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Matthias Bobzien, Axes Systems AG Ingo Petzold, University of Zurich

ICC 2007, Moscow, Russia Automated Derivation of a 1:300 000 Topographic Map from Swiss DLM VECTOR 200. Matthias Bobzien, Axes Systems AG Ingo Petzold, University of Zurich Dirk Burghardt, University of Zurich. Overview. Context / Introduction Derivation of DCM300

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Matthias Bobzien, Axes Systems AG Ingo Petzold, University of Zurich

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  1. ICC 2007, Moscow, Russia Automated Derivation of a 1:300 000 Topographic Map from Swiss DLM VECTOR 200 Matthias Bobzien, Axes Systems AG Ingo Petzold, University of Zurich Dirk Burghardt, University of Zurich ICC 2007, Moscow, 5.-10. Aug. 2007

  2. Overview • Context / Introduction • Derivation of DCM300 • Perspective: Derivation of DCM25 • Conclusion ICC 2007, Moscow, 5.-10. Aug. 2007

  3. Context / Introduction OPTINA-LK Generali- sation DCM 300 MRDB Vector200 Vector200Karto swisstopo’s project OPTINA-LK Feasabilitystudy ICC 2007, Moscow, 5.-10. Aug. 2007

  4. Context / Introduction OPTINA-LK Generali- sation DCM 300 MRDB Vector200 Vector200Karto Generali- sation DCM 25 MRDB TLM TLMKarto swisstopo’s project OPTINA-LK Feasabilitystudy RealisationJan´08 ICC 2007, Moscow, 5.-10. Aug. 2007

  5. Source Data DLM VECTOR200 • digitized from topographic map 1:200'000 • 31 feature classes, 6 topics: • Transportation • Hydrography • Landcover • Buildings • POI • Boundaries • Manually thinned for derivation of DCM300 ICC 2007, Moscow, 5.-10. Aug. 2007

  6. Source Data DLM VECTOR200, sample 1 (mountains): ICC 2007, Moscow, 5.-10. Aug. 2007

  7. Source Data DLM VECTOR200, sample 2 (hills / lake): ICC 2007, Moscow, 5.-10. Aug. 2007

  8. Target Data DCM300 • Digital Cartographic Model for topographic map 1:300'000 • ~40 feature classes (VECTOR200: 31) • Due to more detailed variations, e.g.line symbolisation of roads  Two major parts of processing: • Reclassification • Cartographic Generalisation ICC 2007, Moscow, 5.-10. Aug. 2007

  9. Reclassification FC FC FC FC Reclassification / Model Transformation: m:n relation + Attribute Transformation • Transformation Rules, near Prolog Syntax e.g. road:use:tunnel  road:main AND construct == 3 ICC 2007, Moscow, 5.-10. Aug. 2007

  10. Reclassification Rules definition through GUI: ICC 2007, Moscow, 5.-10. Aug. 2007

  11. Cartographic Generalisation Generalisation Operators used: • Selection • Through feature size • Displacement • Mainly between Road/Railway/River • Parameters: Stiffness (e.g. Major Road or River) • Self-Displacement (e.g. narrow slopes) • Simplification: Variant of Douglas-Peucker • Topology preservant • Connectivity preservant ICC 2007, Moscow, 5.-10. Aug. 2007

  12. Workflow Suitable workflow was compiled after a seriesof tests: • Model transformation • De-selection • Displacement of line features • Line Simplification • Area Simplification ICC 2007, Moscow, 5.-10. Aug. 2007

  13. Examples Sample 1 (mountains): VECTOR200 ICC 2007, Moscow, 5.-10. Aug. 2007

  14. Examples Sample 1 (mountains): DCM300 after MT: ICC 2007, Moscow, 5.-10. Aug. 2007

  15. Examples Sample 1 (mountains): DCM300 after Gen. ICC 2007, Moscow, 5.-10. Aug. 2007

  16. Examples Sample 2 (hills / lake): VECTOR200 ICC 2007, Moscow, 5.-10. Aug. 2007

  17. Examples Sample 2 (hills / lake): DCM300 after MT: ICC 2007, Moscow, 5.-10. Aug. 2007

  18. Examples Sample 2 (hills / lake): DCM300 after Gen. ICC 2007, Moscow, 5.-10. Aug. 2007

  19. Examples Central Switzerland: DCM300 after Gen. ICC 2007, Moscow, 5.-10. Aug. 2007

  20. Context / Introduction OPTINA-LK Generali- sation DCM 300 MRDB Vector200 Vector200Karto Generali- sation DCM 25 MRDB TLM TLMKarto swisstopo’s project OPTINA-LK Feasabilitystudy RealisationJan´08 ICC 2007, Moscow, 5.-10. Aug. 2007

  21. Derivation of DCM25 Source: • Topographic Landscape Model (TLM) • Newly created, currently built up • Only sample data • Basis for maps 1:25K, 1:50K, 1:100K Target: • Digital Cartographic Model DCM25 • Basis for map 1:25K ICC 2007, Moscow, 5.-10. Aug. 2007

  22. Derivation of DCM25 Comparison to DCM300 : • Bigger amount of data • New feature classes (~220) • More generalisation operators needed • Area coverage, to be maintained • Full topology, to be maintained • Need for automated update mechanism ICC 2007, Moscow, 5.-10. Aug. 2007

  23. Derivation of DCM25 Main components of new system: • Workflow Management • New generalisation operators • Partitioning and Generalisation Zones • Horizontal Relations • Automated Incremental Updating ICC 2007, Moscow, 5.-10. Aug. 2007

  24. Workflow Management Workflow Editor: • Define workflows graphically Workflow Engine: • Execute workflow Characteristics of architecture: • Sequences • Sub-Workflows • Branches, concurrent processes • Loops • Connection to Generalisation Services ICC 2007, Moscow, 5.-10. Aug. 2007

  25. Generalisation operators New generalisation operators (compared to DCM300), most already implemented: • Typification / of building alignments • Aggregation • Amalgamation • Merge • Building simplification • Geometry type change • Various special operators ICC 2007, Moscow, 5.-10. Aug. 2007

  26. Partitioning / GenZones Partitioning: handling of large amount of data • Trans-Hydro-Graph • Density analysis, e.g. building density • City / residential zone / rural area • Pre-defined regions • Manual partitioning Generalisation Zones: Effect on Parameters • Urban / Rural • Alpine / Hilly data driven process driven (top-down) ICC 2007, Moscow, 5.-10. Aug. 2007

  27. Horizontal Relations Allow representation of relationships between features within one resolution trans-hydro-graph originalsituation topology nearness buildingalignments ICC 2007, Moscow, 5.-10. Aug. 2007

  28. Conclusion • swisstopo´s OPTINA LK • Derivation of DCM300: • Feasability study • Accomplished • Derivation of DCM25 • Productive System • Realisation Jan´08 Thank you! ICC 2007, Moscow, 5.-10. Aug. 2007

  29. Incremental Updating a a' UR UR Construction GR GR GR Re-Generalisation b b' UR Two Approaches: Re-Generalisation and Construction (see ICC 2005) Re-Generalisation Construction Original data Updated data Original data Updated data a a' ungener-alised b b' generalised ICC 2007, Moscow, 5.-10. Aug. 2007

  30. Relation modeling object-oriented model ICC 2007, Moscow, 5.-10. Aug. 2007

  31. Relation modeling object-oriented model ICC 2007, Moscow, 5.-10. Aug. 2007

  32. Relation modeling object-oriented model ICC 2007, Moscow, 5.-10. Aug. 2007

  33. Relation modeling object-oriented model ICC 2007, Moscow, 5.-10. Aug. 2007

  34. Relation modeling object-oriented model ICC 2007, Moscow, 5.-10. Aug. 2007

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