• Abstract
• Survey Outline
• Geodetic Control
• Data Processing
• Survey Results
• Data Tables
• Figures
• Acknowledgments
• References
• Appendix
• USGS Related Links
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Bathymetry and Acoustic Backscatter—Estero Bay, California

Data Processing

The general processing work flow for converting raw bathymetric soundings to a digital elevation model (DEM), also called grids, is shown in fig. 4. Critical aspects of the processing procedure are discussed below.

Vessel Position and Attitude

The R/V Parke Snavely was equipped with a POS MV 320 system, which records inertial-motion and GNSS position data for the duration of the survey. The POS MV provides real-time pitch information to the multibeam sonar system to facilitate pitch-compensation (see discussion below). As discussed in the Geodetic Control Section, the GNSS data are combined with the inertial-motion measurements within the POSPac MMS software, and high-precision position and attitude corrections are exported as SBET files for merging with the multibeam data.

Sound Velocity Measurements

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 (0.1 ft/s). In addition, sound velocity profiles (SVP) were collected with an Applied Micro Systems, SvPlus 3472. This instrument provided time-of-flight sound-velocity measurements by using invar rods with a sound-velocity accuracy of ±0.06 m/s (0.2 ft/s), pressure was measured by a semiconductor bridge strain gauge to an accuracy of 0.15 percent (500 dbar, full scale), and temperature was measured by thermistor with an accuracy of 0.05 degrees Celsius (Applied Microsystems Ltd., 2005).

Sonar Sounding Processing

CARIS HIPS and SIPS (version 7.1.0) bathymetry processing software was used to georeference the raw sonar data. The real-time attitude and position data was replaced with processed SBET data (described above), sound velocity corrections were applied, and the total propagated uncertainty (TPU) for each sounding was estimated using Caris tools.

Digital Elevation Model Production

The DEM produced in this work was derived solely from the bathymetric data collected by the USGS during field activity S-05-12-SC. Field sheets were created within CARIS to encompass the survey area, and a CARIS Swath Angle BASE (bathymetry with associated statistical error) surface was created at 2-m resolution for water depth less than 100 m and 4-m resolution for water depths greater than 100 m.

Survey lines were filtered to remove adjacent line data from nadir gaps. The subset editor was used to clean artifacts and other unwanted soundings. The binned data were exported as an ASCII table along with calculations of the bin standard deviation (of all soundings within the 2 by 2 m and 4 by 4 m cell spacings) and the sounding density.

To convert the data from ITRF2000 (also known as WGS84 G1150) ellipsoid heights to orthometric heights on NAD83 (CORS96)/NAVD88, the CARIS gridded data was exported as an ASCII table. The data was then transformed from the ITRF2000 ellipsoid to the NAD83 (CORS96) ellipsoid using a 14-point Helmert transformation and the parameterization described by Soler and Snay (2004) with the command line tool CS2CS in the Proj4 library (http://trac.osgeo.org/proj/). The parameters were calculated for an epoch date of 2010.1548 as shown in table 2. The conversion from WGS84 (G1150)/ITRF2000 to NAD83 (CORS96) shifts the data about 1.2 m to the east, 0.50 m to the south, and 0.60 m in elevation.

The vertical datum was transformed from NAD83(CORS96) ellipsoid heights to NAVD88 orthometric heights using the Geoid12 (National Geodetic Survey, 2012) average offset of 35.44 m. 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) DEM were exported in ESRII ASCII GRID (.ASC) format. Horizontal accuracy is on the order of 2 meters owing to transformations and grid- cell size.

Bathymetry data were then imported into ArcMap 10.0, where the 4 m by 4 m grid was added to the 2 m by 2 m grid using ArcMap's Mosaic tool, resulting in a single raster with 2 m resolution for depths less than 100 m and 4-m resolution for depths greater than 100 m. Proper cell alignment was accomplished by applying the nearest neighbor resampling algorithm to the 4 m grid during the mosaicking process. This entire raster was interpolated using the ArcMap's FocalMean function, with one iteration of a 3 cell by 3 cell rectangular focal mean calculated to fill data gaps and provide minor smoothing.

¹Note that the Proj4 program cs2cs reverses the sign of the rotation parameters from the Soler and Snay (2004) algorithm.

Backscatter Image Production

Acoustic backscatter data were processed using Fledermaus (QPS) FMGeocoder software package (version 7.3.2). Survey-line bathymetry data were exported from the Caris HIPS and SIPS (version 7.1) acquisition software as GSF files. These line files were paired with the original backscatter lines files (s7K) and imported into the FMGeocoder software. Each line file was radiometrically corrected and adjusted for angle varying gain (AVG) with the "flat" option with a window size of 30. All processed line files were merged together into one overall 2-m resolution backscatter mosaic. The processed backscatter dB values for a number of lines were adjusted using the backscatter adjustment tool to better match surrounding backscatter dB values. This tool allows the user to manually adjust dB values over entire lines. Often, the dB values within a line changed abruptly causing the mosaic to look patchy. Because of this manual adjustment process and abrupt changes in dB values, the backscatter mosaic may be more useful for visual interpretations rather than for empirical characterizations that compare pixel values over the entire mosaic. Once finalized, the backscatter mosaic was exported as a geoTIFF, imported in ESRI ArcGIS, and converted to a grid.

Estimates of Bathymetric Uncertainty

For flat parts of the seafloor, the standard deviation of sounding elevations within a specific cell spacing is a good measure of the precision of the sonar measurements. This is not true in areas where the seafloor is variable or steep; in these areas the standard deviation reflects natural variation rather than sonar measurement uncertainty. Each survey area discussed below includes two plots of the within-cell standard deviations. The first plot is a simple histogram of the standard deviations. The second is a plan-view map of the standard deviations across the selected survey area. These absolute numbers are a good indication of the distribution of uncertainty in bathymetric soundings; however, uncertainty naturally increases with range from the system (that is, with depth), so a measure of survey reliability that accounts for water depth as a factor is also important. The International Hydrographic Organization (IHO) standards described below provide such a metric by using depth below the transducer as a proxy for distance.¹

The IHO defines several survey orders based on a combination of coverage, depth, and accuracy (International Hydrographic Organization, 2008). The IHO defines maximum allowable total vertical uncertainty (TVU) using a depth-dependent formula with two additional variables as defined below (from International Hydrographic Organization, 2008):

¹References to IHO survey standards are for comparison purposes only. The USGS collects bathymetry for scientific use. The USGS does not certify that these data meet U.S. or International standards for use in nautical charting applications or for safety of navigation. Data described in this report is NOT FOR NAVIGATION.

where:

a represents that part of the uncertainty that does not vary with depth, b represents that part of the uncertainty that varies with depth, and d is the depth.

IHO standards require a 95-percent confidence level, defined as 1.96 x the standard deviation of sounding uncertainty. IHO survey orders use the following values as minimums for their survey orders (note that descriptions are generalized and order 1 and 1a are combined because they have the same values for minimum TVU):

If we assume that the elevation uncertainty in bathymetric soundings is normally distributed, we can estimate the total vertical uncertainty (TVU) in an elevation cell at the 95-percent level using:

where σ_(x,y) is the standard deviation of a cell located at coordinate (x, y). By comparing the calculated values from equation 2 against the standardized TVU thresholds represented by equation 1, we have an objective measure of the quality of the bathymetric surface.

The survey area described in the following section has a plot with the calculated TVU values (equation 2) for a representative subsample of the survey as a function of water depth. Plots include lines indicating the IHO thresholds for special-order, first-order, and second-order surveys derived from equation 1.