Uncertainty Management and New Trends in Data Processing for Hydrography

1. Uncertainty Management and New Trends in Data Processing for Hydrography 2 - Uncertainty overview Definition of terms List of emerging trends Dave Wells Uncertainty overview

2. Defining Terms • Quality • Standards • Uncertainty and 3 types of uncertainty • Uncertainty management Uncertainty overview

3. Hydrographic data quality • Defined by two attributes • Coverage: data density & redundancy • Uncertainty: new term conveying the meaning of both “errors” (negative connotation) and “accuracy” (positive connotation) • Quality control: procedures to modify coverage and uncertainty results in advance or in real time (or while the data acquisition is still underway) • Quality assurance: post-survey assessment of coverage and uncertainty • Quality is usually classified as acceptable / unacceptable by comparison to accepted quality Standards Uncertainty overview

4. Standards • The word “standard” implies something which can be used as a basis for comparison, such as a model or a set of rules, or an authorized measure of some kind. • Along these lines, the International Organization for Standards (ISO) defines the term “standards” as • Rules, guidelines, and definitions of characteristics, which ensure that materials, products, processes and services are fit for their intended purposes. Uncertainty overview

5. “Fit for intended use” • Data must support “informed decision making” for each intended use • This requires data coverage and data uncertainty management strategies • Uncertainty management depends upon data redundancy Uncertainty overview

6. Uncertainty:axioms of measurements • No measurement is exact • Every measurement contains uncertainty • True value of a measurement is never known • Exact uncertainty present is never known Uncertainty overview

7. Uncertainty types • Accidental uncertainty • Mistakes, blunders • Eliminate by searching for outliers • Systematic uncertainty • Controlled by mathematical and physical causes • Detect by looking for “signatures” or “artifacts” • Random uncertainty • What’s left after “data cleaning” • (removing accidents & systematic uncertainty) • May include small accidental uncertainties & systematic uncertainties which were not removed during data cleaning. Uncertainty overview

8. VIM and GUM: new (1980+) ideas about expressing uncertainty • VIM = International Vocabulary of basic and general terms in metrology, 2nd ed (1993) • GUM = Guide to the expression of uncertainty in measurement, corrected ed (1995) • U.S. Guide = ANSI/NCSL Z540-2-1997 is identical to GUM, except swapping “.” and “,” as decimal markers, and Webster vs Oxford spelling. • Taylor & Kuyatt (1994) “Guidelines for evaluating and expressing the uncertainty of NIST measurement results” NIST Technical Note 1297 • [free download at http://physics.nist.gov/cuu/Uncertainty/] Uncertainty overview

9. What’s new about GUM? • Traditional ideas: • Reported uncertainties should be safe & conservative • Random and systematic uncertainties are fundamentally different, and should be reported separately • GUM: • Reported uncertainties should be realistic • There is no inherent different between uncertainty components caused by random and systematic effects • Result: • Report “combined standard uncertainty”, derived from both random and (residual) systematic effects Uncertainty overview

10. Hydrographic uncertainty management steps • Specification: What decisions are based on results from a hydrographic survey? What 95% confidence level performance do these decisions require? • Design: Select equipment, survey procedures and data cleaning methods which will likely meet the specification. • Assurance: Include redundancy and calibration procedures to permit assessing actual uncertainties and 95% confidence regions. • Presentation: Present uncertainty results in an easily understood way to those making decisions based on hydrographic survey results. Big difference between legacy and high-density data. Uncertainty overview

11. Emerging uncertainty management trends • High density data (multibeam and LIDAR) • Moving from uncertainty attribution of surveys to attributing data points - Brian • Higher emphasis on maintaining appropriate metadata • Evolving performance standards - Doug, Jerry & Peter • Tools for uncertainty monitoring / classifying / attributing & remediating - Venders • Awareness of need to better communicate uncertainty information to end users (decision makers) - Lee Uncertainty overview

12. The Hare-Calder-Smith method to represent uncertainty • 1 (Hare - TPE) Compute 3D uncertainties for every depth data point, using theoretical or empirical models for sensor errors. • 2 (Calder - CUBE) Propagate depths & uncertainties to nodes. Allow alternative hypotheses. Use several “disambiguation” metrics. • 3 (Smith - Nav Surface) Maintain rare “golden” shoal depths. Defocus shoals to represent georef uncertainty. Generalize by 3D double-buffering. Uncertainty overview

13. ISO/TC 211 Olaf Østensen, Chairman of ISO/TC 211, Bangkok, 2002-05-22 The goal of ISO/TC 211... • ... is to develop a family of international standards that will • support understanding and usage of geographic information • increase availability, access, integration, and sharing of geographic information • enableinter-operability of geospatially enabled computer systems • ease establishment of geospatial infrastructures on local, regional and global level Uncertainty overview

14. ISO/TC 211 <http://www.isotc211.org/pow.htm> as of 12 December 2003 TC211 standards: Final & Draft ISO 19101:2002 Reference model ISO 19101-2 Reference model - imagery ISO 19103 Conceptual schema language ISO 19104 Terminology ISO 19105:2000 Conformance and testing ISO 19106:2004 Profiles ISO 19107:2003 Spatial schema ISO 19108:2002 Temporal schema ISO 19109 Rules for application schema ISO 19110 Feature cataloguing methodology ISO 19111:2003 Spatial ref by coordinates ISO 19112:2003 Spatial ref by geographic id ISO 19113:2002 Quality principles ISO 19114:2003 Quality evaluation procedures ISO 19115:2003 Metadata ISO 19115-2 Metadata - imagery ISO 19116:2004 Positioning services ISO 19117 Portrayal ISO 19118 Encoding ISO 19119 Services TR 19120:2001 Functional standards TR 19121:2000 Imagery & gridded data TR 19122 Qualifications & certification of personnel ISO 19123 Schema for coverage geometry & functions Rev 19124 Imagery & gridded data components ISO 19125:2004 Simple feature access – Part 1-3 ISO 19126 Profile - FACC Data Dictionary ISO 19127 Geodetic codes and parameters ISO 19128 Web Map Server Interface ISO 19129 Imagery, gridded & coverage data framework ISO 19130 Data model for imagery & gridded data ISO 19131 Data product specification Rev 19132 Location based services (LBS) stds ISO 19133 LBS tracking & navigation ISO 19134 Multimodal LBS for routing & nav ISO 19135 Registration of geographic information ISO 19136 Geography Markup Language (GML) ISO 19137 Generally used spatial schema profiles ISO 19138 Data quality measures ISO 19139 Metadata implementation ISO 19140 Technical amendments to 191xx family Uncertainty overview

15. ISO TC211 workplan Standards finalized per year as of 22 Oct 2004(work began in August 1995) Uncertainty overview

16. S44 - Fourth EditionIHO standards for hydrographic surveys • Working Group established in 1993. Meetings in 1994 and 1997. Eleven countries represented. • Standards for future data collection, for diverse purposes (requiring up-to-date, detailed, reliable, digital data) • Previously S44 based on specified scale & draughting skill. This edition based on error budgets & intended uses. • Emphasizes need for determining and recording depth and position uncertainties (based on redundancy), as well as values. • Specifically addresses use of multibeam, sweep, and LIDAR Uncertainty overview

17. S44 quality factors • Depth measurement uncertainty • Bathymetric model uncertainty • Target detection uncertainty • Spatial referencing uncertainty for depths • Spatial referencing uncertainty for navaids and other features • Tide and tidal stream uncertainty. Uncertainty overview

18. S44 responsibilities left to each HO • Implementing - S44 are performance standards. HOs specify methods. • Legacy Data - specify QA estimation methods • Full bottom search - Define maximum depth requirement • Depth uncertainty - specify & test method for combining uncertainty contributions • Metadata standards - HO to develop & document • Doubtful data - decide whether to retain when not found in search Uncertainty overview

19. Summary of all depth uncertainty standards Uncertainty overview

20. S-44 Fifth Edition • 29Apr04 Rob Ward proposed new edition of S-44 to: • Provide greater clarity in designating nature / size of “targets” • Take a more realistic view of contemporary technological capability • Add metadata & data quality attribution standards, both for nautical charting (e.g. ZOCs) & for more detailed GIS analysis • Include input from wider range of stakeholders (academia, manufacturers, surveyors) • Update section on “Classification criteria for deep ocean soundings” • 26Oct04 14 members nominated to new committee • 10Dec04 “observers” from academia & industry nominated by IHO member states Uncertainty overview

21. Representing uncertainty on legacy charts • Possibilities: • No information provided / available • Source Diagram (SD) describes parameters of the field survey (e.g. date, line spacing, agency, depth sensor, georeferencing sensor, etc.) • Reliability Diagram (RD) advises on preferred areas for navigation, and provides uncertainty assessment (e.g. sounding accuracy, line spacing, survey classification - controlled, lead-line, sounder, shoals examined, sonar swept, etc.) Uncertainty overview

22. Model Source Diagram IHB M4 Uncertainty overview

23. Model Reliability Diagram IHB M4 Uncertainty overview