conflation with jcs automated and human-assisted conflation using the jcs conflation suite presented...
TRANSCRIPT
![Page 1: Conflation with JCS Automated and Human-Assisted Conflation Using the JCS Conflation Suite Presented at GeoTec 2003 Vancouver, BC Martin Davis, Technical](https://reader035.vdocuments.net/reader035/viewer/2022062515/56649cc05503460f94987a98/html5/thumbnails/1.jpg)
Conflation with JCS
Automated and Human-Assisted Conflation Using the JCS Conflation Suite
Presented at GeoTec 2003Vancouver, BC
Martin Davis, Technical Architect
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Conflation with JCS
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
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Conflation with JCS
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
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Conflation with JCS
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
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Conflation with JCS
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
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Conflation with JCS
Overview of Conflation Workflow
• Acquire Datasets• Data Preparation & Validation (QA)• Problem Detection and Visualization• Automated Conflation• Human-assisted Conflation (if
necessary)
• Persist Updated Data
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Conflation with JCS
The JCS Conflation Suite Project
• Project sponsor: Dr. Mark Sondheim - Base Mapping and
Geomatic Services Branch, MSRM
• With support from:GeoConnectionsMinistry of Sustainable Resource
Management, Province of BC
• Project Timeline Initiated: March 2002Finish: ~March 2003
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Conflation with JCS
The JCS Conflation Suite
• Goals:Address real-world conflation problemsLeverage existing spatial tools and modern
software development techniquesOpen development philosophy Build toolbox for performing conflation
• JCS written in 100% pure Java• JCS is Open Source (GPL license)
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Conflation with JCS
JCS Architecture
• JCS provides:APIGUI
• Built using: Java Topology Suite (JTS)Unified Mapping Platform (JUMP)
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Conflation with JCS
JTS Topology Suite
• Implementation of OpenGIS Consortium Simple Features Specification
• Open-Source, 100% Java• Goals:
Fast, production quality Robust Explicit precision model
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Conflation with JCS
JTS Topology SuiteGeometry Model and Operations
• Geometry model: Points, LineStrings, Polygons, collections
• Spatial predicates (using Dimensionally Extended 9-Intersection Model)
• Boolean operations, buffer, convex hull, centroid, etc.
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Conflation with JCS
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
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Conflation with JCS
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
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Conflation with JCS
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
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Conflation with JCS
Conflation in JCS Overview
• Provides tools for:Dataset QAProblem detectionAutomated ConflationHuman-assisted conflation (manual edits)
• Kinds of conflation algorithmsCoverage AlignmentRoad Network Matching
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Conflation with JCS
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”
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Conflation with JCS
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
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Conflation with JCS
Coverage CleaningError Detection
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Conflation with JCS
Coverage CleaningAutomated Alignment
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Conflation with JCS
Coverage Cleaning QA of Automated Process
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Conflation with JCS
Coverage CleaningManual Tools – Vertex Snapping
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Conflation with JCS
Boundary AlignmentError Detection
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Conflation with JCS
Boundary AlignmentAutomated Conflation
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Conflation with JCS
General Coverage AlignmentError Detection
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Conflation with JCS
General Coverage Alignment Automated Conflation
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Conflation with JCS
Road Network MatchingProblem Example
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Conflation with JCS
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
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Conflation with JCS
Road Network MatchingMatching & Visualization
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Conflation with JCS
Road Network MatchingWarping based on Matching
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Conflation with JCS
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