Description and Generalization of Point Clustering Features

  • Haowen Yan


This chapter aims at presenting the algorithms for point clustering feature generalization. For this purpose, it firstly defines and describes the relevant concepts (Sect. 2.1) and illustrates the types of point clustering features on maps (Sect. 2.2), and analyzes the approaches for describing point clustering features (Sect. 2.3). After this, it presents and analyzes the existing algorithms (Sects. 2.4 and 2.5). Last, the chapter is ended by a concluding summary (Sect. 2.6).


  1. Ahuja, N., 1982. Dot pattern processing using Voronoi neighborhoods. IEEE Transactions on Pattern Analysis and Machine Intelligence 4 (3), 336–343.CrossRefGoogle Scholar
  2. Ahuja, N., Tuceryan, M., 1989. Extraction of early perceptual structure in dot patterns: integrating region, boundary and component gestalt. Computer Vision, Graphics and Image Processing 48 (3), 304–356.CrossRefGoogle Scholar
  3. Bjørke, J., 1996. Framework for entroy-based map evaluation. Cartography and Geographic Information Systems 23 (2), 78–95.CrossRefGoogle Scholar
  4. Burghardt, D., Purves, R., Edwards, A., 2004. Techniques for on the-fly generalization of thematic point data using hierarchical data structures. In: Proceedings of the GIS Research UK 12th Annual Conference, Norwich, UK.
  5. Cecconi, A., Galanda, M., 2002, Adaptive zooming in web cartography, Computer Graphics Forum, 21, pp. 787–799.CrossRefGoogle Scholar
  6. De Berg, M., Bose, P., Cheong, O., Morin, P., 2004. On simplifying dot maps. Computational Geometry 27 (1), 43–62.CrossRefGoogle Scholar
  7. Guo, R., 1997. Spatial Analysis, first ed. Press of Wuahan Technical University of Surveying and Mapping, Wuhan, 236pp (in Chinese).Google Scholar
  8. Harrie, L., Sarjakoski, T., Lehto, L., 2002, A variable-scale map for small-display cartography. In Proceedings of the Joint International Symposium on Geospatial Theory, Processing and Applications (Ottawa), CD-ROM.Google Scholar
  9. Jones, C.B., Ware, J.M., 2005. Map generalization in the web age. International Journal of Geographical Information Science 19 (8–9), 859–870.CrossRefGoogle Scholar
  10. Langran, C., Poicker, T., 1986. Integration of name selection and name placement. In: Proceedings of second International Symposium on Spatial Data Handling, Washington, USA, pp. 50–64.Google Scholar
  11. Li, Z., Huang, P., 2002. Quantitative measures for spatial information of maps. International Journal of Geographical Information Systems 16 (7), 699–709.CrossRefGoogle Scholar
  12. Li, Z., Yan, H., Ai, T., Chen, J., 2004. Automated building generalization based on urban morphology and gestalt theory. International Journal of Geographical Information Science 18 (5), 513–534.CrossRefGoogle Scholar
  13. Mustiere, S., 2005. Cartographic generalization of road in a local and adaptive approach: a knowledge acquisition problem. International Journal of Geographical Information Science 19 (8–9), 937–956.CrossRefGoogle Scholar
  14. Neumann, J., 1994. The topological information content of a map: an attempt at a rehabilitation of information theory in cartography. Cartographica 31 (1), 26–34.CrossRefGoogle Scholar
  15. Sadahiro, Y., 1997. Cluster perception in the distribution of point objects. Cartographica 34 (1), 49–61.CrossRefGoogle Scholar
  16. Sester, M., 2005. Optimization approaches for generalization and data abstraction. International Journal of Geographical Information Science 19 (8–9), 871–897.CrossRefGoogle Scholar
  17. Shannon, C., Weaver, W., 1949. The Mathematical Theory of Communication. University of Illinois Press, Urbana, IL, 117pp.Google Scholar
  18. Sukhov, V., 1967. Information capacity of a map entropy. Geodesy and Aerophotography 10 (4), 212–215.Google Scholar
  19. Sukhov, V., 1970. Application of information theory in generalization of map contents. International Yearbook of Cartography 10 (1), 41–47.Google Scholar
  20. Töpfer, F., Pillewizer, W., 1966. The principles of selection. The Cartographic Journal 3 (1), 10–16.CrossRefGoogle Scholar
  21. Tobler, W.R., 1970. A computer movie simulating urban growth in the Detroit region. Economic Geography 46 (2), 234–240.CrossRefGoogle Scholar
  22. Van Kreveld, M., Van Oostrum, R., Snoeyink, J., 1995. Efficient settlement selection for interactive display. In: Proceedings of Auto Carto 12, Bethesda, MD, USA, pp. 287–296.Google Scholar
  23. Van Kreveld, M., Van Oostrum, R., Snoeyink, J., 1997. Efficient settlement selection for interactive display. In: Proceedings of Auto Carto 13, Bethesda, MD, USA, pp. 287–296.Google Scholar
  24. Weibel, R., Burgardt, D., 2008, On-the-Fly generalization. In: Shekhar, [et al.]. Encyclopedia of GIS. New York, US, pp.339–344.Google Scholar
  25. Yan, H., Weibel R., 2008, An algorithm for point cluster generalization based on the Voronoi diagram. Computers & GeoSciences. 34(8): 939–954.CrossRefGoogle Scholar

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© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Haowen Yan
    • 1
  1. 1.Faculty of GeomaticsLanzhou Jiaotong UniversityLanzhouChina

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