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Highly efficient computer oriented octree data structure and neighbors search in 3D GIS spatial

机译:面向计算机的高效八叉树数据结构和3D GIS空间中的邻居搜索

摘要

Three Dimensional (3D) have given new perspective in various field such as urban planning, hydrology, infrastructure modeling, geology etc due to its capability of handling real world object in more realistic manners, rather than two-dimensional (2D) approach. However, implementation of 3D spatial analysis in the real world has proven difficult due to the complexity of algorithm, computational power and time consuming. Existing GIS system enables 2D and two-and-a-half dimensional (2.5D) spatial datasets, but less capable of supporting 3D data structures. Recent development in Octree see more effort to improve weakness of octree in finding neighbor node by using various address encoding scheme with specific rule to eliminate the need of tree traversal. This paper proposed a new method to speed up neighbor searching and eliminating the needs of complex operation to extract spatial information from octree by preserving 3D spatial information directly from Octree data structure. This new method able to achieve O(1) complexity and utilizing Bit Manipulation Instruction 2 (BMI2) to speedup address encoding, extraction and voxel search 700% compared with generic implementation.
机译:三维(3D)因其能够以更现实的方式而不是二维(2D)的方式处理现实世界中的物体而在诸如城市规划,水文学,基础设施建模,地质学等各个领域提供了新的视角。但是,由于算法的复杂性,计算能力和耗时,已证明在现实世界中实施3D空间分析非常困难。现有的GIS系统支持2D和二维半(2.5D)空间数据集,但支持3D数据结构的能力较弱。 Octree的最新发展表明,通过使用具有特定规则的各种地址编码方案来消除对树遍历的需求,可以更加努力地改善八叉树在寻找邻居节点方面的弱点。本文提出了一种新方法,可通过直接从Octree数据结构中保留3D空间信息来加快邻居搜索速度,并消除从八叉树提取空间信息的复杂操作。与通用实现相比,这种新方法能够实现O(1)复杂性,并利用位操作指令2(BMI2)来加速地址编码,提取和体素搜索700%。

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