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3D Solids and Their Management In DBMS

  • Chen Tet Khuan
  • Alias Abdul-Rahman
  • Sisi Zlatanova
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

3D spatial modeling is one of the most important issues in 3D GIS research. It involves the definition of spatial objects, data models, and attributes for visualization, interoperability and standards. Real world complexity leads to different modeling approaches, as seen in different GIS applications. This paper provides some review of the problems, challenges and issues pertaining to the 3D GIS problems, especially in the handling and managing of 3D solids in DBMS. The paper also describes 3D spatial operators in DBMS and presents results using a simulation dataset. At the end of the paper, we provide and highlight requirements and recommendations for future research.

Keywords

Spatial Object NURBS Curve Bezier Curve Minimum Bound Rectangle Very Large Data Base 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Abdul-Rahman A, Zlatanova S, Coors V (2006) Lecture Note on geoinformation and cartography — Innovations in 3D Geo Information Systems, Springer-VerlagGoogle Scholar
  2. Aguilera A (1998) Orthogonal polyhedra: study and application. Ph.D. Thesis, LSI-Universitat Polit èecnica de CatalunyaGoogle Scholar
  3. Arens CA (2003) Modelling 3D spatial objects in a geo-DBMS using a 3D primitives. Msc thesis, TU Delft, The NetherlandsGoogle Scholar
  4. Arens C, Stoter JE, van Oosterom PJM (2005) Modelling 3D spatial objects in a geo-DBMS using a 3D primitive. In: Computers & Geosciences, 31:165–177CrossRefGoogle Scholar
  5. Arya S, Mount DM, Netanyahu NS, Silverman R, Wu AY (1994) An optimal algorithm for approximate nearest neighbor searching. In: Proc. ACM-SIAM Symposium on Discrete Algorithms, pp. 573–582Google Scholar
  6. Beckmann N, Kriegel H, Schneider R, Seeger B (1990) The R* tree: An efficient and robust access method for points and rectangles. In: Proc. ACM SIGMOD Int. Conf. on Management of Data, pp. 322–331Google Scholar
  7. Bentley (2007) available at http://www.bentley.com/
  8. Berchtold S, Keim DA, Kreigel HP (1996) The X-tree: An index structure for high dimensional data. In: Proc. of the Int. Conf. on Very Large DatabasesGoogle Scholar
  9. Berchtold S, Keim DA, Kriegel HP, Seidl T (2000) A new technique for nearest neighbor search in high-dimensional space. IEEE Trans. In: Knowledge and Data Engineering, 12(1):45–57CrossRefGoogle Scholar
  10. Chen TK, Abdul-Rahman A (2006) 0-D feature in 3D planar polygon testing for 3D spatial analysis. In: Abdul-Rahman A, Zlatanova S, and Coors V (eds), Lecture Note on geoinformation and cartography — innovations in 3D Geo information systems, Springer-Verlag. pp. 169–183Google Scholar
  11. CityGML available at http://www.citygml.org/
  12. Clark JH (1976) Hierarchical geometric models for visible surface algorithm. In: Communications of the ACM, 19(10), pp. 547–554CrossRefGoogle Scholar
  13. ESRI (2007) available at http://www.esri.com/
  14. Ferhatosmanoglu H, Tuncel E, Agrawal D, Abbadi AE (2001) Approximate nearest neighbor searching in multimedia databases. In: Proc. Int. Conf. on Data Engineering, pp. 503–511Google Scholar
  15. Garcia YJ, Leutenegger ST, Lopez MA (1998) A greedy algorithm for bulk loading R-trees. In: Proc. of ACM GISGoogle Scholar
  16. Gionis A, Indyk P, Motwani R (1999) Similarity search in high dimensions via hashing. In: Proc. 25th International Conference on Very Large Data Bases (VLDB), pp. 518–529Google Scholar
  17. Guttman A (1984) R-trees: A dynamic index structure for spatial searching. In: Proceedings of ACM SIGMOD, International Conference on Management of Data, Boston, MA, pp. 47–57Google Scholar
  18. Henrich A (1994) A distance scan algorithm for spatial access structures. In: Proc. ACM International Workshop on Advances in Geographic Information Systems, pp. 136–143Google Scholar
  19. Hjaltason GR, Samet H (1995) Ranking in spatial databases. In: Proc. 4th Symposium on Spatial Databases, pp. 83–95Google Scholar
  20. Ledoux H, Gold CM (2004) Modelling oceanographic data with the three-dimensional Voronoi diagram. In: ISPRS 2004-XXth Congress, Istanbul, Turkey,. Vol. 2, pp. 703–708Google Scholar
  21. Kada M, Haala N, Becker S (2006) Improving the realism of existing 3D city model. In: Abdul-Rahman A, Zlatanova S, and Coors V (eds), Lecture Note on geoinformation and cartography — innovations in 3D Geo information systems, Springer-Verlag. pp. 405–415Google Scholar
  22. Kamel I, Faloutsos C (1994) Hilbert R-tree:An improved R-tree using fractals. In: Proc. 20th International Conference on Very Large Databases, pp. 500–509Google Scholar
  23. Katayama N, Satoh S (1997) The SR-tree: an index structure for high-dimensional nearest neighbor queries. In: Proc. ACM SIGMOD International Conference on Management of Data, pp. 369–380Google Scholar
  24. Kolbe T, Groeger G, Czerwinski A (2006) City Geography Markup Language (CityGML). In: OGC, OpenGIS Consortium, Discussion Papers, Version 0.3.0Google Scholar
  25. Les P (1991) On NURBS: a survey. IEEE Computer Graphics and Applications 11(1): 55–71CrossRefGoogle Scholar
  26. Lin KI, Jagdish HV, Faloutsos C (1994) The TV-tree: An index structure for high-dimensional data. VLDB Journal, 3:517–542CrossRefGoogle Scholar
  27. Lomet DB, Salzberg B (1990) The hB-tree: A multi-attribute indexing method with good guaranteed performance. Proc. A CM Syrup. on Transactions of Database Systems, 15(4):625–658CrossRefGoogle Scholar
  28. OGC (1999) Abstract specifications overview. Available at http://www.opengis.org/
  29. OGC (1999a) OpenGIS simple features specification for SQL. Available at http://www.opengis.org/
  30. OGC (2001) The OpenGIS™ Abstract specification, topic 1: feature geometry (ISO 19107 Spatial Schema) Version 5 Oracle Spatial 10g available at http://www.oracle.com/
  31. Orenstein J (1986) Spatial query processing in an object-oriented database system. In: Proceedings of 1986 ACM SIGMOD International Conference on Management of Data, pp. 326–336Google Scholar
  32. Penninga F (2005) 3D topographic data modelling: why rigidity is preferable to pragmatism. In: Spatial Information Theory, Cosit’05, Vol. 3693 of Lecture Notes on Computer Science, Springer. pp 409–425Google Scholar
  33. Penninga F, van Oosterom PJM, Kazar BM (2006) A TEN-based DBMS approach for 3D topographic data modelling. In: Spatial Data Handling 2006Google Scholar
  34. Penninga F, van Oosterom PJM (2007) A compact topological DBMS data structure for 3D topography. In: Fabrikant S, Wachowicz M (eds.), Lecture Notes in Geoinformation and Cartography. ISBN: 978-3-540-72384-4Google Scholar
  35. Pilouk M (1996) Integrated modelling for 3D GIS. PhD Thesis, ITC, The NetherlandsGoogle Scholar
  36. PostGIS (2006) available at http://postgis.refractions.net/
  37. Pu S (2005) Managing freeform curves and surfaces in a spatial DBMS. Msc Thesis, TU DelftGoogle Scholar
  38. Pu S, Zlatanova S (2006) Integration of GIS and CAD at DBMS level. In: E. Fendel E, Rumor M (eds), Proceedings of UDMS’06 Aalborg, Denmark, TU Delft, pp 9.61–9.71Google Scholar
  39. Rigaux P., Scholl M, Voisard A (2002) Spatial databases-with application to GIS. Morgan Kaufmann Publishers, San FranciscoGoogle Scholar
  40. Robinson J (1981) The K-D-B-Tree: A search structure for large multidimensional dynamic indexes. In: Proceedings of ACM SIGMOD International Conference on Management of Data, pp. 10–18Google Scholar
  41. Sakurai Y, Yoshikawa M, Uemura M, Kojima H (2002) Spatial indexing of high-dimensional data based on relative approximation. The International Journal on Very Large Data Bases, 11(2), pp. 93–108CrossRefGoogle Scholar
  42. Seeger B, Kriegel HP (1990) The Buddy tree: an ef[FB01?]cient and robust access method for spatial data base systems. In: Proc. 16th International Conference on Very Large Data Bases (VLDB), pp. 590–601Google Scholar
  43. Vebree E, Zlatanova S (2004) 3D-modeling with respect to boundary representations within geo-DBMS. GISt report No.29, TU DelftGoogle Scholar
  44. Wang F (1991) Relational-linear quadtree approach for two-dimensional spatial representation and manipulation. IEEE Trans. on Knowledge and Data Engineering, 3(1):118–122CrossRefGoogle Scholar
  45. Weber R, Schek HJ, Blott S (1998) A quantitative analysis and performance study for similarity-search methods in high dimensional spaces. In: Proc. 24th International Conference on Very Large Data Bases (VLDB), pp. 194–205Google Scholar
  46. White DA, Jain R (1996) Similarity Indexing with the SS-tree. In: Proc. IEEE 12th International Conference on Data Engineering, pp. 516–523Google Scholar
  47. Zlatanova S (2000) 3D GIS for urban development. PhD thesis, ITC, The NetherlandsGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Chen Tet Khuan
    • 1
  • Alias Abdul-Rahman
    • 1
  • Sisi Zlatanova
    • 2
  1. 1.Department of Geoinformatics, Faculty of Geoinformation Science and EngineeringUniversiti Teknologi MalaysiaSkudaiMalaysia
  2. 2.OTB, section GIS TechnologyDelft University of Technologythe Netherlands

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