Spatial Queries in the Presence of Obstacles

  • Jun Zhang
  • Dimitris Papadias
  • Kyriakos Mouratidis
  • Manli Zhu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2992)


Despite the existence of obstacles in many database applications, traditional spatial query processing utilizes the Euclidean distance metric assuming that points in space are directly reachable. In this paper, we study spatial queries in the presence of obstacles, where the obstructed distance between two points is defined as the length of the shortest path that connects them without crossing any obstacles. We propose efficient algorithms for the most important query types, namely, range search, nearest neighbors, e-distance joins and closest pairs, considering that both data objects and obstacles are indexed by R-trees. The effectiveness of the proposed solutions is verified through extensive experiments.


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  1. [AGHI86]
    Asano, T., Guibas, L., Hershberger, J., Imai, H.: Visibility of Disjoint Polygons. Algorithmica 1, 49–63 (1986)zbMATHCrossRefMathSciNetGoogle Scholar
  2. [BKOS97]
    de Berg, M., van Kreveld, M., Overmars, M., Schwarzkopf, O.: Computational Geometry, pp. 305–315. Springer, Heidelberg (1997)zbMATHGoogle Scholar
  3. [BKS93]
    Brinkhoff, T., Kriegel, H., Seeger, B.: Efficient Processing of Spatial Joins Using R-trees. In: SIGMOD (1993)Google Scholar
  4. [BKSS90]
    Becker, B., Kriegel, H., Schneider, R., Seeger, B.: The R*-tree: An Efficient and Robust Access Method. In: SIGMOD (1990)Google Scholar
  5. [CMTV00]
    Corral, A., Manolopoulos, Y., Theodoridis, Y., Vassilakopoulos, M.: Closest Pair Queries in Spatial Databases. In: SIGMOD (2000)Google Scholar
  6. [D59]
    Dijkstra, E.: A Note on Two Problems in Connection with Graphs. Numeriche Mathematik 1, 269–271 (1959)zbMATHCrossRefMathSciNetGoogle Scholar
  7. [EL01]
    Estivill-Castro, V., Lee, I.: Fast Spatial Clustering with Different Metrics in the Presence of Obstacles. In: ACM GIS (2001)Google Scholar
  8. [G84]
    Guttman, A.: R-trees: A Dynamic Index Structure for Spatial Searching. In: SIGMOD (1984)Google Scholar
  9. [GM87]
    Ghosh, S., Mount, D.: An Output Sensitive Algorithm for Computing Visibility Graphs. In: FOCS (1987)Google Scholar
  10. [HS98]
    Hjaltason, G., Samet, H.: Incremental Distance Join Algorithms for Spatial Databases. In: SIGMOD (1998)Google Scholar
  11. [HS99]
    Hjaltason, G., Samet, H.: Distance Browsing in Spatial Databases. TODS 24(2), 265–318 (1999)CrossRefGoogle Scholar
  12. [KHI+86]
    Kung, R., Hanson, E., Ioannidis, Y., Sellis, T., Shapiro, L., Stonebraker, M.: Heuristic Search in Data Base Systems. Expert Database Systems (1986)Google Scholar
  13. [LW79]
    Lozano-Pérez, T., Wesley, M.: An Algorithm for Planning Collision-free Paths among Polyhedral Obstacles. CACM 22(10), 560–570 (1979)Google Scholar
  14. [PV95]
    Pocchiola, M., Vegter, G.: Minimal Tangent Visibility Graph. Computational Geometry: Theory and Applications (1995)Google Scholar
  15. [PV96]
    Pocchiola, M., Vegter, G.: Topologically Sweeping Visibility Complexes via Pseudo-triangulations. Discrete Computational Geometry (1996)Google Scholar
  16. [PZMT03]
    Papadias, D., Zhang, J., Mamoulis, N., Tao, Y.: Query Processing in Spatial Network Databases. In: VLDB (2003)Google Scholar
  17. [R95]
    Rivière, S.: Topologically Sweeping the Visibility Complex of Polygonal Scenes. In: Symposium on Computational Geometry (1995)Google Scholar
  18. [SRF87]
    Sellis, T., Roussopoulos, N., Faloutsos, C.: The R+-tree: a Dynamic Index for Multi-Dimensional Objects. In: VLDB (1987)Google Scholar
  19. [SS84]
    Sharir, M., Schorr, A.: On Shortest Paths in Polyhedral Spaces. In: STOC (1984)Google Scholar
  20. [THH01]
    Tung, A., Hou, J., Han, J.: Spatial Clustering in the Presence of Obstacles. In: ICDE (2001)Google Scholar
  21. [W85]
    Welzl, E.: Constructing the Visibility Graph for n Line Segments in O(\({\it n}^2\)) Time. Information Processing Letters 20, 167–171 (1985)zbMATHCrossRefMathSciNetGoogle Scholar
  22. [Web]

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Jun Zhang
    • 1
  • Dimitris Papadias
    • 1
  • Kyriakos Mouratidis
    • 1
  • Manli Zhu
    • 1
  1. 1.Department of Computer ScienceHong Kong University of Science and TechnologyHong Kong

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