U.S. Geological Survey Data Series 514
Swath Bathymetry Surveys of the Monterey Bay Area from Point Año Nuevo to Moss Landing, San Mateo, Santa Cruz, and Monterey Counties, California
GPS Data Processing
The R/V Snavely was equipped with a CodaOctopus F180 attitude and position system for the duration of the survey. The F180 is running F190 firmware and receives RTK corrections directly. The RTK GPS data (2-cm error ellipse) are combined with the inertial-motion measurements directly within the F190 hardware so that high-precision position and attitude corrections are fed in real-time to the sonar acquisition equipment. The WGS84 (G1150) Epoch 2002.0 3-dimensional reference frame was used for all measurements.
Sound Velocity Profile Measurements
Sound velocity profile (SVP) measurements were collected, on average, every two hours throughout the survey. A total of 438 SVPs were collected for this survey; 114 SVPs were collected during field activity S-7-09-MB and 324 SVPs were collected during S-10-09-MB. In general, SVPs were collected every 2 hours, or when the survey vessel moved to a different survey block. Typically, two SVPs were collected every four lines. Water column SVPs varied significantly throughout the survey; however, this frequency of SVP collection was sufficient to correct for variations in sound velocity. Only one line from field activity S-7-09-MB (BlockA_230_044) shows a small artifact from an uncorrected sound-velocity error (smile) for part of its length. Insufficient sound-velocity data were available to correct this line, and no attempt was made to synthesize data.
SVPs 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). In addition, an Applied Micro Systems Micro SV accurate to ±0.03 m/s was deployed on the transducer frame for real-time sound-velocity adjustments at the transducer-water interface.
SVPs taken at this density constitute a largely unexplored dataset that provides insight into spatial and temporal temperature variation within the Monterey Bay area between mid-August and late December 2009.
Sonar Sounding Processing
The general processing workflow procedures for converting bathymetric soundings to a digital elevation model (DEM) are shown in figure 2.
GPS data and measurements of vessel motion are combined in the F180 hardware to produce a high-precision vessel-attitude packet. This packet is transmitted to the Swath Processor acquisition software in real-time 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 2,048 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 3.05.18.04). 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 is stored line-by-line in both raw (.sxr) and processed (.sxp) trackline files. For this field activity, processed files were filtered across-track with a mean filter at 0.5 m resolution. Processed (.sxp) files were further processed with sxpegn (build 151) by David Finlayson (USGS) to remove erroneous data from the files and to make valid gain-normalized amplitude data for amplitude data processing.
The DEM produced in this work is derived solely from the bathymetric data collected by the USGS during field activities S-7-09-MB and S-10-09-MB.
CARIS HIPS and SIPS (version 188.8.131.52 Service Pack 1) was used to clean and grid sounding data. Processed .sxp files were imported to CARIS, and field sheets were created within CARIS. Field-sheet extents were defined to the nearest even integer meter in ground coordinates (WGS84(G1150) UTM Zone 10) and created to approximately match Calif. State Waters Map Blocks 36-41, as defined by the WCMG California Seafloor Mapping Program. Because blocks 38 and 39, and blocks 40 and 41 had little horizontal overlap, a horizontal overlap was added to the eastern blocks in both cases; that is, the western bounds of blocks 39 and 41 were extended to create overlap between field sheets. A small field sheet (CA0) was created where there was no State Waters map block defined.
Survey lines were filtered to remove adjacent line data from nadir gaps. Target overlap between lines was 25-30 percent, though values ranged from ~10 percent to <50 percent depending on line spacing and data quality. CARIS Swath Angle BASE surfaces were created for each map block at 2 m resolution, and the subset editor was used to clean artifacts from biological targets and other unwanted soundings. Cleaned data were used to regenerate the BASE surfaces, and grids of depth and standard deviation were exported as XYZ point files.
XYZ files were imported to ArcGIS (version 9.3.1) and combined into a single grid for statistical analysis and DEM interpolation. The mean standard deviation of all cells in the Monterey Bay dataset was 0.29 m (1 sigma) and 0.44 m (2 sigma).
An interpolation mask was created by calculating the euclidean distance from cells containing data in the grid out to a distance of 20 m; this filled the nadir gaps and small data holes. Values less than 20 m were then set to NoData, and the resulting grid was buffered back toward the survey area the same distance. The complement of this grid was used as a processing mask for trimming and interpolation of the DEM.
Prior to interpolation, outliers were identified and removed by computing the z-score for each grid cell with a 7x7-cell moving kernel (rectangular focal mean N=49) over the entire grid and removing datapoints with a z-score >3. Z-score is defined as:
Bathymetry data were then interpolated using the ArcGIS FocalMean function, with one iteration of a 3x3 rectangular focal mean calculated to fill small data gaps. The resulting grid was converted into a multipoint file, and remaining holes in the raster were filled using natural-neighbors interpolation. Noise was added to the interpolated cells by creating a random grid with values within ±0.5 standard deviations of the dataset (0.14 m) and adding the random grid to the grid of interpolated cells. Voids in the bathymetry were filled with the resulting grid.
To convert the data from the WGS84 (G1150) epoch 2002.0 ellipsoid to NAD83 (CORS96) epoch 2002.0, the bathymetric data were exported from ArcGIS as an ESRI ASCII grid, and converted to an XYZ point file in a python script. Next, a 14-parameter Helmert transformation was applied to the data set with time-dependent transformation parameters calculated for January 1, 2002 according to methods outlined in Soler and Snay (2004). Calculations were applied using CS2CS (Version 4.4.6), an open-source program developed as part of the PROJ.4 Library, originally developed by Gerald Evenden while working for the USGS. Table 2 shows the specific parameters in the format required by CS2CS.
The NAD83 (CORS96) ellipsoid elevations in the bathymetry data were converted to orthometric heights based on NAVD88 using the National Geodetic Survey Geoid09 Model (National Geodetic Survey, 2009). The vertical datum was transformed from NAD83(CORS96) to NAVD88 using VDatum (Version 2.2.7), a vertical datum transformation tool under active development by the National Oceanic and Atmospheric Administration (NOAA) National Geodetic Survey (NGS), Office of Coast Survey (OCS), and Center for Operational Oceanographic Products and Services (CO-OPS). Figure 3 shows the settings used in VDATUM to transform vertical coordinates from NAD83(CORS96) to NAVD88 for this project. Data were then re-gridded in ArcGIS using a nearest-neighbor gridding algorithm on 2-m cells snapped to integer meter cell centers. Final NAD83(CORS96) DEMS were exported in ESRII ASCII GRID (.ASC) and .TIF formats. Horizontal accuracy is on the order of 2 meters due to transformations and grid cell size.
For more information, contact David Finlayson.