Navigation Surface and Uncertainty: A Brief Overview

1. Navigation Surface and Uncertainty:A Brief Overview Lee Alexander University of New Hampshire

2. What is a “Navigation Surface”? •  a new database approach for processing bathymetric data. • Developed at the University of New Hampshire by LT Shep Smith (NOAA) • a DTM model of the seafloor that is “optimized” for safety-of-navigation.

3. The Problem • Traditional data validation (tools and procedures) are overwhelmed by the volume of soundings associated with modern MB systems. • Cartographic processes are manually intensive and subjective. • Traditional products created are incompatible with the needs of other users of marine bathymetric information.

4. Smooth Sheet • Shoal Biased depths at spacing defined by scale (5mm) • Contours at rounding threshold, sometimes drawn by hand • Conflicting information has to be reconciled • Legal Record of Survey • Used for chart compilation Snow Passage Depth Plot H10949

5. Navigation Surface • A new technique that bypasses the rather subjective, “selected soundings” approach. • Instead, a statistical model is created directly from processed data . - The model is a “best estimate” of depths – not soundings.

6. “Navigation Surface” and Uncertainty • The model of the seafloor consists of a high-resolution bathymetric grid with an uncertainty value assigned to each node on the grid. • The model is then optimized to preserve the least depths over significant features. • For each node, an uncertainty value is computed which becomes an integral part of the model. • The distribution of the points around the mean is combined with the predicted uncertainty of each measurement to form an overall uncertainty model.

7. Survey Database Products Depths & Bathymetry Navigation Surface Other ENC Hydro Vector Database Nautical Charts Three Basic Steps

8. Navigation Surface: Concepts • A database of source bathymetry maintained at the highest resolution the data will support. • Meant to support multiple products (e.g., navigation, habitat, geological, environmental, military, etc. • Uses the best available data for the area --regardless of source • Utilizes a set of rules for automated product creation.

9. Creating a Navigation Surface Database • Basic Principle: populate the database with the highest resolution, reconciled surface model that the source measurements (survey data) can support. • High-res MB – resolution will be approx the footprint size of the sonar. • - a 1.5 degree sonar has a footprint of about 1m2 at 20m depth • - can produce a regular grid with uniform grid spacing • - grazing angle and slope are factors that must be considered (i.e., need CUBE) • Low density SB and lead-line – area between measurements is modeled based on a TIN

10. Navigation Surface Processing Pipeline Full Res. DTM Navigation Surface Database Modern Multibeam Merged DTM Dirty Data Deconflict Generalize to Scale CUBE SAIC 8125 Clean Data Estimate Uncertainty Weighted Grid H10763 Estimate Uncertainty H08090 TIN Grid Extract Cartography H03032 Sparse Data

11. Database Contents Source: LT Shep Smith

12. Low-Density Data Sources Source: LT Shep Smith

13. WHITING 8101 1950s Singlebeam RUDE 9003

14. Uncertainty Modeling • Traditionally, the measurement error of a given sounding is the value reported as the uncertainty of the depth. In other words: How good was that measurement? • But, what mariners really want to know is: How well is the depth known at this location?

15. When we shoal bias multibeam, we keep the least accurate measurements

16. Fundamental Process Goal • First: determine what is the true depth in the area of interest without any consideration of a final product, scale or ‘hydrographic’ concerns • - i.e., how well do we know that depth? • Then: make the appropriate products with due regard for the end-user requirements.

17. Uncertainty Modeling • Three basic methodologies: • Forward error • Backward error • Interpolation

18. Forward Error • When applied to high-density MB bathymetry, each depth is assigned a predicted error based on: • 1) the systems used to collect it • 2) environmental conditions at the time of the survey

19. Backward Error • Uses the standard error of the measurements around the weighted mean. • Limitation: difficult to distinguish between areas of steep slope, high seafloor irregularity, and high error.

20. Uncertainty for Interpolated Areas • Gaps between MB survey lines or SB soundings are a nagging concern. • Typically, uncertainty interpolation: • is related to the measurement uncertainty at the node where the measurement was made • increases as a function of the distance to the nearest measurement • is higher on a more irregular seafloor

21. Uncertainty Model of Clean Multibeam • The uncertainty of the node is the greater of: • -the average uncertainty of the measurements • the 95% bound of the distribution of the measurements around the mean. • Interpolated areas follow the sparse data rules • High uncertainty is expected on steep slopes due to horizontal error.

22. Other Types of Uncertainty • Time-Dependent – dynamic seafloor areas may require a “changeability coefficient” to be assigned at every node. • Superceding Data * – when superceding old data with new, some rules should be applied: • a model node with lower uncertainty supercedes one with greater • a newer node supercedes an older node • a shoaler node supercedes a deeper node • * Primarily applies to navigation products

23. Navigation Surface  Chart Product Generation • Three steps are involved: • Defocusing - apply the horizontal uncertainty of the model nodes to the model • - at each node, adjacent nodes are adjusted in the shoal direction if they are deeper or fall into the horizontal error circle of the node. • Generalization - for the intended product, use a “buffering” process • Extract Cartographic Objects – e.g., contours, depth areas, and selected soundings

24. Defocusing Properties • Least depths preserved on significant features • Horizontal error reflected in the surface • Generalized surface for smooth contour creation at the scale of the product

25. Defocusing for Horizontal Error Horizontal Error of Sounding Base Point Adjusted Point

26. Defocusing Concept Horizontal Uncertainty

27. Defocusing • Need to compensate for horizontal error • If the bottom is not flat, horizontal error implies vertical error • The greater the slope, the higher the potential error • Provides a better assessment slopes (absolute vs relative positioning)

28. CHS Pacific EM3000 – Esquimalt - 1m Surface defocused using 5m horizontal uncertainty estimate Defocusing (Horizontal Error) Source: “Total Propagated Error, BASE Surfaces and CARIS HIPS 5.4”, Lamey, B. et al., Proc. 3rd Int. Conf. On High-Resolution Surveys in Shallow Water, Sydney, Australia, 2003.

29. Raw 1m grid Provided by Shep Smith

30. Defocus 10m Provided by Shep Smith

31. Defocus 20m Provided by Shep Smith

32. Defocus 50m Provided by Shep Smith

33. Defocus 100m Provided by Shep Smith

34. Generalisation • - Composite surface has too much detail for cartographic work • - Need to remove ‘extraneous’ detail but still preserve shoal depths • Uses 3D Double-Buffering technique, which that is shoal preserving

35. Buffering • A new line is created a prescribed distance from the nearest point on the original line. When buffered back in the opposite direction, a generalized version of the original line is created that conforms to one edge (i.e., the seaward edge of the original line). • 3-D Buffering – a new surface is created a specified distance up from the original surface, then buffered back toward the original surface. • Net Result: honors the shoal surfaces, but smooth over small, regular depressions (e.g., troughs between sand waves)

36. Double-Buffering-2D • The blue line represents a contour • The green line is the seaward half of a buffer drawn around the contour • The red line is the result of buffering the green line back in the original direction

38. 3D Generalisation Source: “Management of Bathymetric Databases using BASE Surfaces”, Gourley, M. et al., Proc. 3rd Int. Conf. On High-Res. Survey in Shallow Water, Sydney, Australia, 2003.

39. 2m BASE Surface 4m Product Surface 1:20,000 10m Product Surface 1:50,000 3D Generalisation Source: “Total Propagated Error, BASE Surfaces and CARIS HIPS 5.4”, Lamey, B. et al., Proc. 3rd Int. Conf. On High-Resolution Surveys in Shallow Water, Sydney, Australia, 2003.

40. Navigation Surface: Implications • High data volume • Other uses of bathy data • Non-traditional sources of bathy data • Prioritization of survey effort • Field quality control • ENC production • Product uncertainty

41. High Data Volume • When processing high-density depth data, the current approach: each measurement evaluated as being good or bad (i.e., “cleaning”) • Of all cleaned soundings, the shoalest one is usually selected for a particular geographic area. • Depending on the type of survey, the ratio of selected soundings to all soundings can vary widely. • leadline surveys = 1:2 • multibeam surveys = 1:20,000 • Result: smooth sheet soundings from MB become biased toward accepted measurements containing the greatest error.

42. Other Uses for Bathymetric Data • Other users of bathy data have different requirements: - high spatial resolution - less concern about absolute depth with respect to datum than internal consistency - want gridded format • Traditional shoal-biasing and sounding suppression processes reduce the value of the data for other purposes (e.g., smooth sheet density vs. high-res bathy)

43. Smoothsheet Density Shoal-Biased Selected Soundings Reson 8101 at Survey Density (NOAA Ship WHITING)

44. Nav Surface  New Applications • Detailed DTMs increasingly used for: • seafloor classification • marine geology • fisheries habitat management • marine information objects (MIOs) • additional military layers (AMLs) • coastal zone management

45. Non-traditional Sources of Survey Data • Federal, state, commercial and academic institutions are collecting high-quality bathymetric data. • may be the “best data available”, but usually not acquired or processed to IHO standards. • HOs need to develop a process whereby this data could be used for charting purposes • to do so, the accuracy of the data must be assessed. • Navigation Surface provides a methodology for systematically tracking survey accuracy.

46. An Example • Research Institute conducts a high-res MB survey of a coastal area. • If tidal information was not applied, uncertainty could be increased to encompass the tidal range in the area. • If the resulting depth and uncertainty is adequate for the intended navigational purpose, and its accuracy is assessed and maintained as part of a master database, • Then this data should be sufficient for safe navigation.

47. Prioritization of Survey Effort • Survey effort is usually prioritized for areas where the current level of uncertainty is incompatible with current or proposed use. • - Currently, no systematic way of doing this. •  Using navigation surface as a database, surveys can be systematically prioritized for areas with: • - low under-keel clearances • - high uncertainty of depth estimates • - older data in areas with dynamic seabed • - known inconsistencies and large numbers of unresolved reported items

48. Field Quality Control • Using an uncertainty surface, hydrographers can optimize their time in the field by tuning their acquisition needs to meet the assigned standards. • systematically removing the outer beams of wide-swath multibeam systems, narrows the width of the swath by half. (practice is based on a worst-case scenario for accuracy of those outer beams) • With Navigation Surface, tracking the uncertainty of both of the measurement and the derived surface can result in using a larger swath during optimal conditions

49. Making Products • With a Navigation Surface database: • Each grid attributed with depth & uncertainty (i.e.,“CUBE-ed” • Grids de-conflicted to be consistent • Grids represent ‘best available information’ • Grids consistent products • Combine component grids to make one grid • Insure hydrographic safety in products • Ensure appropriate cartographic scale • Specialization occurs when a product is defined - not before • All data is retained at highest resolution

50. Application to Charting • Once the full-resolution depth surfaces and their associated uncertainties have been compiled, the database can be used to produce multiple products. • Basic Basic Task: generalize high-res bathy data to make it appropriate for display at desired scale for a specific product and navigation purpose. • To accomplish, a product generation process is required. • - Using the Navigation Surface approach, this is done at the model – not the cartographic level