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BIM 和GIS 的空间语义数据集成方法及应用研究
引用本文:翟晓卉,史健勇. BIM 和GIS 的空间语义数据集成方法及应用研究[J]. 图学学报, 2020, 41(1): 148. DOI: 10.11996/JG.j.2095-302X.2020010148
作者姓名:翟晓卉  史健勇
作者单位:上海交通大学船舶海洋与建筑工程学院,上海 200240
基金项目:上海市科技创新计划项目(15DZ1203403)
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  

Spatial and semantic data integration method and application of BIM and GIS
ZHAI Xiao-hui,SHI Jian-yong. Spatial and semantic data integration method and application of BIM and GIS[J]. Journal of Graphics, 2020, 41(1): 148. DOI: 10.11996/JG.j.2095-302X.2020010148
Authors:ZHAI Xiao-hui  SHI Jian-yong
Affiliation:School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Abstract:With the development of digital city and smart city construction, the integration of buildinginformation modeling (BIM) and geographic information system (GIS) has received much attentionfrom a wide academic circle. The current integration mainly focuses on the conversion of bothgeographic and semantic information between the two data standards, IFC and CityGML, but thereare problems, such as data error and loss, lacking geometric-semantic coherence and poor applicationextensibility. This paper proposed a multi-scale 3D city data model which takes both entity andgeographical objects into account, and studied the extraction, processing and transformation methodof spatial and semantic data of BIM and GIS. Accordingly, the integrated application framework wasdesigned, verifying and preliminarily applied to the 3D visualization platform. It is advantageous inthe realization of a total fusion of BIM and GIS information in terms of geometry, semantics andprecision as well as the avoidance of the information loss caused by the traditional datatransformation. It also has an advantage over the multilevel storage, loading and displaying ofmulti-scale spatial and semantic data and helps to achieve efficient integration of a large scale ofbuilding and city data with high accuracy.
Keywords:building information modeling  geographic information system  IFC  CityGML  dataintegration  
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