Abstract
For storing and modelling three-dimensional topographic objects (e.g. buildings, roads, dykes and the terrain), tetrahedralisations have been proposed as an alternative to boundary representations. While in theory they have several advantages, current implementations are either not space efficient or do not store topological relationships (which makes spatial analysis and updating slow, or require the use of a costly 3D spatial index). We discuss in this paper an alternative data structure for storing tetrahedralisations in a DBMS. It is based on the idea of storing only the vertices and stars of edges; triangles and tetrahedra are represented implicitly. It has been used previously in main memory, but not in a DBMS—we describe how to modify it to obtain an efficient implementation in a DBMS. As we demonstrate with one real-world example, the structure is around 20 % compacter than implemented alternatives, it permits us to store attributes for any primitives, and has the added benefit of being topological. The structure can be easily implemented in most DBMS (we describe our implementation in PostgreSQL) and we present some of the engineering choices we made for the implementation.
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Notes
- 1.
Notice that this model is often called “TEN", which stands for either TEtrahedral Network, TEtrahedral irregular Network, TEtrahedronised irregular Network or TEtrahedron Network, depending on the authors. For the purpose of this paper, they are all equivalent and a TEN is a tetrahedralisation, as defined in Sect. 2.
- 2.
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Acknowledgments
This research is supported by the Dutch Technology Foundation STW, which is part of the Netherlands Organisation for Scientific Research (NWO) and partly funded by the Dutch Ministry of Economic Affairs, Agriculture and Innovation (project codes: 11300 and 11185).
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Ledoux, H., Meijers, M. (2013). Representing Three-Dimensional Topography in a DBMS With a Star-Based Data Structure. In: Pouliot, J., Daniel, S., Hubert, F., Zamyadi, A. (eds) Progress and New Trends in 3D Geoinformation Sciences. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29793-9_7
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