Skip to main content
Log in

Using B+-trees for processing of line segments in large spatial databases

  • Published:
Journal of Intelligent Information Systems Aims and scope Submit manuscript

Abstract

Points, lines, and regions are the three basic entities for constituting vector-based objects in spatial databases. Many indexing methods (G-tree, K-D-B tree, Quad-tree, PMR-tree, Grid-file, R-tree, and so on) have been widely discussed for handling point or region data. These traditional methods can efficiently organize point or region objects in a space into a hashing or hierarchical directory. They provide efficient access methods to meet the requirement of accurate retrievals. However, two problems are encountered when their techniques are applied to deal with line segments. The first is that representing line segments by means of point or region objects cannot exactly and properly preserve the spatial information about the proximities of line segments. The second problem is derived from the large dead space and overlapping areas in external and internal nodes of the hierarchical directory caused by the use of rectangles to enclose line objects. In this paper, we propose an indexing structure for line segments based on B +-tree to remedy these two problems. Through the experimental results, we demonstrate that our approach has significant improvement over the storage efficiency. In addition, the retrieval efficiency has also been significantly prompted as compared to the method using R-tree index scheme. These improvements derive mainly from the proposed data processing techniques and the new indexing method.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Bentley, J. L. (1975). Multidimensional binary search trees used for associative searching. Communications of the ACM, 18(9), 509–517.

    Article  MATH  MathSciNet  Google Scholar 

  • Blanken, H., Ijbema, A., Meek, P., & Akker, B. (1990). The generalized grid file: Description and performance aspects. In Proceeding of 6th IEEE International Conference on Data Engineering, 380–388. Washington, DC: IEEE Computer Society.

  • Gaede, V., & Gunther, O. (1998). Multidimensional access methods. ACM Computing Surveys, 30(2), 170–231.

    Article  Google Scholar 

  • Guttman, A. (1984). R-trees: A dynamic index structure for spatial searching. In Proceedings of ACM SIGMOD (47–57). New York: ACM.

  • Hoel, E. G., & Samet, H. (1991). Efficient processing of spatial queries in line segment databases In O. Gunther & H. J. Schek (Eds.), Advances in spatial databases—2nd symposium, SSD91, Lecture notes in computer science 525 (pp. 237–256). Berlin: Springer.

    Google Scholar 

  • Hoel, E. G., & Samet, H. A. (1992). Qualitative comparison study of data structure for large segment databases, SIGMOD (pp. 205–214). San Diego, CA.

  • Jagadish, H. V. (1990). On indexing line segments. In D. McLeod, R. Sacks-Davis, & H. Schek (Eds.), Proceedings of the Sixteen International Conference on Very Large Data Bases (614–625). Brisbane, Australia.

  • Kumar, A. (1994). G-tree: A new data structure for organization multidimensional data. IEEE Transaction on Knowledge and Data Engineering, 6(2), 341–347.

    Article  Google Scholar 

  • Lanka, S., & Mays, E. (1991). Fully persistent B +-trees. In Proceedings of ACM SIGMOD (426–435). New York: ACM.

  • Lindenbaum, M., Samet, H., & Hjaltason, G. R. A. (2000). Probabilistic analysis of trie-based sorting of large collections of line segments in spatial databases, University of Maryland Computer Science TR 3455.1.

  • Nievergelt, J., Hinterberger, H., & Sevcik, K. (1984). The grid file: an adaptable symmetric multikey file structure. ACM Transactions on Database Systems, 9(1), 38–71.

    Article  Google Scholar 

  • Orenstein, J. A., & Merrett, T. H. (1984). A class of data structure for associative searching. In Proceedings of the Third ACM SIGACT-SIGMOD Symp. on Principles of Database Systems (pp. 181–190). New York: ACM.

  • Papadias, D., & Theodoridis, Y. (1997). Spatial relations, minimum bounding rectangles and spatial data structures. International Journal of Geographical Information Science, 11(2), 111–138.

    Article  Google Scholar 

  • Robinson, J. T. (1981). The K-D-B Tree: A search structure for large multidimensional dynamic indexes. In Proceedings of ACM SIGMOD (pp. 10–18). New York: ACM.

  • Six, H., & Widmayer, P. (1988). Spatial searching in geometric databases. In Proceeding of 4th IEEE International Conference on Data Engineering (496–503).

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hung-Yi Lin.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lin, HY. Using B+-trees for processing of line segments in large spatial databases. J Intell Inf Syst 31, 35–52 (2008). https://doi.org/10.1007/s10844-007-0039-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10844-007-0039-y

Keywords

Navigation