Martin Davis, Technical Architect mbdavis@vividsolutions

1. Automated and Human-Assisted Conflation Using the JCS Conflation SuitePresented at GeoTec 2003Vancouver, BC Martin Davis, Technical Architect mbdavis@vividsolutions.com Conflation with JCS

2. Overview of Conflation • “Conflation” is a very broad term • Conflation problems need to be precisely defined in order to be automated • Conflation algorithms difficult to generalize • Still awaiting “Grand Unifying Theory” of conflation Conflation with JCS

3. Overview of ConflationTerminology • Matching – identifying features or data elements which represent the same real-world entity • Alignment – whether two features or data elements have coincident geometry • Adjustment – altering geometry or attributes of matched features to make them align • Reference –dataset to be conflated to • (usually of greater spatial accuracy) • Subject – dataset to be matched or adjusted Conflation with JCS

4. Overview of ConflationProblem Categorization • Horizontal – conflation between adjacent datasets • e.g. Boundary Alignment • Vertical – conflation between datasets covering the same area • e.g. Coverage Alignment, Road Network Matching • Internal – conflation between items in a single dataset • e.g. Coverage Cleaning Conflation with JCS

5. Overview of ConflationAutomated VS Human-Assisted • Automated • uses algorithm(s) to match and adjust features automatically. • May not be able to fix 100% of problems • Human-Assisted • use manual editing tools to adjust features • Assisted by automated tools to detect problems, perform precise adjustment Conflation with JCS

6. Overview of Conflation Workflow • Acquire Datasets • Data Preparation & Validation (QA) • Problem Detection and Visualization • Automated Conflation • Human-assisted Conflation (if necessary) • Persist Updated Data Conflation with JCS

7. The JCS Conflation Suite Project • Project sponsor: • Dr. Mark Sondheim - Base Mapping and Geomatic Services Branch, MSRM • With support from: • GeoConnections • Ministry of Sustainable Resource Management, Province of BC • Project Timeline • Initiated: March 2002 • Finish: ~March 2003 Conflation with JCS

8. The JCS Conflation Suite • Goals: • Address real-world conflation problems • Leverage existing spatial tools and modern software development techniques • Open development philosophy • Build toolbox for performing conflation • JCS written in 100% pure Java • JCS is Open Source (GPL license) Conflation with JCS

9. JCS Architecture • JCS provides: • API • GUI • Built using: • Java Topology Suite (JTS) • Unified Mapping Platform (JUMP) Conflation with JCS

10. JTS Topology Suite • Implementation of OpenGIS Consortium Simple Features Specification • Open-Source, 100% Java • Goals: • Fast, production quality • Robust • Explicit precision model Conflation with JCS

11. Spatial predicates (using Dimensionally Extended 9-Intersection Model) • Boolean operations, buffer, convex hull, centroid, etc. JTS Topology SuiteGeometry Model and Operations • Geometry model: Points, LineStrings, Polygons, collections Conflation with JCS

12. JUMP Unified Mapping Platform • 100% pure Java • Open Source (GPL license) • Both API and GUI • Goals: • Rich GUI environment for developing spatial algorithms, visualizing data and output • Interactive environment for supporting human-assisted spatial processes • Leverage capabilities of Java platform for spatial processing • Easily extensible Conflation with JCS

13. JUMP - API • Features with attributes and geometry • Feature Collections • Spatial Access Methods • Quadtree, STR-Tree, Binary Interval Tree • Warping • Affine Transform • Bilateral Interpolated Triangulation • Dataset I/O • Well Known Text, GML, ESRI Shapefile Conflation with JCS

14. JUMP Workbench • Multi-Window GUI • Supports multiple layers of spatial data; rich styling options • Provides GUI for JUMP API functions • Geometry & Attribute editing • Easily extensible via Plugin framework Conflation with JCS

15. Conflation in JCS Overview • Provides tools for: • Dataset QA • Problem detection • Automated Conflation • Human-assisted conflation (manual edits) • Kinds of conflation algorithms • Coverage Alignment • Road Network Matching Conflation with JCS

16. Coverage AlignmentProblem Subtypes • Boundary Alignment • e.g. Municipal Parcels • “Horizontal Conflation” • Coverage Cleaning • “Internal Conflation” • General Coverage Alignment • e.g. aligning suburb boundaries to parcels • “Vertical Conflation” Conflation with JCS

17. Coverage AlignmentAlgorithm • Key idea: Lines that are “close” should be identical • Match Line segments • Hausdorff distance < tolerance • Relative angle < tolerance • Adjust Vertices • Snap close vertices • Add or merge vertices if necessary • Heuristics: • Do not break topology • Minimize change to existing vertices Conflation with JCS

18. Coverage CleaningError Detection Conflation with JCS

19. Coverage CleaningAutomated Alignment Conflation with JCS

20. Coverage Cleaning QA of Automated Process Conflation with JCS

21. Coverage CleaningManual Tools – Vertex Snapping Conflation with JCS

22. Boundary AlignmentError Detection Conflation with JCS

23. Boundary AlignmentAutomated Conflation Conflation with JCS

24. General Coverage AlignmentError Detection Conflation with JCS

25. General Coverage Alignment Automated Conflation Conflation with JCS

26. Road Network MatchingProblem Example Conflation with JCS

27. Road Network MatchingAlgorithm • Match Nodes and Edges based on weighting • Node Match weight • Distance between nodes • Topology match between incident edges • Edge Match weight • Hausdorff distance between edges • Relative length of edges • For “straight edges”, relative angle Conflation with JCS

28. Road Network MatchingMatching & Visualization Conflation with JCS

29. Road Network MatchingWarping based on Matching Conflation with JCS

30. Further Development • New / improved conflation algorithms • Complete Road Network Matching tools • Improve Coverage Alignment algorithm • Alignment to natural boundaries • E.g. Admin Boundary / Heights-of-land • Stream Network matching (Refractions Research) • Additional JUMP functionality • Colour-theming by attribute • More flexible GML support • JTS improvements • Robustness of spatial functions, buffer Conflation with JCS