31 March 2005Uncertainty overview1 of 72 Uncertainty Management and New Trends in Data Processing for Hydrography 2 - Uncertainty overview Definition of terms List of emerging trends Dave Wells

31 March 2005Uncertainty overview2 of 72 Defining Terms Quality Standards Uncertainty and 3 types of uncertainty Uncertainty management

31 March 2005Uncertainty overview3 of 72 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

31 March 2005Uncertainty overview4 of 72 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.

31 March 2005Uncertainty overview5 of 72 “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

31 March 2005Uncertainty overview6 of 72 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

31 March 2005Uncertainty overview7 of 72 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.

31 March 2005Uncertainty overview8 of 72 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 Z 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

31 March 2005Uncertainty overview9 of 72 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

31 March 2005Uncertainty overview10 of 72 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.

31 March 2005Uncertainty overview11 of 72 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

31 March 2005Uncertainty overview12 of 72 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.

31 March 2005Uncertainty overview13 of 72 ISO/TC 211 Geographic information/Geomatics … building the foundation of the geospatial infrastructure, brick by brick... ISO/TC 211 Olaf Østensen, Chairman of ISO/TC 211, Bangkok, Revenues in the traditional Geographic Information Systems market (GIS), for business support systems (BSS) and the emerging technology, location- based mobile services (LBMS), based on various sources.

31 March 2005Uncertainty overview14 of 72 The goal of ISO/TC 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 enable inter-operability of geospatially enabled computer systems ease establishment of geospatial infrastructures on local, regional and global level ISO/TC 211 Olaf Østensen, Chairman of ISO/TC 211, Bangkok,

31 March 2005Uncertainty overview15 of 72 ISO 19101:2002 Reference model ISO Reference model - imagery ISO Conceptual schema language ISO Terminology ISO 19105:2000 Conformance and testing ISO 19106:2004 Profiles ISO 19107:2003 Spatial schema ISO 19108:2002 Temporal schema ISO Rules for application schema ISO 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 Metadata - imagery ISO 19116:2004 Positioning services ISO Portrayal ISO Encoding ISO Services TR 19120:2001 Functional standards TR 19121:2000 Imagery & gridded data TR Qualifications & certification of personnel ISO Schema for coverage geometry & functions Rev Imagery & gridded data components ISO 19125:2004 Simple feature access – Part 1-3 ISO Profile - FACC Data Dictionary ISO Geodetic codes and parameters ISO Web Map Server Interface ISO Imagery, gridded & coverage data framework ISO Data model for imagery & gridded data ISO Data product specification Rev Location based services (LBS) stds ISO LBS tracking & navigation ISO Multimodal LBS for routing & nav ISO Registration of geographic information ISO Geography Markup Language (GML) ISO Generally used spatial schema profiles ISO Data quality measures ISO Metadata implementation ISO Technical amendments to 191xx family TC211 standards: Final & Draft ISO/TC 211 as of 12 December 2003

31 March 2005Uncertainty overview16 of 72 ISO TC211 workplan Standards finalized per year as of 22 Oct 2004 (work began in August 1995)

31 March 2005Uncertainty overview17 of 72 Released 7 January 2004 ISBN (Springer) 322 pages $129 Intended for those who want / need to Know more about GIS standards, and the role of the ISO in setting them Implement ISO191xx standards in software Understand the overall structure of ISO191xx standards Understand the rather abstract ISO191xx documents Contents: 1 Basics of standards 2 Geomatics standards 3 Detailed description of graphic standards 4 Liaison members of ISO/TC211 5 Applications 6 Annexes

31 March 2005Uncertainty overview18 of 72 S44 - Fourth Edition IHO standards for hydrographic surveys Working Group established in Meetings in 1994 and 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

31 March 2005Uncertainty overview19 of 72 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.

31 March 2005Uncertainty overview20 of 72 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

31 March 2005Uncertainty overview21 of 72 Summary of all depth uncertainty standards

31 March 2005Uncertainty overview22 of 72 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

31 March 2005Uncertainty overview23 of 72 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.)

31 March 2005Uncertainty overview24 of 72 Model Source Diagram IHB M4

31 March 2005Uncertainty overview25 of 72 Model Reliability Diagram IHB M4