Efficient representation and analysis of triangulated terrains
Efficient representation and analysis of triangulated terrains
复制标题
三角地形的高效表示和分析
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
L. Floriani
中科院分区：
文献类型：
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作者：
Riccardo Fellegara;F. Iuricich;L. Floriani
地形树是一个新的核心空间索引家族，用于表示和分析不规则三角网（TIN）。地形树联合收割机结合了底层三角形网格的连通性的最小编码和层次空间索引，隐式地表示顶点、边和三角形之间的拓扑关系。在运行时，基于特定的应用需求，在层次索引的每个叶块内本地提取拓扑关系。我们已经开发了一个工具，基于地形树的地形分析，其中包括国家的最先进的估计斜率和曲率，并提取关键点，以及基于拓扑的地形分割和多场地形分析的算法。通过处理从非常大的LiDAR（光，检测和测距）数据集生成的TIN，我们展示了地形树对最先进的紧凑数据结构的有效性和可扩展性。
Terrain trees are a new in-core family of spatial indexes for the representation and analysis of Triangulated Irregular Networks (TINs). Terrain trees combine a minimal encoding of the connectivity of the underlying triangle mesh with a hierarchical spatial index, implicitly representing the topological relations among vertices, edges and triangles. Topological relations are extracted locally within each leaf block of the hierarchal index at runtime, based on specific application needs. We have developed a tool based on Terrain trees for terrain analysis, which includes state-of-the-art estimators for slope and curvature, and for the extraction of critical points, as well as algorithms for topology-based terrain segmentation and multifield terrain analysis. By working on TINs generated from very large LiDAR (Light, Detection and Ranging) data sets, we demonstrate the effectiveness and scalability of the Terrain trees against a state-of-the-art compact data structures.