Location and grain-size analysis results of sediment samples collected in Nantucket Sound, Massachusetts, in May 2016 and May 2017 by the U.S. Geological Survey during field activities 2016-005-FA and 2017-022-FA (simplified point shapefile and CSV file)

Step 1: Collected data.
Two marine geological surveys were conducted in Nantucket Sound, Massachusetts, in May 2016 and May 2017. The survey vessel occupied one of the target sites and the MiniSEABOSS was deployed off the vessel's starboard side in 2016 and off the vessel's stern in 2017. The MiniSEABOSS was equipped with a modified Van Veen grab sampler, two GoPro HERO4 Black digital cameras, an oblique downward-looking SeaViewer 6000 HD Sea-Drop video camera with a topside feed, and a dive light to illuminate the sea floor for video and photograph collection. The elements of this particular MiniSEABOSS system 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. The winch operator lowered the sampler until the sea floor was observed in the topside live video feed. Generally, the vessel and sampler 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. Bottom video was also recorded during the drift. Then, the winch operator lowered the Van Veen sampler until it rested on the sea floor. When the system was raised, the Van Veen 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. A total of 76 sites were occupied with the MiniSEABOSS: 55 sites were occupied aboard the R/V Rafael in May 2016 during field activity 2016-005-FA, and 21 sites were occupied aboard the R/V Tioga in May 2017 during field activity 2017-022-FA. Sediment samples were collected at all 76 sites.

Step 2: Acquired and processed navigation.
During field activity 2016-005-FA, DGPS navigation from a Hemisphere DGPS receiver was logged through HYPACK navigation software and a DataBridge data logger. The DGPS was set to receive fixes at a 2-second interval in geographic coordinates (WGS 84). Dates and times were recorded in Coordinated Universal Time (UTC). Log files for each MiniSEABOSS deployment were saved in text format and then combined for each Julian day. An AWK script (awkseth.gprmc.16005.awk) was used to parse the GPRMC navigation string from the log files and create ASCII Comma Separated Values (CSV) text files. The output files were merged and then reformatted using an AWK script (nav_time_reformat.awk), creating a processed navigation CSV text file for the survey (2016-005-FA_OdysseyAudioStamp_nav_ALL.csv). For field activity 2017-022-FA, a GPS log file in text format for the R/V Tioga was provided by the Woods Hole Oceanographic Institution. The navigation was collected at a 1-second interval in geographic coordinates (WGS 84), and dates and times were recorded in UTC. An AWK script (awksethTioga.gprmc.17022.awk) was used to parse the GPRMC navigation string from the log file, creating a processed navigation CSV text file for the survey (2017022FA_TiogaShip_nav.csv).

Step 3: Assembled sample information for sediment laboratory.
The sediment sample times (as recorded in the survey logs) were used to parse GPS positions for each sediment sample from the logged GPS data. Approximate depths for each sample, which had been acquired using the ship's fathometer, were extracted from the HYPACK target file for the 2016 samples and the captain's log for 2017. 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 each survey.

Step 4: Analyzed sediment samples.
The samples from each survey 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. The samples 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 for each survey 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. For the 2016 samples, shell and shell fragments were manually removed from the -1-phi and coarser fractions and weighed, and their weights were recorded in the data entry spreadsheet (this was not done for the 2017 samples). 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 for each survey. The fine fraction distribution data were added to the data entry spreadsheet for each survey. The spreadsheet for each survey was used to calculate a continuous phi class distribution from the original fractions.

Step 5: 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) for each survey. 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) for each survey. 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 6: Interpolated to create 1-second navigation.
The navigation fixes were interpolated to create 1-second navigation. This was done because the application used to geotag the bottom photos would have interpolated between fixes; therefore, the navigation was interpolated so that the sediment and imagery data could be mapped using the same 1-second navigation. To interpolate the 2016 navigation data, first, a column of the original source filename was deleted from the processed navigation CSV text file (2016-005-FA_OdysseyAudioStamp_nav_ALL.csv). Next, a shapefile was created from the CSV file in Esri ArcGIS (version 10.3.1) and projected to WGS 84 UTM Zone 19N so that the distance in meters between the navigation fixes could be calculated. Then, the Generate Near Table tool was run using the planar method with the input and output features set to the UTM navigation shapefile and with the option checked to find only the closest feature. The output table was used to identify erroneous fixes, and two erroneous fixes were deleted from the navigation CSV text file. A Jupyter Notebook Python script (Interp_NAV_Dec2019_for_Nantucket2016-005-FA.ipynb) was run to interpolate and create a CSV text file of 1-second navigation. The original 2-second fixes were logged only when the video was recorded, so the script also interpolated between the end point of a video trackline and the start point of the next trackline. To create a final file of 1-second navigation, the points between the video trackline start and end times were extracted (which removed the interpolated positions during the transits between the video tracklines) and were saved as a CSV text file (out_interp_2016Nantucket_sel_for_gpx.csv). Finally, the CSV file was reorganized and formatted to have fields of the latitude, longitude, hours, minutes, seconds, Julian day, year, field activity ID, and Julian day and time. For the 2017 survey, navigation data were logged for the full Julian day, including when the survey vessel was at the dock and when it was transiting to, from, and between the sampling sites. First, the navigation data from 13:30:00 to 19:14:59 were extracted from the processed navigation CSV text file (2017022FA_TiogaShip_nav.csv) to remove the navigation logged at, departing, and returning to the dock. Next, columns of the original source filename and time (the hours, minutes, and seconds were listed individually in other columns) were deleted from the CSV text file, and leading spaces were deleted as needed. Then, a shapefile was created from the CSV file in Esri ArcGIS (version 10.3.1) and projected to WGS 84 UTM Zone 19N so that the distance in meters between the navigation fixes could be calculated. The Generate Near Table tool was run using the planar method with the input and output features set to the UTM navigation shapefile and with the option checked to find only the closest feature. The output table was used to identify erroneous fixes, but no erroneous fixes were identified. The navigation data, however, were noisy. To smooth the data, the coordinates were rounded from seven to six decimal places and every fourth fix was extracted. A Jupyter Notebook Python script (Interp_NAV_Dec2019_for_Nantucket2017-022-FA.ipynb) was run to interpolate and create a CSV text file of 1-second navigation (2017022FA_TiogaShip_nav_4secint_round6_interp_for_gpx.csv). Finally, the CSV file was reorganized and formatted to have fields of the latitude, longitude, hours, minutes, seconds, Julian day, year, field activity ID, and Julian day and time to create a final CSV file of 1-second navigation for the survey. This process step and the subsequent process steps were performed by the same person, Emily Huntley.

Step 7: Checked and updated sediment sample locations.
The sediment sample times (as recorded in the survey logs) were checked by viewing the sea-floor videos to see when the sampler was lifted off the sea floor at each site and updated with more precise times as appropriate. The new sample times were matched to the corresponding times in the final interpolated navigation files to update the latitude and longitude of each sample in the sediment grain-size analysis results spreadsheets in Microsoft Excel 2016 for Mac.

Step 8: Created final sediment grain-size analysis results CSV file.
The sediment grain-size analysis results spreadsheets for each survey were merged in Microsoft Excel 2016 for Mac and then edited to remove some fields, format fields, and add a no data value (-9999) to empty attributes as needed. The Microsoft Excel spreadsheet was then saved as a CSV file.

Step 9: Created a simplified sediment grain-size analysis results shapefile.
The sediment grain-size analysis results CSV file was copied and edited to create a simplified version of the CSV file with fewer attribute fields (specifically, STDEV, SKEWNESS, KURTOSIS, the individual phi measurements [e.g., PHI_11], and the percentages of shell or carbonate material in the coarse phi fractions [e.g., PHI-1_SHELLPCT] were removed). A shapefile was created using the simplified version of the CSV file in Esri ArcGIS (version 10.3.1), and XTools Pro (version 12.0) for Esri ArcGIS was used to modify some field parameters in the point shapefile (Table Operations - Table Restructure). Please note that this metadata file represents the CSV file; users should access the CSV file for the full sediment grain-size analysis results.