2002•Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIERequires access

Practical algorithm of building Delaunay triangle mesh for terrain modeling

Chuan-Jie Xiang, Yunde Jia

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Abstract

The triangular irregular network (TIN) method is a rational choice for building digital elevation model (DEM) to keep model more precise. The common problem in forming standard delaunay triangle mesh is time-consuming, especially with the large data of sampling nodes. Accordingly, we introduce a practical algorithm to reduce sampling quantity of terrain in a single delaunay triangle mesh and to increase the efficiency of building the mesh greatly. We tested the algorithm with several real sampling data with different distributions. We also present the comparison result of the proposed method with the traditional.

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What this paper is about

The triangular irregular network (TIN) method is a rational choice for building digital elevation model (DEM) to keep model more precise. The common problem in forming standard delaunay triangle mesh is time-consuming, especially with the large data of sampling nodes. Accordingly, we introduce a practical algorithm to reduce sampling quantity of terrain in a single delaunay triangle mesh and to increase the efficiency of building the mesh greatly. We tested the algorithm with several real sampling data with different distributions. We also present the comparison result of the proposed method with the traditional.

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Available abstract

The triangular irregular network (TIN) method is a rational choice for building digital elevation model (DEM) to keep model more precise. The common problem in forming standard delaunay triangle mesh is time-consuming, especially with the large data of sampling nodes. Accordingly, we introduce a practical algorithm to reduce sampling quantity of terrain in a single delaunay triangle mesh and to increase the efficiency of building the mesh greatly. We tested the algorithm with several real sampling data with different distributions. We also present the comparison result of the proposed method with the traditional.

Key concepts: Delaunay triangulation, Triangulated irregular network, Computer science, Triangle mesh, Terrain, Algorithm, Sampling (signal processing), Constrained Delaunay triangulation

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