Document Open Access Logo

Center Point of Simple Area Feature Based on Triangulation Skeleton Graph (Short Paper)

Authors Wei Lu , Tinghua Ai

PDF

File

Thumbnail PDF
PDF
LIPIcs.GISCIENCE.2018.41.pdf
  • Filesize: 455 kB
  • 6 pages

Document Identifiers

Subject Classification

ACM Subject Classification
  • Information systems → Geographic information systems
Keywords
  • Shape Center
  • Triangulation Skeleton Graph
  • Graph Centrality

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads
    0
    Metadata Views

Abstract

In the area of cartography and geographic information science, the center points of area features are related to many fields. The centroid is a conventional choice of center point of area feature. However, it is not suitable for features with a complex shape for the center point may be outside the area or not fit the visual center so well. This paper proposes a novel method to calculate the center point of area feature based on triangulation skeleton graph. This paper defines two kinds of centrality of vertices in skeleton graph according to the centrality theory in graph and network analysis. Through the measurement of vertices centrality, the center points of polygon area features are defined as the vertices with maximum centrality.

Cite As Get BibTex

Wei Lu and Tinghua Ai. Center Point of Simple Area Feature Based on Triangulation Skeleton Graph (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 41:1-41:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018) https://doi.org/10.4230/LIPIcs.GISCIENCE.2018.41

Author Details

Wei Lu
  • Wuhan University, Wuhan, China
Tinghua Ai
  • Wuhan University, Wuhan, China

Funding

This research was supported by the National Key Research and Development Program of China (Grant No. 2017YFB0503500), and the National Natural Science Foundation of China (Grant No. 41531180).

References

  1. Tinghua Ai and Peter van Oosterom. Gap-tree extensions based on skeletons. In Advances in Spatial Data Handling, pages 501-513. Springer, Berlin, Heidelberg, 2002. URL: http://dx.doi.org/10.1007/978-3-642-56094-1_37.
  2. Wolfgang Aigner, Franz Aurenhammer, and Bert Jüttler. On triangulation axes of polygons. Information Processing Letters, 115(1):45-51, 2015. URL: http://dx.doi.org/10.1016/j.ipl.2014.08.006.
  3. Xiang Bai and Longin Jan Latecki. Path similarity skeleton graph matching. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(7):1282-1292, 2008. URL: http://dx.doi.org/10.1109/TPAMI.2007.70769.
  4. Mark de Berg, Otfried Cheong, Marc van Kreveld, and Mark Overmars. Computational Geometry: Algorithms and Applications. Springer, Santa Clara, CA, USA, 3 edition, 2008. Google Scholar
  5. Harry Blum. Biological shape and visual science (part 1). Journal of Theoretical Biology, 38(2):205-287, 1973. URL: http://dx.doi.org/10.1016/0022-5193(73)90175-6.
  6. Stephen P. Borgatti and Martin G. Everett. A graph-theoretic perspective on centrality. Social Networks, 28(4):466-484, 2006. URL: http://dx.doi.org/10.1016/j.socnet.2005.11.005.
  7. Tao Chen and Tinghua Ai. Automatic extraction of skeleton and center of area feature. Geomatics and Information Science of Wuhan University, 29(5):443, 2004. URL: http://dx.doi.org/10.13203/j.whugis2004.05.015.
  8. Jesús A. De Loera, Jörg Rambau, and Francisco Santos. Triangulations:Structures for Algorithms and Applications, volume 25 of Algorithms and Computation in Mathematics. Springer Berlin Heidelberg, Berlin, Heidelberg, 2010. URL: http://dx.doi.org/10.1007/978-3-642-12971-1.
  9. Daniel Garcia-Castellanos and Umberto Lombardo. Poles of inaccessibility: A calculation algorithm for the remotest places on earth. Scottish Geographical Journal, 123(3):227-233, 2007. URL: http://dx.doi.org/10.1080/14702540801897809.
  10. Bin Jiang and Xintao Liu. Scaling of geographic space from the perspective of city and field blocks and using volunteered geographic information. International Journal of Geographical Information Science, 26(2):215-229, feb 2012. URL: http://dx.doi.org/10.1080/13658816.2011.575074.
  11. Jia-Guu Leu. Computing a shape’s moments from its boundary. Pattern Recognition, 24(10):949-957, jan 1991. URL: http://dx.doi.org/10.1016/0031-3203(91)90092-J.
Any Issues?
X

Feedback on the Current Page

CAPTCHA

Thanks for your feedback!

Feedback submitted to Dagstuhl Publishing

Could not send message

Please try again later or send an E-mail
© 2023-2025 Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact