This data release presents eelgrass distributions and bathymetry data derived from acoustic surveys of Bellingham Bay, Washington. Survey operations were conducted between February 16 and February 21, 2019 (USGS Field Activity Number 2019-606-FA) by a team of scientists from the U.S. Geological Survey Pacific Coastal and Marine Science Center and Washington State Department of Ecology. Eelgrass and bathymetry data were collected from the R/V George Davidson equipped with a single-beam sonar system and global navigation satellite system (GNSS) receiver. The sonar system consisted of a Biosonics DT-X single-beam echosounder and 420 kHz transducer with a 6-degree beam angle. Depths from the echosounder were computed using sound velocity data measured using a YSI CastAway CTD during the survey. Positioning of the vessel was determined at 5 Hz using a Trimble R9s GNSS receiver and Trimble Zephyr Model 2 antenna operating in real time kinematic (RTK) mode. Differential corrections were transmitted by a cellular modem to the GNSS receiver on the survey vessel at 1-Hz from a GNSS continuously operating reference station operated by the Washington State Reference Network (WSRN; http://www.wsrn3.org/) located in the city of Bellingham (station BELI). Output from the GNSS and sonar systems were combined in real time by the Biosonics DT-X deck unit and output to a computer running HYPACK hydrographic survey software. Navigation information was displayed on a video monitor, allowing the vessel operator to navigate along predefined survey lines spaced at 25- to 100-m intervals alongshore at speeds of approximately 2 m/s. Acoustic backscatter data were analyzed using a custom graphical user interface (GUI) that implements a signal processing algorithm applied to each sonar sounding to extract the location of the bottom and presence of vegetation (Stevens and others, 2008 ). Individual acoustic returns along a survey line were grouped into packets of ten, and eelgrass percent cover was calculated as the fractional percent of acoustic returns that were classified as vegetated within each group, resulting in a estimate of percent cover every 4 to 5 m (depending on vessel speed). The positioning data from the bathymetric survey were postprocessed using Waypoint Grafnav to apply differential corrections with data recorded at the GNSS base station BELI and archived by the WSRN; these data superseded the original positions recorded in real time. The GUI was used to combine filtered sonar data with postprocessed positioning data and orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. The estimated vertical uncertainty of the bathymetric measurements ranged from 2.0 cm to 18.3 cm with a mean of 6.7 cm. Uncertainty in the vertical positions associated with pitch and roll of the survey vessel is unknown. The final point data are provided in a comma-separated text file and are projected in Cartesian coordinates using the Universal Transverse Mercator (UTM), Zone 10 north, meters coordinate system.

This portion of the USGS data release presents eelgrass distributions derived from towed underwater video surveys of the Nisqually River delta, Washington in 2014 (USGS Field Activity Number D-01-14-PS). Eelgrass data were collected from the R/V George Davidson equipped with a towed underwater video system and global navigation satellite system (GNSS) receiver. The underwater video system consisted of a Splashcam standard definition video camera connected to a Sony GV-D1000 video monitor and tape recorder. Positioning of the survey vessel was determined at 0.5 Hz intervals using a Garmin 76c GNSS receiver. The positioning data from the GNSS were encoded onto the audio track of the digital video recording using Red Hen Systems (RHS) VMS200 hardware. Underwater video data were recorded as the vessel navigated along a series of shore-perpendicular transects at speeds between 1 and 2 knots. The underwater video recording was later reviewed and the presence or absence of eelgrass was determined for each 2-s segment of video tape. These data were used to evaluate the classification of single-beam sonar data acquired during the same time period.

This dataset shows the eelgrass data extent identified from the acoustic surveys completed within and adjacent to the boundaries of Cape Cod National Seashore (CaCo) from Duck Harbor to Jeremy Point in Cape Cod Bay, and Wellfleet Harbor from Wellfleet to Eastham, Massachusetts, August 10 – December 12, 2015, and July 12 – September 7, 2016. Full coverage sidescan and partial coverage bathymetry data were collected using an Edgetech 6205 Phase-Measuring Sidecan Sonar. In total, 5723.8 hectares of sidescan imagery were mapped at primarily 20 – 40 meter line spacing and 50 meter swath range to allow overlap of lines and a total of 19.3 hectares were identified as Eelgrass. The minimum mapping unit for this study site for eelgrass was 100 square meters and was hand digitized from individual sidescan sonar files at a visual extent of 1:1000 m.

This portion of the USGS data release presents eelgrass distributions derived from towed underwater video surveys of the Nisqually River delta, Washington in 2012 (USGS Field Activity Number D-01-12-PS). Eelgrass data were collected from the R/V George Davidson equipped with a towed underwater video system and global navigation satellite system (GNSS) receiver. The underwater video system consisted of a Splashcam standard definition video camera connected to a Sony GV-D1000 video monitor and tape recorder. Positioning of the survey vessel was determined at 1 Hz intervals using a Trimble R7 GNSS receiver and Trimble Zephyr Model 2 antenna. The positioning data from the GNSS were encoded onto the audio track of the digital video recording using Red Hen Systems (RHS) VMS200 hardware. Underwater video data were recorded as the vessel navigated along a series of shore-perpendicular transects at speeds between 1 and 2 knots. The underwater video recording was later reviewed and the presence or absence of eelgrass was determined for each 1-s segment of video tape. These data were used to evaluate the classification of single-beam sonar data acquired during the same time period.

This portion of the USGS data release presents eelgrass distributions derived from towed underwater video surveys of the Nisqually River delta, Washington in 2017 (USGS Field Activity Number 2017-614-FA). Eelgrass data were collected from the R/V George Davidson equipped with a towed underwater video system and global navigation satellite system (GNSS) receiver. The underwater video system consisted of a Splashcam standard definition video camera connected to a Sony GV-D1000 video monitor and tape recorder. Positioning of the survey vessel was determined at 1 Hz intervals using a Trimble R7 GNSS receiver and Trimble Zephyr Model 2 antenna. The positioning data from the GNSS were encoded onto the audio track of the digital video recording using Red Hen Systems (RHS) VMS200 hardware. Underwater video data were recorded as the vessel navigated along a series of shore-perpendicular transects at speeds between 1 and 2 knots. The underwater video recording was later reviewed and the presence or absence of eelgrass was determined for each 1-s segment of video tape. These data were used to evaluate the classification of single-beam sonar data acquired during the same time period.

This portion of the USGS data release presents eelgrass distributions derived from towed underwater video surveys of the Nisqually River delta, Washington in 2017 (USGS Field Activity Number 2017-614-FA). Eelgrass data were collected from the R/V George Davidson equipped with a towed underwater video system and global navigation satellite system (GNSS) receiver. The underwater video system consisted of a Splashcam standard definition video camera connected to a Sony GV-D1000 video monitor and tape recorder. Positioning of the survey vessel was determined at 1 Hz intervals using a Trimble R7 GNSS receiver and Trimble Zephyr Model 2 antenna. The positioning data from the GNSS were encoded onto the audio track of the digital video recording using Red Hen Systems (RHS) VMS200 hardware. Underwater video data were recorded as the vessel navigated along a series of shore-perpendicular transects at speeds between 1 and 2 knots. The underwater video recording was later reviewed and the presence or absence of eelgrass was determined for each 1-s segment of video tape. These data were used to evaluate the classification of single-beam sonar data acquired during the same time period.

Eelgrass (Zostera marina) characteristics, sediment grain size distributions, sediment total organic carbon contents (TOC), carbon isotope ratios of sediment organic matter, and total carbon to total nitrogen ratios were measured at four lower intertidal sites in Bellingham Bay, Washington, July 2-5, 2019.

These data are in six tables relating to surveys of eelgrass beds in three bays adjacent to Togiak National Wildlife Refuge, in southwestern Alaska. The tables provide environmental conditions, eelgrass abundance, distribution, and measurements used to estimate overall biomass.

These data are in six tables relating to surveys of eelgrass beds in three bays adjacent to Togiak National Wildlife Refuge, in southwestern Alaska. The tables provide environmental conditions, eelgrass abundance, distribution, and measurements used to estimate overall biomass.

Seafloor character, a combination of seafloor induration (surface hardness) and rugosity, was derived from multibeam echosounder (MBES) and annotated underwater video data collected offshore of the Eel River, California. The MBES and underwater video data were collected in support of the U.S. Geological Survey (USGS) California Seafloor Mapping Program, under a collaboration with the California State University Monterey Bay Seafloor Mapping Lab, the California Ocean Protection Council, and the National Oceanic and Atmospheric Administration (NOAA). Substrate observations from the underwater video were translated into Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data Committee, 2012) induration classes to use as training for a supervised numerical classification of the MBES data. The seafloor character raster is provided as a 2-meter resolution GeoTIFF.