Seafloor character offshore of the Eel River, California

Frequently anticipated questions:

• What does this data set describe?
  1. How might this data set be cited?
  2. What geographic area does the data set cover?
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
  5. What is the general form of this data set?
  6. How does the data set represent geographic features?
  7. How does the data set describe geographic features?
• Who produced the data set?
  1. Who are the originators of the data set?
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
• Why was the data set created?
• How was the data set created?
  1. From what previous works were the data drawn?
  2. How were the data generated, processed, and modified?
  3. What similar or related data should the user be aware of?
• How reliable are the data; what problems remain in the data set?
  1. How well have the observations been checked?
  2. How accurate are the geographic locations?
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
  5. How consistent are the relationships among the data, including topology?
• How can someone get a copy of the data set?
  1. Are there legal restrictions on access or use of the data?
  2. Who distributes the data?
  3. What's the catalog number I need to order this data set?
  4. What legal disclaimers am I supposed to read?
  5. How can I download or order the data?
• Who wrote the metadata?

What does this data set describe?

1. How might this data set be cited?
   Cochrane, Guy R., 20230930, Seafloor character offshore of the Eel River, California: data release DOI:10.5066/P902YIF5, U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, California.

   Online Links:

   • https://doi.org/10.5066/P902YIF5

   This is part of the following larger work.
   Cochrane, Guy R., 2023, Bathymetry, backscatter intensity, and benthic habitat offshore of the Eel River, California: data release DOI:10.5066/P902YIF5, U.S. Geological Survey, Reston, VA.

   Online Links:

   • https://doi.org/10.5066/P902YIF5

   Other_Citation_Details:

   Suggested Citation: Cochrane, G.R., 2023, Bathymetry, backscatter intensity, and benthic habitat offshore of the Eel River, California: U.S. Geological Survey data release, https://doi.org/10.5066/P902YIF5.

2. What geographic area does the data set cover?

   West_Bounding_Coordinate: -124.460418
   East_Bounding_Coordinate: -124.245087
   North_Bounding_Coordinate: 40.69593
   South_Bounding_Coordinate: 40.536667
   

3. What does it look like?

   SeafloorCharacter_OffshoreEelRiver.jpg (JPEG)

   Preview image of Seafloor Character data offshore of the Eel River

4. Does the data set describe conditions during a particular time period?

   Calendar_Date: 2010

   Currentness_Reference:

   ground condition at time MBES and video data were collected

5. What is the general form of this data set?

   Geospatial_Data_Presentation_Form: GeoTIFF
   

6. How does the data set represent geographic features?
   1. How are geographic features stored in the data set?
      This is a Raster data set. It contains the following raster data types:
      • Dimensions 8981 x 8972 x 1, type Grid Cell
   2. What coordinate system is used to represent geographic features?
      

      Grid_Coordinate_System_Name: Universal Transverse Mercator
      Universal_Transverse_Mercator:

      UTM_Zone_Number: 10
      Transverse_Mercator:

      Scale_Factor_at_Central_Meridian: 0.9996
      Longitude_of_Central_Meridian: -123.00000
      Latitude_of_Projection_Origin: 0.00000
      False_Easting: 500000.0
      False_Northing: 0.00
      

      Planar coordinates are encoded using coordinate pair
      Abscissae (x-coordinates) are specified to the nearest 10.0
      Ordinates (y-coordinates) are specified to the nearest 10.0
      Planar coordinates are specified in Meters
      The horizontal datum used is D_WGS_1984.
      The ellipsoid used is WGS_844.
      The semi-major axis of the ellipsoid used is 6378137.00.
      The flattening of the ellipsoid used is 1/298.257223563.
      
7. How does the data set describe geographic features?

   value

   seafloor character class integer value (Source: Producer defined)

   Value

   seafloor character class (Source: Cochrane (2008))

   Value	Definition
   1	soft and flat fine grain sedimented seafloor
   2	hard and flat coarse grain sediment and bedrock seafloor
   3	hard and rugose boulder, megaclast, and bedrock seafloor

   count

   number of pixels assigned to class (Source: none)

   Range of values
   Minimum:	20504
   Maximum:	24553056
   Units:	none

   Entity_and_Attribute_Overview:

   The complete 2-m resolution Offshore the Eel River seafloor character grid is a GeoTIFF image with integer values representing induration and rugosity classes: 1 for soft and flat bottom, 2 for hard and flat bottom, and 3 for hard and rugose bottom.

   Entity_and_Attribute_Detail_Citation: Cochrane, 2008
   

Who produced the data set?

1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
   • Guy R. Cochrane
2. Who also contributed to the data set?
3. To whom should users address questions about the data?
   U.S. Geological Survey, Pacific Coastal and Marine Science Center

   Attn: PCMSC Science Data Coordinator

   2885 Mission Street

   Santa Cruz, CA
   

   831-427-4747 (voice)

   pcmsc_data@usgs.gov

Why was the data set created?

How was the data set created?

1. From what previous works were the data drawn?

   CSUMB Seafloor mapping lab library (source 1 of 2)

   California State University, Monterey Bay, Seafloor Mapping Lab, 2008, Southern California 2008 CSMP surveys: California State University, Monterey Bay, Seafloor Mapping Lab Data Library: U.S. Geological Survey, online.

   Online Links:

   • http://seafloor.otterlabs.org/SFMLwebDATA_SURVEYMAP.htm

   Type_of_Source_Media: online database and viewer
   Source_Contribution: MBES data is classified into seafloor character data
   

   USGS Marine video portal (source 2 of 2)

   Golden, Nadine E., Ackerman, Seth D., and Dailey, Evan T., 2015, Coastal and Marine Geology Program video and photograph portal: U.S. Geological Survey, online.

   Online Links:

   • https://doi.org/10.5066/F7JH3J7N

   Type_of_Source_Media: online database and viewer
   Source_Contribution:

   underwater video was used to help train and classify habitat maps

2. How were the data generated, processed, and modified?

   Date: 2010 (process 1 of 3)

   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). Data sources used in this process:

   • CSUMB Seafloor mapping lab library

   Date: 2012 (process 2 of 3)

   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).

   Date: 2023 (process 3 of 3)

   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.

3. What similar or related data should the user be aware of?
   Reid, Jane A., Reid, Jamey M., Jenkins, Chris J., Zimmermann, Mark, Williams, S. Jeffress, and Field, Michael E., 2019, usSEABED: Pacific Coast (California, Oregon, Washington) Offshore Surficial-Sediment Data Release, version 1: Data Series DS 182, U.S. Geological Survey, Reston, VA.

   Online Links:

   • https://doi.org/10.3133/ds182

   Other_Citation_Details:

   Reid, Jane.A., Jamey M. Reid, Chris J. Jenkins, Mark Zimmermann, S. Jeffress Williams, Michael E. Field, 2006, U.S. Geological Survey Data Series, number 182.

   Golden, Nadine, 2019, California State Waters Map Series Data Catalog: Data Series DS 781, U.S. Geological Survey, Reston, VA.

   Online Links:

   • https://doi.org/10.3133/ds781

   Other_Citation_Details:

   Golden, N.E., compiler, 2019, California State Waters Map Series Data Catalog, https://doi.org/10.3133/ds781

   Cochrane, Guy R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat.

   Online Links:

   • https://seagrant.uaf.edu/lib/aksg/0803/mhmta-cochrane.pdf

   Other_Citation_Details:

   Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194.

   Federal Geographic Data Committee, 2012, Coastal and Marine Ecological Classification Standard.

   Online Links:

   • https://www.fgdc.gov/standards/projects/cmecs-folder/CMECS_Version_06-2012_FINAL.pdf

   Other_Citation_Details:

   Federal Geographic Data Committee, 2012, Coastal and Marine Ecological Classification Standard, 343 p.

   Anderson, Tara J., Cochrane, Guy R., Roberts, Dale A., Chezar, Hank, and Hatcher, Gerry, 2007, A rapid method to characterize seabed habitats and associated macro-organisms.

   Other_Citation_Details:

   Anderson, T.J., Cochrane, G.R., Roberts, D.A., Chezar, H., and Hatcher, G., 2007, A rapid method to characterize seabed habitats and associated macro-organisms, in Todd, B.J., and Greene, H.G., eds., Mapping the seafloor for habitat characterization: Geological Association of Canada Special Paper 47, p. 71-79.

How reliable are the data; what problems remain in the data set?

1. How well have the observations been checked?
   A small number of observations of seafloor character from the video data were used to supervise the classification of the MBES data. All the video observations were subsequently used to assess the accuracy of the predicted character values. Additional observations of substrate were obtained from usSEABED (Reid and others, 2009). Two types of accuracy were calculated for the raster using a 10-meter radius circular buffer around each observation point (shown on the overview figure) in the study area. Presence accuracy is the number of observations where the buffer around the observation had at least one predicted value that matched the observed value. Majority accuracy is the percentage of observations where the largest number of predicted pixels in the buffer matched the observed value. There were 29 observations in the study area. All the observations were in the soft-flat class so there is no accuracy value for the other two classes. For soft-flat class the presence accuracy was 100 percent and the majority accuracy was 100 percent.
2. How accurate are the geographic locations?
   The POS MV position and motion compensation system used when collecting the MBES data has a horizontal positional accuracy of about 0.5 m with DGPS corrections and roll and pitch accuracies of about 0.02 degrees (http://www.measutronics.com/wp-content/uploads/2011/01/posmv320_specifications.pdf). Accuracies of final products may be lower due to water depth and total propagated uncertainties of the mapping systems, which include sonar system, position and motion compensation system, and navigation, as well as data processing that includes sounding cleaning, gridding, and datum transformations.
3. How accurate are the heights or depths?
   
4. Where are the gaps in the data? What is missing?
   Dataset is considered complete for the area mapped with MBES data.
5. How consistent are the relationships among the observations, including topology?
   No formal logical accuracy tests were conducted.

How can someone get a copy of the data set?

1. Who distributes the data set? (Distributor 1 of 1)
   
   U.S. Geological Survey - CMGDS

   2885 Mission Street

   Santa Cruz, CA
   

   831-427-4747 (voice)

   pcmsc_data@usgs.gov
2. What's the catalog number I need to order this data set? These data are available in GeoTIFF format (SeafloorCharacter_OffshoreEelRiver.tif), along with a tif world file (.tfw).
3. What legal disclaimers am I supposed to read?
   Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty.
4. How can I download or order the data?
   • Availability in digital form:

     Data format:	These data are available in GeoTIFF format, along with a tif world file (.tfw). in format GeoTIFF (version ArcMap (version 10.8.2)) Size: 0.19
     Network links:	https://doi.org/10.5066/P902YIF5 https://doi.org/10.3133/ds781

   • Cost to order the data: None.

5. What hardware or software do I need in order to use the data set?
   The downloadable data file has been compressed with the Windows 10 "zip" command and can be unzipped using Windows File Explorer, or with Winzip (or other compression tools). To utilize these data, the user must have software capable of viewing a GeoTIFF file.

Who wrote the metadata?

Dates:

Last modified: 30-Sep-2023

Metadata author:

U.S. Geological Survey, Pacific Coastal and Marine Science Center

Attn: PCMSC Science Data Coordinator

2885 Mission Street

Santa Cruz, CA

831-427-4747 (voice)

pcmsc_data@usgs.gov

Metadata standard:

Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)