应申, 郭仁忠, 靳凤攒, 朱利平, 李威阳. 利用CityGML模型自动构建三维封闭建筑体[J]. 武汉大学学报 ( 信息科学版), 2018, 43(5): 732-738. DOI: 10.13203/j.whugis20150556
引用本文: 应申, 郭仁忠, 靳凤攒, 朱利平, 李威阳. 利用CityGML模型自动构建三维封闭建筑体[J]. 武汉大学学报 ( 信息科学版), 2018, 43(5): 732-738. DOI: 10.13203/j.whugis20150556
YING Shen, GUO Renzhong, JIN Fengzan, ZHU Liping, LI Weiyang. Auto-Construction of 3D Colsed Buildings from CityGML LoD3[J]. Geomatics and Information Science of Wuhan University, 2018, 43(5): 732-738. DOI: 10.13203/j.whugis20150556
Citation: YING Shen, GUO Renzhong, JIN Fengzan, ZHU Liping, LI Weiyang. Auto-Construction of 3D Colsed Buildings from CityGML LoD3[J]. Geomatics and Information Science of Wuhan University, 2018, 43(5): 732-738. DOI: 10.13203/j.whugis20150556

利用CityGML模型自动构建三维封闭建筑体

Auto-Construction of 3D Colsed Buildings from CityGML LoD3

  • 摘要: 给出了利用CityGML模型自动构建三维封闭建筑体的基本框架和流程。充分利用已有的CityGML数据,分析其与三维封闭建筑体的语义关联和差别,奠定利用CityGML构建三维封闭建筑体的理论基础;从构建三维封闭建筑体所需几何数据出发,根据语义关联从CityGML中提取相应的几何数据,构建符合三维封闭建筑体要求的几何对象,满足三维立体规划和审批、核查的空间数据需要,进而弥补传统地籍数据采集方式的不足。

     

    Abstract: The development of 3D space planning and management strongly require 3D data to support volumetric representation of 3D space. This paper aims to construct 3D closed building from building information with CityGML LoD3 data and provides the framework and workflow that how to transform and construct 3D closed buildings from CityGML LoD3 data step by step. The semantic objects between 3D property unit and building information are quite different and the 3D space they describe and represent are thorough different. According to the requirement of the geometry of 3D cadastral objects, semantic relationships and object correspondences between CityGML LoD3 and 3D closed building are calibrated. Based on these, the paper gives the methods to extract the geometry data from CityGML and recombines the data to enclose the 3D closed building that satisfy certain 3D geometric rules. The approach in this paper develops a space transformation idea way to construction 3D property unit from building information and can make up the deficiency of the traditional acquisition methods for 3D cadastre.

     

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