An Integrative Approach to Geospatial Data Fusion

  • Silvija Stankutė
  • Hartmut Asche
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5592)


Geodata are used in different branches of industry or academic fields, e.g. landscape planning, environmental protection, traffic, urbanism, economy, tourism et cetera. Depending on the objectives and applications, geodata will have to meet certain requirements in order to be utilised, e.g. concerning geometry and/or semantics. A frequent problem of geo information processing is to identify suitable datasets. The geometric requirements are often met, while this is not the case with semantic requirements. Sometimes geo datasets have similar geometric properties but different semantics. Generally, the acquisition of fresh geodata meeting the requirements defined is not an option. Instead, data mining concepts, as such as data fusion, provide an effective solution to this problem. The fundamental concept of data fusion is the extraction of the best-fit geometry data as well as the most suitable semantic data from existing datasets. The extracted data features are subsequently amalgamated into a newly created dataset. Data fusion can be applied to linear and polygonal data. This work introduces algorithms allowing for the joining of linear structures. The method discussed is based on the comparison of coordinates. The fusion process has been automated and implemented in the DataMerge software tool using the PERL scripting language and thus is not bound to any specific GIS software.


Data fusion edge matching vector data homogenization heterogeneous geodata data mining 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Saalfeld, A.: Conflation: automated map compilation. International Journal of Geographical Information Systems 2, 217–228 (1988)CrossRefGoogle Scholar
  2. 2.
    Brown, J., Rao, A., Baran, J.: Automated GIS conflation: coverage update problems and solutions. In: Proc. of Geographic Information Systems for Transportation Symposium (GIS-T), American Association of State Highway and Transportation Officials, Sparks, Nevada, pp. 220–229 (1995)Google Scholar
  3. 3.
    Walter, V., Fritsch, D.: Matching spatial data sets: a statistical approach. International Journal of Geographical Information Science 13, 445–473 (1999)CrossRefGoogle Scholar
  4. 4.
    Xiong, D.: A three-stage computational approach to network matching. Transportation Research, part C 8(1-6), 71–89 (2000)CrossRefGoogle Scholar
  5. 5.
    Doytsher, Y., Safra, E., Kanza, Y., Sagiv, Y.: Proceedings of the 14th annual ACM international symposium on Advances in geographic information systems, Geographic Information Systems, November 10-11, 2006, pp. 59–66 (2006)Google Scholar
  6. 6.
    Butenuth, M., Gösseln, G.v., Tiedge, M., Heipke, C., Lipeck, U., Sester, M.: Integration of heterogeneous gespatial data in a federated data-base. ISPRS Journal of Photogrammetry & Remote Sensing 62, 328–346 (2007)CrossRefGoogle Scholar
  7. 7.
    Kieler, B.: Derivation of semantic relationships between different ontologies with the help of geometry. In: Workshop Semantic web meets geospatial applications, held conjuncion with AGILE 2008 (2008)Google Scholar
  8. 8.
    Bartelme, N.: Geoinformatik: Modelle, Strukturen, Funktionen. Springer, Heidelberg (2005)Google Scholar
  9. 9.
    Stankute, S.: Entwicklung und Implementierung von Algorithmen für ein automatisiertes Verfahren zur Zusammenführung von Parametern aus Geodatenbanken unter besonderer Beachtung von Unschärfen in der Georeferenzierung. Unpublished master thesis (Universität Potsdam/DLR-Verkehrsstudien) (2007)Google Scholar
  10. 10.
    Wolff, M., Stankute, S., Asche, H., Zenner, C.: Erzeugung von GIS-Datenbeständen für themenkartographische Anwendungen mittels Datenfusion. In: Strobl, J., Blaschke, T., Griesebner, G. (eds.) Angewandte Geoinformatik 2008. Beiträge zum 20. AGIT-Symposium, p. 83. Wichmann, Heidelberg (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Silvija Stankutė
    • 1
  • Hartmut Asche
    • 1
  1. 1.Department of GeographyUniversity of PotsdamPotsdamGermany

Personalised recommendations