三维海量点云数据的组织与索引方法  

Organization and Indexing Method for 3D Points Cloud Data

作　　者：路明月[1] 何永健[1] 

机构地区：[1]南京信息工程大学遥感学院,南京210044

出　　处：《地球信息科学》2008年第2期190-194,共5页Geo-information Science

基　　金：虚拟地理环境教育部重点实验室开放基金(2007VGE02)资助

摘　　要：三维点云是三维GIS重要的数据来源,也是三维GIS对地学空间对象、现象进行表达、描述以及建模的重要手段。点云数据的高效组织是对其进行各种分析处理的基础,为此本文在对三维坐标点按照一定的规则进行排序的基础上,采用规则空间八叉树与平衡二叉树相结合的嵌套复合结构进行组织,大大加速了三维点数据基于坐标的查询检索,为海量点云数据的进一步分析操作奠定了基础。最后,文中对该复合组织结构进行了内外存相统一的设计与实现,并验证了该方法的正确性及有效性。Being the primary data source, 3D points cloud is also an important means to describe and express the geographic objects and phenomena in 3D GIS as well as to perform model building. And the effective organization of the points is the basis for its operation and analysis. Therefore, in this paper, 3D points are arranged and sorted according to a specified rule, and then organized by a compound structure of spatial octree and balanced binary tree, which greatly speeds up the query process based on the 3D coordinate, and lays a solid foundation for the further analysis of 3D points data. This paper also unifies the compound structure in both memory and database. And a case study has proved its validity.

关 键 词：三维海量点云 三维GIS 空间数据组织 复合组织结构 

分 类 号：P208[天文地球—地图制图学与地理信息工程] TP391.41[天文地球—测绘科学与技术]