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CONFLATION: EDGEMATCHING TOOLS AND WORKFLOWS

CONFLATION: EDGEMATCHING TOOLS AND WORKFLOWS. Dan Lee dlee@esri.com. Agenda. Conflation overview and geoprocessing tools Edge Matching Workflows Demo Conclusions and Future Work. Conflation Overview and Geoprocessing Tools. TW session (this morning):

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CONFLATION: EDGEMATCHING TOOLS AND WORKFLOWS

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  1. CONFLATION: EDGEMATCHING TOOLS AND WORKFLOWS Dan Lee dlee@esri.com

  2. Agenda Conflation overview and geoprocessing tools Edge Matching Workflows • Demo Conclusions and Future Work

  3. Conflation Overview and Geoprocessing Tools TW session (this morning): Introduction to Geoprocessing Conflation Tools and Workflows

  4. When using multi-source spatial data together Common obstacles in analysis and mapping: • Spatial and attribute inconsistency caused by differences in data collection and modeling • High cost to fix the problems Adjacent datasets Overlapping datasets

  5. Conflation reconciles multi-source datasets and optimizes data quality and usability Conflation involves the process of： • Identifying corresponding features, also known as feature matching(FM) • Making spatial adjustment and attribute transfer • Combining matched and unmatched features into one unified dataset with the optimal accuracy, completeness, consistency, and integrity • Resolving conflicts and connection issues among adjacent datasets, also known as edge matching, to ensure seamless data coverage Long-term benefits: • No longer living with various imperfect datasets • More confidence in reliable analysis and high quality mapping

  6. Have you used these tools in ArcMap? Geoprocessing tools Develop highly automated tools in Geoprocessing framework • Starting with linear features (roads, parcel lines, etc.) • Aiming at high feature matching accuracy (not promising 100%) • Providing information to facilitate post-processing Build workflows In ArcGIS 10.4.1 and Pro 1.3

  7. Edge matching (EM) tools for adjacent datasets Based on proximity, topology, and continuity analysis,as well as attributes information Generate Edgematch Links (GEL) • From source features to adjacent features Followed by Edgematch Features (EF) • Connects features guided by the established links GEL EF

  8. Options of connecting features

  9. Conceptual workflow

  10. Edgematching of adjacent datasets Goal - make two adjacent datasets connect Source features Together Adjacent features

  11. Results Move endpoint

  12. Edge Matching Workflows

  13. Three components in conflation workflows Preprocessing Conflation and evaluation Postprocessing • Conflation tools • Workflow tools • In same projection • Data validation • Selection of relevant features • Queued review • Interactive editing

  14. Supplemental tools and guidelines for download http://www.arcgis.com/home/item.html?id=36961cde1b074f1f944758f6abec87cc You can also search by “conflation” at arcgis.com to find the download. Improved toolbar and new tools are coming soon.

  15. Workflow strategy Demo Real world scenario

  16. Breakdown of the conceptual workflow into sub-steps Step7 Step6a QA Step6b

  17. Demo data overview Two road datasets (an area in Alabama): • EdgeRoads – 7576 features • GISRoads – 3634 features Both datasets: • Contain roads that are within 1 km to borders • Have inconsistent road names

  18. GEL result Generated 454 links; midpoints of links were created for visualization purpose. Borders were not in the process, but displayed for reference.

  19. EM_CONF in output • 100 (matched with no ambiguity) • 50 (spatially matched with unmatched attributes) • < 50 (spatially matched with some ambiguity and weak continuity)

  20. GEL evaluation results EM_CONF < 33: 134 links Intersecting links: 33 locations Potential missing links: 62 source dangle locations It’s time for inspection …

  21. Inspection and editing of edgematch links Reviewed: • 33 locations of intersecting links NEAR_DIST >= 0 • 98 low EM_CONF links (EM_CONF < 33) AND (REV_FLAG IS NULL) • 62 source dangle locations (near links) Summary: • 388 (~85%) of total 459 links were good (54 were flagged for recheck) • 71 (~15%) of total links were modified, removed, or added

  22. What happened to the SRC_FID and TGT_FID of the added or modified links? Ready for edgematching …

  23. Edgematch result Review flagged locations …

  24. Edgematching of adjacent datasets workflow completed! Automated processing Interactive processing (not counting final review)

  25. Thanks to: • Department of Public Works (DPW), Los Angeles County, USA. • Resource Management Service, LLC, Birmingham, AL, USA. • All others who supported us along the way. Conclusions andFuture Work

  26. Edge matching can be done more efficiently now It takes a workflow: • Use the best practice in preprocessing. • Run automated tools to obtain highly accurate results and evaluation information. • Interactively review and edit the results. The time is worth-spending.

  27. Consider conflation a higher priority Study the tools and workflows; understand the results • Start with small test areas Customize the workflows for your organizations • Improve data quality and usability • Bring new live and value to your data Work with broader communities • Data sharing and collaboration • Seamless analysis and mapping Please send us your feedbacks 

  28. Our future work Align Features New tools and enhancements • Align Features tool • Better edgematch links Integrated review and editing • Plug-in to the Universal Error Inspector (ArcGIS Pro future release) Formalization of workflows • Common scenarios oriented • Other feature types • Contextual conflation (spatially related features) Please send us your use cases and requirements 

  29. Recent papers • Baella B, Lee D, Lleopart A, Pla M (2014) ICGC MRDB for topographic data: first steps in the implementation, The 17th ICA Generalization Workshop, 2014, Vienna, Austria. http://generalisation.icaci.org/images/files/workshop/workshop2014/genemr2014_submission_8.pdf • Lee D (2015) Using Conflation for Keeping Data Harmonized and Up-to-date, to be presented at the ICA-ISPRS Workshop on Generalisation and Multiple Representation, 2015, Rio de Janeiro, Brazil • Lee D, Yang W, Ahmed N (2014) Conflation in Geoprocessing Framework - Case Studies, GEOProcessing, 2014, Barcelona, Spain. http://goo.gl/iOoSGV • Lee D, Yang W, Ahmed N (2015) Improving Cross-border Data Reliability Through Edgematching, to be presented at The 27th International Cartographic Conference, 2015, Rio de Janeiro, Brazil • Yang W, Lee D, and Ahmed N, “Pattern Based Feature Matching for Geospatial Data Conflation”, GEOProcessing, 2014, Barcelona, Spain. http://goo.gl/JKGJbo

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