March 2017 bathymetry (MLLW) of Coyote Creek and Alviso Slough, South San Francisco Bay, California

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Frequently anticipated questions:


What does this data set describe?

Title:
March 2017 bathymetry (MLLW) of Coyote Creek and Alviso Slough, South San Francisco Bay, California
Abstract:
1-m resolution bathymetry collected in Coyote Creek and Alviso Slough in March 2017. Projection = UTM, zone 10 in meters, Horizontal Datum = NAD83 (CORS96), Vertical Datum = MLLW, all units in meters. The surveys extend east from Calaveras Point along Coyote Creek to the railroad bridge, along Alviso Slough to the town of Alviso (just over 7 km), and along the 3.7 km of Guadalupe Slough closest to the San Francisco Bay, California.
Supplemental_Information:
Additional information about the field activities from which these data were derived is available online at: https://cmgds.marine.usgs.gov/fan_info.php?fan=2017-628-FA Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
  1. How might this data set be cited?
    U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC), Santa Cruz, CA., 2018, March 2017 bathymetry (MLLW) of Coyote Creek and Alviso Slough, South San Francisco Bay, California:.

    Online Links:

    This is part of the following larger work.

    U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC), Santa Cruz, CA., 2018, Bathymetry and Digital Elevation Models of Coyote Creek and Alviso Slough, South San Francisco Bay, California (Version 4, Revised 2018): U.S. Geological Survey Open-File Report 2011-1315.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -122.060187436
    East_Bounding_Coordinate: -121.974560855
    North_Bounding_Coordinate: 37.4706742088
    South_Bounding_Coordinate: 37.4231662547
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 28-Mar-2017
    Ending_Date: 29-Mar-2017
    Currentness_Reference:
    ground condition
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: raster digital data
  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 5052 x 6881, 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
      Latitude_of_Projection_Origin: 0.0
      False_Easting: 500000
      False_Northing: 0.0
      Planar coordinates are encoded using row and column
      Abscissae (x-coordinates) are specified to the nearest 1.0
      Ordinates (y-coordinates) are specified to the nearest 1.0
      Planar coordinates are specified in meters
      The horizontal datum used is North American Datum of 1983 (CORS96).
      The ellipsoid used is Geodetic Reference System 80.
      The semi-major axis of the ellipsoid used is 6378137.
      The flattening of the ellipsoid used is 1/298.257.
      Vertical_Coordinate_System_Definition:
      Altitude_System_Definition:
      Altitude_Datum_Name: Mean Lower Low Water (MLLW)
      Altitude_Resolution: 0.01
      Altitude_Distance_Units: meters
      Altitude_Encoding_Method: Attribute values
  7. How does the data set describe geographic features?
    Altitude
    Elevation relative to MLLW in meters. Values are positive up. (Source: USGS Open-File Report: 2011-1315)

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC), Santa Cruz, CA.
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    USGS Pacific Coastal and Marine Science Center
    Attn: Amy Foxgrover
    Geographer
    2885 Mission Street
    Santa Cruz, CA
    USA

    (831) 460-7561 (voice)
    (831) 427-4748 (FAX)
    afoxgrover@usgs.gov

Why was the data set created?

To monitor bathymetric change as the South Bay Salt Pond Restoration Project progresses (http://www.southbayrestoration.org).

How was the data set created?

  1. From what previous works were the data drawn?
    2017-628-FA (source 1 of 1)
    U.S. Geological Survey, Coastal and Marine Geology Program, 2017, USGS CMG Field Activity 2017-628-FA.

    Online Links:

    Type_of_Source_Media: online
    Source_Contribution:
    This 2017 field activity collected bathymetric data in San Francisco Bay.
  2. How were the data generated, processed, and modified?
    Date: 2017 (process 1 of 6)
    Bathymetric surveys were conducted using a 234.5 kHz SEA (Systems Engineering and Assessment Ltd) SWATHplus-M phase-differencing sidescan sonar. The sonar was pole-mounted on the 34-foot USGS mapping vessel R/V Parke Snavely, and affixed to a hull brace. GPS position data were passed through an Applanix Position and Motion Compensation System for Marine Vessels POS/MV inertial measurement unit (IMU) to the sonar hardware and data-collection software. Sonar heads, GPS antennae, and the IMU were surveyed in place to a common reference frame with a Geodimeter 640 Total Station. The R/V Snavely was outfitted with three networked workstations and a navigation computer for use by the captain and survey crew for data collection and initial processing.
    Date: 2017 (process 2 of 6)
    An Applanix Position and Motion Compensation System for Marine Vessels (POS/MV) was used to accurately determine the survey vessel's position. The POS/MV utilizes Global Navigation Satellite System (GNSS) data in combination with angular rate and acceleration data from the IMU and heading data from the GPS Azimuth Measurement Systems (GAMS) to produce accurate position and orientation information through a virtual network of base stations. As opposed to receiving high-accuracy Real-Time Kinematic (RTK) corrections, the POS records raw inertial and GNSS data while surveying, which is later refined through post processing to incorporate publicly available GPS data from nearby base stations. During post processing the POS/MV data is run through POSPac software to produce a Smoothed Best Estimate of Trajectory (SBET) file, which is then imported back into Swath Processor to produce high-accuracy positions relative to the WGS84 ellipsoid. The RMS results from our POS/MV surveys show positional errors of less than 5 cm in X, Y, and Z.
    Date: 2017 (process 3 of 6)
    Sound velocity measurements were collected continuously with an Applied Micro Systems Micro SV deployed on the transducer frame for real-time sound velocity adjustments at the transducer-water interface. The Micro SV is accurate to +/- 0.03 m/s. In addition, sound velocity profiles (SVP) were collected with an Applied Micro Systems, SvPlus 3472. This instrument provides time-of-flight sound-velocity measurements by using invar rods with a sound-velocity accuracy of +/- 0.06 m/s, pressure measured by a semiconductor bridge strain gauge to an accuracy of 0.15 percent (Full Scale) and temperature measured by thermistor to an accuracy of 0.05 degrees Celsius (Applied Microsystems Ltd., 2005).
    Date: 2017 (process 4 of 6)
    GPS data and measurements of vessel motion (heave, pitch, and roll) are combined in the POS/MV hardware to produce a high-precision vessel attitude packet. This packet is transmitted to the Swath Processor acquisition software in post-processing and combined with instantaneous sound velocity measurements at the transducer head before each ping. Up to 20 pings per second are transmitted with each ping consisting of 2048 samples per side (port and starboard). The returned samples are projected to the seafloor using a ray-tracing algorithm working with the previously measured sound velocity profiles in SEA Swath Processor (version 3.12.7). A series of statistical filters are applied to the raw samples that isolate the seafloor returns from other uninteresting targets in the water column. Finally, the processed data are stored line-by-line in both raw (.sxr) and processed (.sxp) trackline files.
    Date: 2017 (process 5 of 6)
    The raw bathymetry data were filtered in SEA Swath Processor (version 3.12.7) and imported into CARIS HIPS and SIPS (version 10.3) for post-processing. Within CARIS a swath angle BASE (Bathymetric with Associated Statistical Error) surface was created at 1 m resolution and the subset editor used to manually eliminate any remaining outliers or artifacts. The average depth within each 1 by 1 m cell was exported as an ASCII text file and imported into Surfer (version 10) for interpolation using a linear kriging algorithm with a 1-simga nugget of 0.05 m and a 2 by 2 m search radius. The resultant grid was exported to ESRI ArcMap (version 10.2.2) for display and further analyses. The entire survey was shoaled by 11 cm to account for a combination of biases resulting from changes in the boat instrumentation and configurations that occurred since the initial survey was collected in 2010.
    Date: 2017 (process 6 of 6)
    To convert the bathymetry from WGS84 ellipsoid heights to the tidal datum of MLLW the data were first transformed from WGS84(ITRF2000) to the NAD83(CORS96) ellipsoid using a 14-point Helmert transformation described by Soler and Snay (2004) using the command line tool CS2CS in the Proj4 library (http://trac.osgeo.org/proj/). A fixed Geoid09 offset of -32.62 m was then applied to convert the NAD83 ellipsoid heights to orthometric heights NAD83(CORS96)/NAVD88. The orthometric NAVD88 elevations were converted to MLLW using the conversions provided by the CO-OPS division of NOAA for a 2005 bathymetric survey of South San Francisco Bay (Foxgrover and others, 2007).
  3. What similar or related data should the user be aware of?
    Foxgrover, Amy C., Jaffe, Bruce E., Hovis, Gerald T., Martin, Craig A., Hubbard, James R., Samant, Manoj R., and Sullivan, Steve M., 2007, 2005 Hydrographic Survey of South San Francisco Bay, California: Open-File Report 2007-1169, U.S. Geological Survey, Reston, VA.

    Online Links:

    Ltd., Applied Microsystems, 2005, SVplus sound velocity, temperature, and depth profiler user's manual: User's manual revision 1.23.

    Soler, T., and Snay, R.A., 2004, Transforming positions and velocities between the International Terrestrial Reference Frame of 2000 and North American Datum of 1983: Journal article Journal of Surveying Engineering, v. 130, no. 2.


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

  1. How well have the observations been checked?
    These bathymetric data have not been independently verified for accuracy.
  2. How accurate are the geographic locations?
    Uncertainty in the horizontal position of each sounding is a function of the total uncertainty propagated through each of the following component instruments: 1) base station GPS, 2) vessel GPS, 3) inertial motion unit (IMU), 4) water sound velocity model, and 5) beam spreading in the water column. Assuming no systematic errors in the measurement instruments themselves, beam spreading is the dominate source of positional uncertainty. The 1-degree sonar beam of the SWATHplus-M results in horizontal uncertainty ranging from 0.10 m at 10 m slant range, to about 0.45 m at 50 m slant range.
  3. How accurate are the heights or depths?
    After filtering the data to remove obvious outliers, the standard deviation of the remaining sounding elevations was calculated for each 1 m by 1 m cell (each containing 19 soundings on average) in CARIS. The mean of the standard deviation for all cells in the survey is 0.09 m. Additional uncertainty associated with the vertical datum conversion from NAVD88 to MLLW has not been assessed.
  4. Where are the gaps in the data? What is missing?
    The raw bathymetry data were filtered in SEA Swath Processor and imported into CARIS HIPS and SIPS for post-processing. Within CARIS a swath angle BASE (Bathymetric with Associated Statistical Error) surface was created at 1 m resolution and the subset editor used to manually eliminate any remaining outliers or artifacts. The average depth within each 1 by 1 m cell was exported as an ASCII text file and imported into Surfer for interpolation using a linear kriging algorithm with a 1-simga nugget of 0.05 m and a 2 by 2 m search radius. The resultant grid was exported to ESRI ArcMap software for display.
  5. How consistent are the relationships among the observations, including topology?
    All bathymetric values are derived from the same instruments and processing workflow.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints: None
Use_Constraints:
USGS-authored or produced data and information are in the public domain from the U.S. Government and are freely redistributable with proper metadata and source attribution. Please recognize and acknowledge the U.S. Geological Survey as the originator of the dataset and in products derived from these data. This information is not intended for navigational purposes.
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey, Pacific Coastal and Marine Science Center (PCMSC)
    Attn: Amy Foxgrover
    2885 Mission Street
    Santa Cruz, CA
    US

    831-460-7561 (voice)
    831-427-4748 (FAX)
    afoxgrover@usgs.gov
  2. What's the catalog number I need to order this data set? These data are available in both X,Y,Z text file format and ESRI ASCII Raster format. Both formats are contained in a single zip file (Mar_2017.zip), which also includes CSDGM FGDC-compliant metadata.
  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: The ASCII file consists of header information containing a set of keywords, followed by cell values in row-major order. The file format is:
      
      <NCOLS xxx>
      <NROWS xxx>
      <XLLCENTER xxx | XLLCORNER xxx>
      <YLLCENTER xxx | YLLCORNER xxx>
      <CELLSIZE xxx>
      {NODATA_VALUE xxx}
      row 1
      row 2
      .
      .
      .
      row n
      
      
      where xxx is a number, and the keyword nodata_value is optional and defaults to -9999. Row 1 of the data is at the top of the grid, row 2 is just under row 1 and so on. The nodata_value is the value in the ASCII file to be assigned to those cells whose true value is unknown. In the grid they will be assigned the keyword NODATA. Cell values are delimited by spaces. No carriage returns are necessary at the end of each row in the grid (although they are included in this case). The number of columns in the header is used to determine when a new row begins. The number of cell values is equal to the number of rows times the number of columns. in format ESRI ASCII Raster Size: 209
      Network links: https://doi.org/10.3133/ofr20111315
      http://pubs.usgs.gov/of/2011/1315/
    • Cost to order the data: No cost


Who wrote the metadata?

Dates:
Last modified: 02-Feb-2018
Metadata author:
Amy Foxgrover
U.S. Geological Survey, Pacific Coastal and Marine Science Center
2885 Mission Street
Santa Cruz, California
USA

(831) 460-7561 (voice)
afoxgrover@usgs.gov
Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)

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