The Progression of Multi-Dimensional Water Column Analysis

Transcription

1 The Progression of Multi-Dimensional Water Column Analysis Authors: Corey Collins and Andy Hoggarth Fredericton Canada Heeswijk The Netherlands Washington DC United States Adelaide Australia

2 Outline Introduction Water Column Processing in CARIS HIPS Reading Water Column Data Support in Swath Editor Use case 1: Gas seep investigation Support in Subset Editor Use case 2: Least depth detection on wreck Ray Tracing the Water Column Data Further processing of Additional Bathymetry Working Efficiently with Water Column Data Conclusions

3 Why Water Column Data? Many Multibeam Sonars can record Water Column data Data useful for a broad audience Hydrography Oceanography Risk / Hazard management Fisheries Defence Can provide additional information about the submarine environment

4 Water Column Processing in CARIS HIPS Goal was to tightly integrate into standard workflow Large and complex initiative Broken into 5 phases 1. Read water column data 2. Display WCI data in Swath Editor 3. Display WCI data in Subset Editor 4. Ray-tracing water column data 5. Least depth analysis, intelligent filtering, volume calculations etc. delivered in coming in 8.0 (Q1 2013) post 8.0 Current support for Kongsberg (*.wcd and*.all) and Reson (*.s7k) sonars, would like to support more..

5 Reading WCI Data It s BIG. Efficient access and display Accessed directly from raw data file Called on demand controlled by extents of views in HIPS Editors Raw data files referenced for access Background threading.all/.wcd.s7k HIPS Swath Editor Subset Editor

6 Support in the Swath Editor Display WCI data in Across and Along track views (X) Overlay Bottom Detection Assign Colour Map Filter based on intensity Enable Stacked View Review controls Add WCI points to Bathymetry (Y)

7 Use Case 1 WCI in Swath Editor Gas Seeps in St. John River, New Brunswick, Canada Across Track View of Seep

8 Isolating the Feature Stacked View (shine thru) Lasso Select Filtered by db range

9 Displaying the Results

10 Support in the Subset Editor Map the WCI into 3D space Using CSAR point cloud technology On the fly ray-tracing based on 1500 m/s SS Vertical adjustment e.g. Tide, waterline Filter WCI data Depth Intensity Minimum slant range Display Controls Colour by Attribute e.g. Intensity Toggle on / off WCI, Bathy, Additional bathymetry Add WCI points to Bathymetry

11 Use Case 2 WCI in Subset Editor GB Church Shipwreck, Vancouver Island, Canada Bathymetry in Subset Editor PlanView

12 Isolating the Missing Data Water Column data overlaid but filtered by minimum slant range Filtered by db range Lasso Select

13 Combining the Datasets Recompute BASE Surface Combined Bathymetry and Water Column in Subset Editor

14 Displaying the Results Additional Bathymetry and BASE Surface in 3D Window

15 Ray-Tracing Water Column Data in CARIS HIPS For Kongsberg Data Data is ray traced using Kongsberg SVC.dll if available If not available default is the UNB SVC algorithm Also applies Tide and VCF offsets e.g. waterline For Reson Data Data is ray traced using standard HIPS SVC algorithm Also applies Tide and VCF offsets e.g. waterline

16 Further Processing Possibilities for Additional Bathymetry Reject, Accept, Query points in Swath or Subset Editors Designate critical soundings Apply post processed motion data to it e.g. True Heave Compute TPU for the additional points Create BASE surfaces Run through CUBE Include in standard data exports In summary the same as standard bathymetry data

17 Working efficiently with Water Column Data Water Column data takes up a lot of disk space Kongsberg *.wcd data 4 to 6 times the size of bathy (3002, 2040) Reson *.s7k with water column has a larger ratio File size increases with water depth and number of beams 1. Read directly, don t convert 2. Distribute the processing over multiple threads or PC s 3. Determine db range in non geo-referenced views (2D) 4. Isolate the data you want to view in 3D using filters Minimum slant range, depth gate, db range 5. Only ray-trace the data you want to incorporate 6. Utilize Data Compression Techniques where possible

18 Conclusion Water Column data allows us to find out more information about the submarine environment Water Column data is large in size, but by incorporating portions of it we can potentially run fewer survey lines Additional uses of this data could provide further justification to conduct hydrographic surveys There s more work to be done especially in the area of intelligent filtering, which will provide additional usability

19 CARIS HIPS/SIPS Under New Management Burns Foster Jamie Parsons

20 References Hughes Clarke, J.E., Lamplugh, M., Czotter, K. (2006), Multibeam Water Column Imaging: Improved Wreck Least-Depth Determination. Presented at Canadian hydrographic Conference Hughes Clarke, J.E. (2006), Applications of Multibeam Water Column Imaging for Hydrographic Survey. The Hydrographic Journal April, Kongsberg, EM2040 Dataset (2011), Data provided courtesy of Canadian Hydrographic Service. Kongsberg, EM3002 Dataset (2006), Data provided courtesy of John Hughes Clarke, OMG UNB, Canada. Masry, M., Schwartzberg, P. (2009), Marine High Density Data Management and Visualization. Presented at the seminar for Management of massive point cloud data: wet and dry. November 26, Shallow Water Common Dataset (2012), Data collected for the 2012 Shallow Water Conference, February 2012.

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