Volume XL-2/W1
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2/W1, 87-92, 2013
https://doi.org/10.5194/isprsarchives-XL-2-W1-87-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2/W1, 87-92, 2013
https://doi.org/10.5194/isprsarchives-XL-2-W1-87-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

  13 May 2013

13 May 2013

COMPARISON OF POINT MATCHING TECHNIQUES FOR ROAD NETWORK MATCHING

A. Hackeloeer1, K. Klasing1, J. M. Krisp2, and L. Meng2 A. Hackeloeer et al.
  • 1BMW Forschung und Technik GmbH, Hanauer Straße 46, 80992 Munich, Germany
  • 2Department of Cartography, Technische Universität München, Arcisstraße 21, 80333 Munich, Germany

Keywords: Conflation, Road Network Matching, Point Matching

Abstract. Map conflation investigates the unique identification of geographical entities across different maps depicting the same geographic region. It involves a matching process which aims to find commonalities between geographic features. A specific subdomain of conflation called Road Network Matching establishes correspondences between road networks of different maps on multiple layers of abstraction, ranging from elementary point locations to high-level structures such as road segments or even subgraphs derived from the induced graph of a road network.

The process of identifying points located on different maps by means of geometrical, topological and semantical information is called point matching. This paper provides an overview of various techniques for point matching, which is a fundamental requirement for subsequent matching steps focusing on complex high-level entities in geospatial networks. Common point matching approaches as well as certain combinations of these are described, classified and evaluated. Furthermore, a novel similarity metric called the Exact Angular Index is introduced, which considers both topological and geometrical aspects. The results offer a basis for further research on a bottom-up matching process for complex map features, which must rely upon findings derived from suitable point matching algorithms. In the context of Road Network Matching, reliable point matches provide an immediate starting point for finding matches between line segments describing the geometry and topology of road networks, which may in turn be used for performing a structural high-level matching on the network level.