Seafloor character offshore of the Eel River, California

Bathymetry and backscatter data were collected by Fugro Pelagos in 2008, using a combination of 400-kHz Reson 7125, 240-kHz Reson 8101, and 100-kHz Reson 8111 multibeam echosounders. An Applanix POS-MV (Position and Orientation System for Marine Vessels) was used to accurately position the vessels during data collection, and it also accounted for vessel motion such as heave, pitch, and roll, with navigational input from GPS receivers. Smoothed Best Estimated Trajectory (SBET) files were postprocessed from logged POS-MV files. Sound-velocity profiles were collected with an Applied Microsystems (AM) SVPlus sound velocimeter. Soundings were corrected for vessel motion using the Applanix POS-MV data, for variations in water-column sound velocity using the AM SVPlus data, and for variations in water height (tides) and heave using the postprocessed SBET data (California State University, Monterey Bay, Seafloor Mapping Lab, 2016). The Reson backscatter data were postprocessed using Geocoder software. The backscatter intensities were radiometrically corrected (including despeckling and angle-varying gain adjustments), and the position of each acoustic sample was geometrically corrected for slant range on a line-by-line basis. After the lines were corrected, they were mosaicked into 0.5-m resolution images (California State University, Monterey Bay, Seafloor Mapping Lab, 2016).

Substrate observations used to supervise the classification of the MBES data were derived from underwater video collected by the USGS in 2012. A USGS camera sled was used that housed two standard-definition video cameras (one forward looking and one downward looking), as well as a high-definition (1,080 x 1,920-pixel resolution) video camera and an 8-megapixel digital still camera. The camera sled was towed 1 to 2 m over the seafloor at speeds of between 1 and 2 nautical miles/hour. While the camera is deployed, several different observations are recorded for a 10-second period once every minute, using the protocol of Anderson and others (2007). Observations of primary substrate, secondary substrate, slope, abiotic complexity, biotic complexity, and biotic cover are mandatory observations every minute. Observations of key geologic features and the presence of key species also are made when observed. A digital still photograph was captured once every 30 seconds. Additional observations of substrate were obtained from usSEABED (Reid and others, 2009).

The CSUMB 0.5-m-resolution backscatter images were mosaiced and clipped to the study area boundary. The backscatter mosaics were decimated to 2-m resolution georeferenced TIFF images using the 2m bathymetry as a snap grid. A vector ruggedness raster derived from the bathymetry data and a backscatter-intensity raster were used in the seafloor characterization in an ArcGIS Geographic Information Systems (GIS) project. Seafloor character was classified in ArcGIS using the Maximum Likelihood Classification tool. Observations of substrate from the seafloor video were used to supervise the classification as described in Cochrane (2008). The seafloor character grids are available in a GeoTIFF file.