABOSS deployment. Bottom video was also recorded during the drift from the oblique downward-looking SeaViewer 6000 HD Sea-Drop video camera directly to a solid-state drive using an Odyssey7 video recorder. Then, the winch operator lowered the Van Veen grab 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. Times for the sampler retrieval, which would later be used to derive the sample locations, were manually recorded in the survey log when the sampler was lifted off the seabed. 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. At four sites (sites 2019-034-FA-012, 2019-034-FA-016, 2019-034-FA-025, and 2019-034-FA-045), a sample was attempted but was not successfully collected (these areas usually had a cobble, boulder, or rocky seabed). During the survey, DGPS navigation from a Hemisphere R131 DGPS receiver was logged through a DataBridge data logger and QGIS (version 3.0.0) GPS Tools. The DGPS was set to receive fixes at a 1-second interval in geographic coordinates (WGS 84). Dates and times were recorded in Coordinated Universal Time (UTC). Log files were saved for each Julian day in NMEA text format. The GPS data were also overlaid onto the SeaViewer video using a Proteus-V Pro video overlay device. A total of 49 sites were occupied aboard the R/V Tioga with the MiniSEABOSS during field activity 2019-034-FA, and sediment samples were successfully collected at 45 of the 49 sites. Not all of these samples are included in the final dataset due to the presence of cobble (see the Completeness Report above for more information), so this dataset includes the grain-size analysis results for 42 sites.

Step 2: Assembled sample information for sediment laboratory.
The sediment sample times (as recorded in the survey log) were checked by viewing the bottom videos to see when the sampler was lifted off the sea floor at each site and updated with more precise times as appropriate. The latitude and longitude from the video overlay at the time of the sample were also noted for each sediment sample. Approximate depths for each sample were extracted from a composite bathymetry dataset (these depths were later updated in a subsequent process step using bathymetry data collected during the affiliated geophysical survey, USGS field activity 2019-002-FA). This information was then provided to the sediment laboratory at the USGS Woods Hole Coastal and Marine Science Center with the sample analysis request form for the survey.

Step 3: Analyzed sediment samples using the Beckman Coulter Multisizer 3 and sieving of the >= 4-phi fraction.
The samples were analyzed in the sediment laboratory at the USGS Woods Hole Coastal and Marine Science Center using the Beckman Coulter Multisizer 3 and sieving of the >= 4-phi fraction. A subsample was taken from each sample submitted to the sediment analysis laboratory for the grain-size analysis. The subsamples were assigned unique analysis identifiers (ANALYSIS_ID), and a macro-enabled Microsoft Excel data entry spreadsheet (GrainSizeWorksheet_xxxx.xlsm, where xxxx is the batch number assigned to the sample submission) was created to record the measurement data. About 50 grams of wet sediment were placed in a pre-weighed beaker, weighed, oven dried at 100 degrees Celsius, and reweighed to correct for salt. The dried sample was wet sieved through a 0.062 mm (No. 230) sieve. The coarse fraction remaining in the sieve was oven dried at 100 degrees Celsius (until completely dried) and weighed. The fine fraction in water was collected in a plastic Nalgene bottle and sealed with a screw lid (stored for no longer than one week). The coarse fraction was dry sieved to determine the individual weights of the 4- to -5-phi fractions, and the weights were recorded in the data entry spreadsheet. The fine fraction was run and combined using the 200-micron and 30-micron Coulter analyses using the Multisizer 3 software to get the fine fraction grain-size distribution. The fine fraction distribution data were added to the data entry spreadsheet. The spreadsheet was used to calculate a continuous phi class distribution from the original fractions.

Step 4: Calculated grain-size classification and statistical analyses.
A continuous phi class distribution from the original fractions was transposed to the "results" tab in the macro-enabled Microsoft Excel data entry workbook (GrainSizeWorksheet_xxxx.xlsm, where xxxx is the identifier assigned to the sample submission). Macros in the workbook ("GS_statistics" and "sedimentname") were run to calculate grain-size classification and statistical analyses and finish processing the data. Sample, navigation, and field identifiers along with continuous phi class distribution data, grain-size classification, and statistical analysis results were copied and pasted into a final Microsoft Excel spreadsheet (xxxx_GS-MS_results.xlsx, where xxxx is the batch number assigned to the sample submission). The processed data were quality control checked and assigned a quality grade based on the examination of the analytical data. Processed data were released to the submitter and incorporated into the laboratory's database. All raw analytical data generated by the samples were archived in the sediment analysis laboratory.

Step 5: Processed navigation.
To process the NMEA navigation data, GPSBabel (version 1.7.0) was used to read the GPRMC navigation sentences from the NMEA log files, translate them to waypoints, and write the waypoints to a GPX XML file (nmea_nav_jd260_jd262.gpx). The GPX file was then converted to a shapefile in QGIS (version 3.10.9). New fields for the latitude and longitude were added to the shapefile and calculated to six decimal places. The shapefile was exported as a CSV text file, which was then formatted in Microsoft Excel for Mac (version 16.16), creating a processed NMEA navigation CSV file for the survey (nmea_nav_jd260_jd262.csv).
Due to an issue with the data logger, the raw navigation data were recorded to NMEA files for only 22 of the 50 sampler deployments. For the remaining 28 deployments, the latitude and longitude 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 4.3.1). 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 4.1.1) 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 added to the video overlay navigation CSV file.
Shapefiles of the NMEA and video overlay navigation CSV files were created in ArcGIS (version 10.7.1). The sites with no NMEA navigation were identified, and the video overlay navigation data for those sites were exported as a table. The exported table was added to the NMEA navigation in Microsoft Excel for Mac and saved as a CSV file, creating a final navigation file for the survey (nmea_and_videocrop_nav.csv). This process step and the subsequent process steps were performed by the same person, Emily Huntley.

Step 6: Updated sediment sample locations and depths.
The updated sediment sample times (as adjusted by viewing the bottom videos in a previous process step) were matched to the corresponding times in the final navigation file to update the latitude and longitude of each sample in the sediment grain-size analysis results spreadsheet in Microsoft Excel 2016 for Mac. The Microsoft Excel spreadsheet was saved as a CSV file, and a shapefile was created from the CSV file using the XY Table To Point tool in Esri ArcGIS Pro (version 2.4.1). The updated locations were then used to extract approximate depths for the sediment sample locations from the bathymetry data collected during the affiliated geophysical survey (USGS field activity 2019-002-FA; see "2019-002-FA_T20P_Bathymetry_5m_MLLW.tif" in the larger work citation) using the Extract Values to Points tool in Esri ArcGIS Pro.

Step 7: Created final sediment grain-size analysis results CSV file.
The sediment grain-size analysis results spreadsheet was edited in Microsoft Excel 2016 for Mac to remove some fields, format fields, add site locations for those sites where no sample was successfully collected, and add a no data value (-9999) to empty attributes as needed. The sites with no successful grab were located using the start time of the sampler retrieval from the survey log; the sampler retrieval position was chosen as the sample location because the video clip is considered the sample in the absence of a physical sample. Finally, the Microsoft Excel spreadsheet was saved as a CSV file (2019-034-FA_samples.csv).

Step 8: Created a shapefile of the sediment sample locations containing a subset of the fields from the grain-size analysis results.
The CSV file of the sediment grain-size analysis results was copied and edited to create a simplified version of the CSV file with fewer attribute fields (specifically, STDEV, SKEWNESS, KURTOSIS, and the individual phi measurements [e.g., PHI_13] were removed). A shapefile was created from the simplified version of the CSV file using the XY Table To Point tool in Esri ArcGIS Pro (version 2.4.1), and then the field properties (i.e., precision, scale, and length) in the point shapefile were modified as needed. Please note that since the shapefile contains a subset of the grain-size analysis results, users should access the CSV file for the full sediment grain-size analysis results.