A Critical Review of the Integration of Geographic Information System and Building Information Modelling at the Data Level

Zhu, Junxiang; Wright, Graeme; Wang, Jun; Wang, Xiangyu

doi:10.3390/ijgi7020066

Volume 7, Issue 2

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A Critical Review of the Integration of Geographic Information System and Building Information Modelling at the Data Level

Junxiang Zhu¹, Graeme Wright², Jun Wang¹ and Xiangyu Wang^1,3,*

Joint Research Centre for Building Information Modelling, School of Built Environment, Curtin University, Bentley 6102, Australia

Faculty of Science and Engineering, Curtin University, Bentley 6102, Australia

School of Civil Engineering, Tongji University, Shanghai 200092, China

Author to whom correspondence should be addressed.

ISPRS Int. J. Geo-Inf. 2018, 7(2), 66; https://doi.org/10.3390/ijgi7020066

Received: 5 February 2018 / Revised: 5 February 2018 / Accepted: 18 February 2018 / Published: 20 February 2018

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Abstract

The benefits brought by the integration of Building Information Modelling (BIM) and Geographic Information Systems (GIS) are being proved by more and more research. The integration of the two systems is difficult for many reasons. Among them, data incompatibility is the most significant, as BIM and GIS data are created, managed, analyzed, stored, and visualized in different ways in terms of coordinate systems, scope of interest, and data structures. The objective of this paper is to review the relevant research papers to (1) identify the most relevant data models used in BIM/GIS integration and understand their advantages and disadvantages; (2) consider the possibility of other data models that are available for data level integration; and (3) provide direction on the future of BIM/GIS data integration. View Full-Text

Keywords: Building Information Modelling (BIM); Geographic Information System (GIS); integration; data interoperability

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Zhu, J.; Wright, G.; Wang, J.; Wang, X. A Critical Review of the Integration of Geographic Information System and Building Information Modelling at the Data Level. ISPRS Int. J. Geo-Inf. 2018, 7, 66.