Skip to main content
SpringerLink
Log in

Matching Networks with Different Levels of Detail

  • Published:
GeoInformatica Aims and scope Submit manuscript

Abstract

This paper deals with the issue of automatically matching networks with different levels of details. We first present why this issue is complex through an analysis of the differences that can be encountered between networks. We also present different criteria, tools and approaches used for network matching. We then propose a matching process, named NetMatcher. This process is a several steps process looking for potential candidates and then analysing them in order to determine the final results. It relies on the comparison of geometrical, attributive, and topological properties of objects. It determines one-to-many links between networks: in particular a node of the less detailed network can be matched to several arcs and nodes forming a complex junction in the most detailed network. An important strength of the process is to self-evaluate its results through the comparison of topological organisation of networks. This paves the way to an interactive editing of the results. The NetMatcher process has been intensively tested on a wide range of actual datasets, thus highlighting its effectiveness as well as its limits.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  1. H. Alt and M. Godau. “Computing the Fréchet distance between two polygonal curves”, International Journal of Computational Geometry and Applications, Vol. Vol. 5(1/2):75–91, 1995.

    Google Scholar 

  2. T. Badard and C. Lemarié. “Propagating updates between geographic databases with different scales,” in Proc. of GeoComputation ’2000: Innovations in GIS VII, pp. 134–146, London, UK: Taylor & Francis, 2000.

  3. T. Badard and A. Braun. “Oxygene: a platform for the development of interoperable geographic applications and web services.” In Proc. of the 15th International Workshop on Database and Expert Systems Applications (DEXA'04), pp. 888–892, IEEE Press: Zaragoza, Spain, 2004.

  4. C. Beeri, Y. Kanza, E. Safra, and Y. Sagiv. “Object fusion in Geographic Information Systems,” in Proc. of the 30th VLDB conference, pp. 816–827, Toronto, Canada, 2004.

  5. A. Bel Hadj Ali, and F. Vauglin. “Geometric Matching of Polygons in GISs and assessment of Geometrical Quality of Polygons,” in Proc. of Int. Symp. on Spatial Data Quality (ISSDQ’99), pp. 33–43, Hong Kong, 1999.

  6. B. Buttenfield. “Line Structure in Graphic and Geographic Space,” PhD thesis, University of Washington, USA, 1984.

  7. M. Deng, X. Chen and Z. Li. “A Generalized Hausdorff Distance for Spatial Objects in GIS,” in Proc. of the 4th ISPRS Workshop on Dynamic and Multi-dimensional GIS, pp. 10–15, Pontypridd, UK, 2005.

  8. T. Devogele. “A new Merging process for data integration based on the discrete Fréchet distance,” in Proc. of the 10th Int. Symposium on Spatial Data Handling (SDH), pp. 167–181, Ottawa, Canada: Springer, 2002.

  9. T. Devogele. “Processus d'intégration et d'appariement des bases de données géographiques—Application à une base de données routière multi-échelles,” PhD thesis, Université de Versailles, France, 1997.

  10. T. Devogele, C. Parent, and S. Spaccapietra. “On spatial database integration”, International Journal of Geographical Information Science, Vol. Vol. 12(4):335–352, 1998.

    Article  Google Scholar 

  11. M. Gombosi, B. Zalik, and S. Krivograd. “Comparing two sets of polygons”, International Journal of Geographical Information Science, Vol. Vol. 17(5):431–443, 2003.

    Article  Google Scholar 

  12. J.–H. Haunert. “Link based conflation of geographic datasets,” in Proc. of the 8th ICA workshop on Generalisation and Multiple Representation, 7 p,, A Coruña, Spain, 2005.

  13. V.I. Levenshtein. “Binary codes capable of correcting deletions, insertions, and reversals,” Soviet Physics-Doklady, Vol. 10(8):707–710, 1966. Translated from Doklady Akademii Nauk SSSR, Vol. 163(4): 845–848, 1965.

  14. D. Mantel and U.W. Lipeck. “Matching Cartographic Objects in Spatial Databases”, in Proc. of ISPRS’2004, Archives of ISPRS, Vol. Vol. 35(B4):172–176, 2004.

    Google Scholar 

  15. A. Mascret, T. Devogele, I. Le Berre and A. Hénaff. “Coastline matching process based on the discrete Fréchet distance,” in Proc. of the 12th International Symposium on Spatial Data Handling (SDH), pp. 383–400, Springer: Vienna, Austria, 2006.

  16. R.B. McMaster. “A statistical analysis of mathematical measures for linear simplification,” PhD thesis, University of Kansas, KS, 1983.

  17. S. Mustière. “Results of experiments on automated matching of networks,” in Proc. of the ISPRS Workshop on Multiple Representation and Interoperability of Spatial Data, pp. 92–100, Hanover, Germany, 2006.

  18. A.-M. Olteanu. “A multi-criteria fusion approach for geographical data matching,” in Proc. of the 5th International Symposium On Spatial Data Quality (ISSDQ), Enschede, Netherlands, 2007.

  19. C. Parent, S. Spaccapietra, and T. Devogele. “Conflicts in Spatial Database Integration,” in Proc. Of the 9th Int. Conf. on Parallel and Distributed Computing Systems, PDCS ‘96, pp. 772–778, Dijon, France, 1996.

  20. C. Plazanet. “Enrichissement des bases de données géographiques: analyse de la géométrie des objets linéaires pour la généralisation cartographique (application au routes),” PhD thesis, Univ. de Marne-la-Vallée (F), 2006.

  21. M.A. Rodriguez and M.J. Egenhofer. “Determining semantic similarity among entity classes from different ontologies”, IEEE Transactions on Knowledge and Data Engineering, Vol. Vol. 15(2):442–456, 2003.

    Article  Google Scholar 

  22. A. Saalfeld. “Conflation: automated map compilation”, International Journal of GIS, Vol. Vol. 2(3):217–228, 1988.

    Google Scholar 

  23. E. Safra, Y. Kanza, Y. Sagiv, and Y. Doytsher. “Efficient integration of road maps,” in Proc. of the 14th annual ACM international symposium on Advances in geographic information systems, pp. 59–66, ACM Press: Arlington, VA, 2006.

  24. A. Samal, S.C. Seth, and K. Cueto. “A feature-based approach to conflation of geospatial sources”, International Journal of Geographical Information Science, Vol. Vol. 18(5):459–489, 2004.

    Article  Google Scholar 

  25. D. Sheeren, S. Mustière, and J.-D. Zucker. “Consistency assessment between multiple representations of geographical databases: a specification-based approach,” in Proc. of 11th International Symposium on Spatial Data Handling (SDH), pp. 617–627, Leicester, United Kingdom: Springer, July 2004.

  26. A. Stonykova. “Semantic validation in spatio-temporal schema integration,” PhD thesis, Ecole Polytechnique Fédérale de Lausanne, Switzerland, 2006.

  27. S. Timpf, G. Volta, D. Pollock, and M.J. Egenhofer. “A conceptual model of wayfinding using multiple levels of abstraction,” in Goos et Hartmanis (Eds.), Theories and Methods of Spatio-Temporal Reasoning in Geographic Space, Springer, pp. 348–367, 1992.

  28. H. Uitermark. “Ontology-based geographic data set integration,” PhD thesis, Universiteit Twente, The Netherlands, 2001.

  29. S. Volz. “An iterative approach for matching multiple representations of street data,” in Proc. of the ISPRS workshop on Multiple Representation and Interoperability of Spatial Data, pp. 101–110, Hanover (G), 2006.

  30. V. Walter and D. Fritsch. “Matching spatial data sets: a statistical approach”, International Journal of Geographical Information Science, Vol. Vol. 13(5):445–473, 1999.

    Article  Google Scholar 

  31. M. Zhang, W. Shi, and L. Meng. “A generic matching algorithm for line networks of different resolutions,” in Proc. of 8th ICA workshop on Generalisation and Multiple Representation, 8 p, A Coruña, Spain, 2005.

Download references

Author information

Authors and Affiliations

  1. IGN/COGIT Lab, 2 Av. Pasteur, 94160, St-Mandé, France

    Sébastien Mustière

  2. Naval Academy Research Institute (IRENav), Lanvéoc, BP 600, 29240, Brest Naval, France

    Thomas Devogele

Authors
  1. Sébastien Mustière
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Thomas Devogele
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sébastien Mustière.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Mustière, S., Devogele, T. Matching Networks with Different Levels of Detail. Geoinformatica 12, 435–453 (2008). https://doi.org/10.1007/s10707-007-0040-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10707-007-0040-1

Keywords

Search

Navigation