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Seabed image processing and datacleaning of the EM 3002 Common Data Set

Seabed image processing and datacleaning of the EM 3002 Common Data Set. Berit Horvei, Project Manager, SW Hydrography, Subsea Division. Outline. Data collection Tide / realtime heave Sound speed variation Seabed Image processing Datacleaning. Data collection. R/V Coastal Surveyor

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Seabed image processing and datacleaning of the EM 3002 Common Data Set

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  1. Seabed image processing and datacleaning of the EM 3002 Common Data Set Berit Horvei, Project Manager, SW Hydrography, Subsea Division WORLD CLASS – through people, technology and dedication

  2. Outline • Data collection • Tide / realtime heave • Sound speed variation • Seabed Image processing • Datacleaning

  3. Data collection • R/V Coastal Surveyor • EM 3002 D mounted to the existing ram system onboard • All other sensors supplied by UNH • Used RTK • 3 ½ Day with surveying

  4. Tide / realtime heave • Problems with realtime heave • Measured tide from NOAA homepage. • Height values extracted in Neptune • Established modified tide values

  5. Real time heave in the data  Modified tide file 1 m corridor

  6. Sound speed at transducer • Gridded measured sound speed at transducer head. • Small part(red) with wrong sound speed.

  7. Seabed image processing • Seabed image datagram, corrected for incidence angle • Backscatter, one value / beam

  8. Seabed image processing • Seabed image data gridded with a higher resolution than the depth values. • Overlay on top of the ordinary grid

  9. Seabed image processing • Seabed image data • Backscatter values gridded

  10. Seabed image processing

  11. Seabed image processing

  12. Datacleaning • Line based: Looks at every depth in the current ping. Removes time- and overhangs errors. • Grid based: Uses the Tukey-algorithm to construct a curved surface that fits as good as possible to most of the depths in the cell unit. Does cell splitting and merging to find best possible cell size first. Reconsiders all depths from previous lines every time the same geographical area is processed. Uses statistics to remove spikes based on standard deviation, but can also use grazing angle and calculated error estimates for each depth to flag out depths.

  13. Datacleaning • Raw data gridded • Selected area where the sound speed profile created problems.

  14. Datacleaning • Data cleaned in Neptune. Removed on beam angle, manual inspection and descision • xyz-data from Neptune is gridded in SIS

  15. Datacleaning • Residue standard deviation rule. • Noise removed, but effect of sound speed still visible.

  16. Datacleaning • Residue std. rule • Point data. Red invalid points. Blue valid points.

  17. Datacleaning • Grazing angle rule • For each depth the angle between the beam and the bottom surface is calculated.

  18. Datacleaning • Grazing angle rule • Point data. Red invalid points. Blue valid points.

  19. Datacleaning • Upper left, raw data • Upper right, xyz data, cleaned in Neptune • Lower left, standard deviation rule • Lower right, grazing angle rule

  20. Summary • Tide / realtime heave • Sound speed variation • Seabed Image processing • Datacleaning

  21. Kongsberg Maritime

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