地球信息科学学报 ›› 2015, Vol. 17 ›› Issue (12): 1442-1449.doi: 10.3724/SP.J.1047.2015.01442

• 地球信息科学理论与方法 • 上一篇    下一篇

三维城市模型数据划分及分布式存储方法

李朝奎(), 严雯英, 杨武, 陈果   

  1. 1. 湖南科技大学 地理空间信息技术国家地方联合工程实验室,湘潭 411201
    2. 湖南科技大学 地理空间信息湖南省工程实验室,湘潭 411201
  • 收稿日期:2014-07-15 修回日期:2015-07-26 出版日期:2015-12-20 发布日期:2015-12-20
  • 作者简介:

    作者简介:李朝奎(1967-),男,博士,教授,研究方向为三维GIS建模及应用。E-mail: chkl_hn@163.com

  • 基金资助:
    国家自然科学基金项目(41271390、41571374);卫星测绘技术与应用国家测绘地理信息局重点实验室开放基金 项目(KLAMTA-201406)

Research on Three Dimensional City Model Data Partitioning and Distributed Storage

LI Chaokui*(), YAN Wenying, YIN Zhihui, CHEN Guo   

  1. 1. National-Local Joint Engineering Laboratory of Geo-Spatial Information Technology, Hunan University of Science and Technology, Xiangtan 411201, China
    2. Hunan Province Engineering Laboratory of Geospatial Information, Hunan University of Science and technology, Xiangtan 411201, China
  • Received:2014-07-15 Revised:2015-07-26 Online:2015-12-20 Published:2015-12-20
  • Contact: LI Chaokui E-mail:chkl_hn@163.com
  • About author:

    *The author: CHEN Nan, E-mail:fjcn99@163.com

摘要:

随着信息获取技术的快速发展,地理信息数据每天以TB级的数量增加。三维城市模型数据作为三维GIS的重要内容,在数字城市和智慧城市建设过程中发挥重要作用。由于三维城市模型数据结构复杂,其数据量具有海量性,因此,高效地对三维城市模型进行划分及存储,以满足数据的长效管理及三维GIS系统的快速可视化数据调度和空间辅助决策需求,成为近年的研究热点。以往的数据划分方法导致划分区域在数据调度中变化频繁,使数据更新和管理变得困难,需寻找一种更为稳定且具有普适性的数据划分方法。本文分析了现有三维城市模型数据划分方法的不足,提出了基于拓扑关系模型的大比例尺图幅划分方法,并对划分后三维模型数据进行统一命名编码;借助非关系数据库MongoDB强大的海量数据组织及高效的多并发访问功能,构建了MongoDB分片集群服务器;对三维城市模型数据进行了单元划分,并采用规则建模软件City Engine进行建模,得到三维城市模型,借助非关系数据库软件MongoDB进行数据存储实验。结果表明,基于拓扑关系模型的大比例尺图幅划分方法适用于三维城市模型数据划分,划分后数据的存储效率明显提高,MongoDB数据库的多并发访问效率具有良好的稳定性。

关键词: 三维城市模型, 数据划分, 空间拓扑, 空间数据库, MongoDB

Abstract:

With the rapid development of information acquisition technology, the geographic information data is increasing at the magnitude of terabyte every day. As an important content of 3D GIS, 3D city model data plays an important role in the construction of digital city and smart city. Because the data structure of 3D city model is complex and the data volume is huge, how to efficiently divide and store large amount of 3D city model data in order to meet the long-term management of data, the rapid visualization of data scheduling and the requirement of spatial assistant decision-making of 3D GIS system, has become a research hotspot in recent years. Previous data partitioning methods have caused the changes of zoning frequently in the data scheduling, which makes the update and management of data become more difficult. So, it is necessary to find out a more stable and universal data partitioning method. In this paper, based on the research of the shortcomings for the existing 3D city model data partitioning methods, we proposed the large scale map partition method based on topology relation model, and then we designed a unified name encoding scheme for the 3D models data after splitting. With the help of the powerful massive data organization and efficient multiple concurrent access function of the non-relational database MongoDB, a MongoDB sharded cluster server is constructed. The 3D city model data was used in unit division, and the rules modeling software City Engine was applied to processing the divided units, thus producing the 3D city model. Afterwards, MongoDB was used for data storage experiments. The results show that the large scale map partition method based on topology relation model is capable and sutable for the data partition of 3D city model, and the storage efficiency of the divided data is obviously improved. Moreover, the MongoDB database has a good stability on multiple concurrent access.

Key words: 3DCM, data partition, spatial topological relations, spatial database, MongoDB