欢迎访问《图学学报》 分享到:

图学学报

• 建筑与城市信息模型 • 上一篇    下一篇

BIM 和GIS 的空间语义数据集成方法及应用研究

  

  1. 上海交通大学船舶海洋与建筑工程学院,上海 200240
  • 出版日期:2020-02-29 发布日期:2020-03-11
  • 基金资助:
    上海市科技创新计划项目(15DZ1203403)

Spatial and semantic data integration method and application of BIM and GIS

  1. School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
  • Online:2020-02-29 Published:2020-03-11

摘要: 随着数字城市和智慧城市的建设发展,建筑信息模型(BIM)和地理信息系统(GIS)
的集成被广泛研究和应用。目前的集成研究主要是通用数据标准IFC 和CityGML 之间的空间和
语义转换,但由于应用领域和空间尺度等差异,存在信息错误和丢失、几何语义信息耦合度低、
应用拓展性差等问题。为此提出了一种兼顾三维实体对象和地理空间对象的三维城市数据模型,
研究了BIM 和GIS 的空间和语义数据的提取、处理和转换方法,设计了BIM 和三维GIS 的集
成应用框架并在三维可视化平台上进行验证和初步应用。该方法可实现BIM和GIS 信息在几何、
语义、精度上的完全融合,避免了传统的数据转换带来的信息缺失,在多尺度的空间和语义信
息分级存储和加载显示方面存在着优势,有利于实现大规模、高精度的建筑和城市信息的高效
集成。

关键词: 建筑信息模型, 地理信息系统, IFC, CityGML, 数据集成

Abstract: With the development of digital city and smart city construction, the integration of building
information modeling (BIM) and geographic information system (GIS) has received much attention
from a wide academic circle. The current integration mainly focuses on the conversion of both
geographic and semantic information between the two data standards, IFC and CityGML, but there
are problems, such as data error and loss, lacking geometric-semantic coherence and poor application
extensibility. This paper proposed a multi-scale 3D city data model which takes both entity and
geographical objects into account, and studied the extraction, processing and transformation method
of spatial and semantic data of BIM and GIS. Accordingly, the integrated application framework was
designed, verifying and preliminarily applied to the 3D visualization platform. It is advantageous in
the realization of a total fusion of BIM and GIS information in terms of geometry, semantics and
precision as well as the avoidance of the information loss caused by the traditional data
transformation. It also has an advantage over the multilevel storage, loading and displaying of
multi-scale spatial and semantic data and helps to achieve efficient integration of a large scale of
building and city data with high accuracy.

Key words: building information modeling, geographic information system, IFC, CityGML, data
integration