Network conflation is a continuing necessity and difficult task for agencies using geo-referenced maps and databases. Conflation is the process of identifying common points and references to reconcile two or more geo-datasets across overlapping areas. Because of differences in scales, resolutions, and accuracy or conventions, data referring to the same location often do not have the same geographic reference and cannot be combined easily. This leads to defining “near enough” criteria to expect two references to represent the same feature. The user of “near enough criteria,” while allowing several corresponding features to be merged effectively, is not perfect. Feature variations encountered over large geodatabases reveal that reconciliation will always be needed and problematic, pointing to issues in quality control and verification.

The federal government and state agencies are moving to wider application of the federally mandated road network database, ARNOLD (All Road Network of Linear Referenced Data). Since ARNOLD is the base map for both HPMS and HPMRDS, it’s likely that it will become the foundation for most transportation mapping applications and the primary input for conflation of other map resources. It should be noted that the private industry is seeking to overcome similar challenges through the use of open source and crowdsourcing to develop base maps such as Open Street Map (OSM) and Google Maps.

As part of NCHRP 08-119 project, efforts are underway to develop several products that will help practitioners with challenges associated with network conflation. The products resulting from these efforts will provide recommendations regarding best practices for network conflation tools, researching potential improvements to these tools and methods, and identifying transportation agencies where the use of best conflation practices can be demonstrated. These products include: 

  • Guidance document describing best practices and summarizing their value and appropriate use. This document would be oriented toward practice managers potentially interested in adopting some or all for the product recommendations.
  • Software tools or scripts providing an implementation pathway for improved georeferencing processing.
  • Prototypical referenced datasets based on partner agency inputs and demonstration results.

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