Integration of 3DGIS and BIM and its application in visual detection of concealed facilities

ABSTRACT

The multi-level modeling technology of Building Information Modeling (BIM), combined with Three-dimensional Geographic Information System (3DGIS) macro-scene visualization technology and location information, can realize the transmission of decentralized information from various disciplines to multi-disciplinary collaborative information sharing services. It can be applied independently for the whole life cycle, which plays a positive role in reducing the cost and improving the efficiency of engineering planning, design, construction, operation, and maintenance. In this paper, the data integration and function integration methods of 3DGIS and BIM are designed. In order to avoid the breaking problems caused by attribute information loss and excessive simplification in the process of BIM data integration, the attribute mapping between 3DGIS and BIM based on Industry Foundation Classes (IFC) and City Geography Markup Language (CityGML) and the data simplification method considering the geometric characteristics of BIM are designed. By setting the relevant preconditions and thresholds of patch merging, on the premise of maintaining the structural characteristics of BIM data surface, reduce the amount of model data to improve the efficiency of BIM data loading, rendering and display effect in 3D geospatial scene. Through the data and function integration of 3DGIS and BIM, we can effectively manage the data of large-scale model, and calculate and obtain the geospatial location and direction of key parts of buildings through the coordinate transformation of BIM, which can effectively assist the rapid and accurate positioning of BIM in virtual 3D scene and expand the visualization ability of 3DGIS. By effectively integrating 3DGIS and BIM, this paper gives full play to the spatial management advantages of 3DGIS and the component management advantages of BIM. The rationality and operability of the method are verified by its application in the operation and maintenance management project of concealed facilities in actual buildings.

KEYWORDS:

• Three-dimensional geographic information system (3DGIS)
• building information modeling (BIM)
• integration
• concealed facilities
• visual detection

1. Introduction

A Three-dimensional Geographic Information System (3DGIS) has several advantages, including big data capacity, intuitive spatial relation expression, and strong spatial analysis ability; therefore, it has been widely applied to space management, macro-planning, decision-making, and other fields. When using 3DGIS to manage the 3D building model in practical applications, both outdoor and indoor spatial objects need to be managed to realize integrated indoor and outdoor expression. However, 3DGIS can only express the outside surface of real buildings using skin or solid models that have elevation information but cannot effectively express the inner structural information of building objects. Therefore, the traditional 3DGIS focuses more on visual applications and most of them merely target the aspects of browsing, viewing, and simple spatial statistics and analysis. Among these aspects, spatial analysis and its research only focus on the outdoor aspect, which limits the evolution of 3DGIS to the micro world.

Building Information Modeling (BIM) can integrate a building’s graphical and non-graphical information and present it through virtual 3D scenes. In addition, BIM can reduce information transfer loss during the building’s all stages. BIM generally focuses on single engineering projects or single buildings and pays attention to the management and expression of micro and detailed information, but it lacks overall planning and unified management. When applied to the management of multiple long-term projects, such as city-class large-scale regions and roads, railways, tunnels, water, and electricity, it cannot realize unified management, visualization, and analysis of all the BIM data. Currently, BIM is more frequently applied to planning, designing, and construction supervision stages rather than the operation and maintenance stages. However, in the whole life cycle of building, BIM only has several years of use in planning, designing, and construction supervision. In fact, the operation and maintenance of a building last the longest. If BIM is not fully applied to the operation and maintenance stages, then once the project is accomplished and received, the generated BIM data will become “data fossil”.

The integration of 3DGIS with BIM is an important direction of multiple dimensional applications, and it has become a hot topic of research in academic and industrial circles (Zhu, Li, and Lin 2018). 3DGIS provides professional spatial positioning; inquiry; analysis ability at the macrogeographical environment level; and can solve the difficulties of BIM, such as being unable to position the spatial location, united management, and decision-making and prediction. 3DGIS can satisfy the application demands that arise when combining large-scale scenes and indoor refined scenes, and it can also deeply discover the application value of BIM on the building’s whole life cycle. Meanwhile, BIM has solved the technical bottleneck due to the difficulties of 3DGIS in expressing the micro world. Based on BIM, the specific description for building information, unifying and effectively organizing the indoor, outdoor, beneath the ground, and above the ground spatial 3D data can expand 3DGIS’s visual function to indoors or beneath the ground so as to realize the integrated roaming from indoor to outdoor or from above the ground to beneath the ground. In addition, it can improve the management ability of 3DGIS’s visualization and integration. The combination of BIM’s multilevel refined modeling technology and 3DGIS macro scene’s visualization technology with location information can transfer the scattered information from individual disciplines to a multiple discipline synergetic information sharing service and transfer the stage-independent application to a whole life cycle service. It has played a great role in reducing the cost and improving the efficiency of project planning, designing, construction, operation, and maintenance. Therefore, it can provide strong and comprehensive technical support for decision-making at different stages and for different requirements.

2. Analysis of the current state of 3DGIS and BIM integration

In reviewing the development processes of 3DGIS and BIM, it can be discovered they are almost the same: both were developed from manual drawings (3DGIS is a map and BIM is an engineering drawing) for automation and 3D visualization via computer technology (Liu et al. 2017). 3DGIS and BIM have a natural similarity, but they are no substitute for each other; rather, they tend to be complementary. 3DGIS reflects the real world while BIM constructs it. The logic and implementation processes of both are reciprocal. BIM is a process from zero to one, that is, the process is from the human brain to the entity. 3DGIS is a process from reality to virtualization, that is, the process from the entity to the human brain (spatial cognition to the real world). The integration of the two forms a closed loop; therefore, the integration of them is necessary and operable.

To realize the integration of 3DGIS with BIM, data bridges between 3DGIS and BIM need to be established for data integration, including the unification of multiple BIM data and the transformation of the coordinate system, as well as the integration of standards. Furthermore, functional connectivity between the two systems needs to be set up. This requires using BIM to integrate and manage all stages’ information of the building; using 3DGIS to integrate and manage the external geographical environment information; and interchanging and interoperating the BIM information in a micro field with the 3DGIS information in the macro field to satisfy the functions of 3D spatial information query, analysis, and management. There have been many studies on data integration between 3DGIS and BIM. One of the highly recognized methods is using Industry Foundation Classes (IFC) and City Geography Markup Language (CityGML) to realize data integration. This method has stronger generality and less workload compared to the traditional method that directly transforms BIM data to corresponding data on the GIS platform or directly transfers the GIS data to the BIM platform. Based on IFC and CityGML standards, Tang, Zhu, and Zhao (2014) proposed IFC geometric feature filtering method and semantic mapping rules from IFC to CityGML, providing a common means for geometric and semantic information interoperability between IFC and CityGML building models; Laat and Berlo (2011) proposed GeoBIM, an extension mode of CityGML, and used GeoBIM to transform IFC into CityGML; Kang and Hong (2015) proposed an architecture of BIM/GIS-based information Extract, Transform, and Load (BG-ETL), using ETL concept to realize data integration between BIM and GIS; Karan, Irizarry, and Haymaker (2016) used semantic web technology to realize semantic interoperability between BIM and GIS by building ontology database, semantic integration and heterogeneous information source query; Liu, Liu, and Li (2016) put forward IFC and CityGML data conversion framework of BIM and GIS integration; Zhu and Deng (2016) proposed a method based on semantic mapping to transform geometric and semantic information from IFC to CityGML; Deng, Cheng, and Anumba (2016) developed an ontology library of city semantic model, and used the example based method to generate mapping rules based on the same components of the same entity in the same model. Hajji et al. (2021) proposed an integrated approach based on BIM and 3DGIS for the implementation of a 3D cadastre in Morocco. This approach demonstrates the relevance of such integration for the efficient management of cadastral information. The functional integration of 3DGIS with BIM mainly contains data management and visualization integration. BIM is used to integrate and manage whole stage information of the building; 3DGIS is used to integrate and manage the building’s external environment spatial information; and the micro BIM information is interchanged and interoperated with the macro 3DGIS information to satisfy the functions of 3D spatial information browsing, query, analysis and management, and to realize the functional connectivity of the two systems (Atazadeh et al. 2021; Borrmann et al. 2015; Boguslawski et al. 2015; Dold and Groopman 2017; Kim et al. 2011; Guo et al. 2016; Ehrlich and Blankenbach 2019). Yang and Kuang (2016) proposed that the data storage and display fusion of 3DGIS and BIM is the key problem of their integration; Ni and Wang (2015) studied the integration of 3DGIS and BIM in the process of model browsing in large-scale terrain scene and viewpoint unification in local independent coordinate system; Emamgholian, Taleai, and Shojaei (2021) designed a 3D proximity analysis and implemented to determine Rights, Restrictions, and Responsibilities (RRRs) and associated easement rights in non-topology-based data structures; Zhou et al. (2017) designed the integration method of visualization and spatial analysis functions of 3DGIS and BIM. Dangermond and Goodchild (2020) elaborated on the concept of geospatial infrastructure, and argued that it is essential if geospatial technology is to contribute to the solution of problems facing humanity. Noardo et al. (2020) investigated the application of georeferencing to IFC models and making consistent conversions between 3D city models and BIM, considering the Open Geospatial Consortium (OGC) CityGML and building SMART IFC as reference standards.

3. Proposed method for integrating 3DGIS and BIM

3.1. Data integration of 3DGIS and BIM

As shown in Figure 1, there are two aspects included in 3DGIS and BIM data integration: geometric data integration and attribute data integration. Existing data integration methods often pay attention to the corresponding transformation of attributes in the integration process, but there is less research on the data simplification of maintaining the characteristics of the model. BIM data are generally fine, large in volume and many components. There are problems such as low loading speed, low rendering efficiency, and system memory corruption in the process of visualization and integration management. In the process of data integration between 3DGIS and BIM, it is necessary to realize the BIM data that can browse and manage large-scale model data smoothly while retaining the geometric features and necessary attribute information of the BIM. In the proposed data integration method of 3DGIS and BIM, geometric data integration contains integration of an object’s spatial location coordinate data, that is, the unification of the coordinate system and projective mode and so on, as well as data simplification. Attribute data integration contains a projection of the 3DGIS and BIM objects at different levels, and transformation of the model’s construction parameters, materials, textures, and so on. After BIM data transformation, during geometric simplification of the CityGML data, the neighboring three-point method and triangular facet are merged to realize the simplification of the borderline and triangular facet.

Figure 1. 3DGIS and BIM data integration.

In the process of BIM modeling, the user-defined independent coordinate system in line with the actual situation is generally used to facilitate the follow-up construction, such as the local coordinate system. 3DGIS has many data sources and different collection methods, and the coordinate system used also has some differences. The integrated application of BIM and 3DGIS faces the problem that their coordinate systems are different and cannot be matched. In the process of data integration, it is necessary to transform the coordinate of the BIM data in order to load the BIM into the real position of the 3D scene (As shown in Figure 2),

1. For the case of known BIM engineering coordinate system, the actual geographic location of BIM is obtained by solving from engineering coordinate to geographic coordinate.

2. For the case that the coordinate system can’t be verified after several changes of BIM, because the engineering coordinate system mostly adopts rectangular coordinate system, the 7-parameter transformation method (including bursa model, one-step model, Helmert model, etc.) can be used to calculate the translation parameters, rotation parameters and scale factor through the control points, and then the BIM coordinate transformation can be carried out, That is, select more than three control point pairs (feature point pairs) evenly, correct the model coordinates through feature point matching, and obtain the actual geographic location of BIM.

Figure 2. Coordinate transformation of BIM model. (a) BIM data. (b) The constructed real 3D scene. (c) Loading BIM into 3D scene.

A data simplification method considering the geometric features of BIM model is designed based on the combination of adjacent three-point method and triangular grid patch, and considering the simplification of boundary line and triangular patch, in order to effectively avoid the problem that the original geometric features cannot be maintained after the geometric data simplification of BIM data, and there are broken faces. Among them, the simplification of the borderline is performed through the neighboring three-point method. Each vertex is marked clockwise starting from a random vertex on the borderline. From the starting point, any three neighboring points on the polygon borderline are successively selected as an analysis unit. The angle between the formed two straight lines is calculated. When the angle is larger than or equal to a threshold, it is thought these three points are collinear and the middle point is deleted; then, the process is restarted from the first point. When the angle is less than the threshold, no operation is needed, and the process is continued from the second point. For the triangular facet simplification, the angle between two neighboring edge-sharing triangular facets is used to judge if these two triangular facets are coplanar. When the angle is less than a threshold, these two triangular facets are considered as coplanar and marked; then, the marked triangular facets are continuously estimated and marked. Triangular facets marked as coplanar are merged by selecting a benchmark projective plane, and a new facet is formed by connecting the vertexes of the merged facet. All triangular facets are traversed until all the triangular facets are estimated. For the unmarked triangular facets after traversing, no operation is needed. The specific implementation steps are as follows (as shown in Figure 3):

Figure 3. Flow chart of triangular facet merging simplification.

Step 1: Mark all triangular facets as 0.

Step 2: Count the number of triangular facets marked as 0 is $N_0$. If $N_0=0$, terminate the triangular facet merging and simplification; if $N_0>0$, any triangular facet marked with 0 is selected as the seed facet $\mathit{A}$, marked as 1.

Step 3: Identify the three vertices of the seed facet clockwise.

Step 4: Obtain a facet $A_i\left(\mathit{i}=1,2,\cdots ,\mathit{n}\right)$ adjacent to the seed facet $\mathit{A}$ and marked as 0, where $\mathit{n}$ is the number of facets.

Step 5: Calculate the angle ${\theta }_i$ between the seed facet $\mathit{A}$ and the adjacent triangular facet $A_i$.

Step 6: Determine the relationship between the angle ${\theta }_i$ (shown in Figure 4) and the face merge threshold. If ${\theta }_i\le$ threshold, it is determined that the triangular facet $A_i$ is coplanar with the seed facet $\mathit{A}$, and Step 7–9 is performed; if ${\theta }_i>$ threshold, it is judged that the triangular facet $A_i$ and the seed facet $\mathit{A}$ are not coplanar, then the next triangle is determined (i++), go to Step 5. If the adjacent triangles are judged, Count the number of triangular facets marked 1 is $\mathit{N}$. If $\mathit{N}=1$, the seed facet $\mathit{A}$ is remarked to 2, go to Step 2; if $\mathit{N}>1$, go to Step 10–13.

Figure 4. Definition of angle between triangular facets.

Step 7: Mark $A_i$ as 1, and obtain the identifier of the two ends of the adjacent side of the triangular facet $A_i$ and $\mathit{A}$.

Step 8: If the identifiers of the endpoints are connected, insert another vertex of the triangular facet $A_i$ between the two ends of the adjacent edge; if not, identify the other vertex of $A_i$ as the value that is equal to the large value of the two endpoint identifiers of adjacent edges plus 1.

Step 9: Jump to Step 2.

Step 10: Project all the triangular facet vertices marked 1 to the plane where the seed facet $\mathit{A}$ is located.

Step 11: Mark all the projection points according to the original vertex identifier.

Step 12: Sequentially connect according to the projection point identification order, and construct the merged polygon.

Step 13: Mark the reconstructed polygon as 2 and jump to Step 2.

When building the attribute information mapping relationship between 3DGIS and BIM, combined with the characteristics that IFC model and CityGML model are semantic information models, information transfer is carried out by establishing semantic mapping. The IFC overall model is decomposed into multiple model elements, and semantic mapping is established with CityGML to transfer and share IFC model spatial information to CityGML. Firstly, the attribute concepts in CityGML and IFC are normalized; Then, based on the semantic mapping relationship between IFC LOD100 and CityGML LOD 2, IFC LOD 200 and CityGML LOD 3, IFC LOD 300 and CityGML LOD 4 in the data integration platform FME, it is extended and improved, and the corresponding relationship between CityGML and IFC classes is defined; Finally, the semantic mapping library between CityGML and IFC is constructed by defining class attributes and creating instances, as shown in Figure 5. Based on the FME workbench development platform, in order to ensure the integrity of information in the process of transmission, IFC model is divided into five model elements: point, line, area, material and color, and semantic mapping is established with CityGML model elements, respectively.

Figure 5. Construction of semantic mapping library between CityGML and IFC based on FME.

3.2. Functional integration of 3DGIS and BIM

BIM reduces the loss of information in the process of building transmission by establishing information flow model. How to integrate the information visualization and management functions of BIM and 3DGIS, effectively store and manage the information of BIM in each stage and the spatial information of external geographical environment of 3DGIS, so as to realize the macro-micro, indoor-outdoor, ground-underground integration seamless roaming, as well as the whole life cycle and spatial management of information, is the key to realize the functional integration of 3DGIS and BIM, as shown in Figure 6.

Figure 6. Key technologies for 3DGIS and BIM functional integration.

In the process of visualization functional integration of 3DGIS and BIM, the key technologies involved include precise matching of BIM and 3DGIS terrain, LOD construction of BIM data and collision roaming technology. In the aspect of data management functional integration, by referring to the process information attribute items defined in Construction Operations Building Information Exchange (COBie) at different stages, it is first converted into IFC format files, and the BIM process information database table structure is designed, the stage identification attribute items are added, and the BIM process information is stored in the database; then, the process attribute information, BIM geometry information, model semantics, topology, appearance attribute and so on are carried out. Finally, two-way query from model to attribute and attribute to model is realized by linking attribute information with model object. On the one hand, it is convenient to select and delete process information in stages in the process of subsequent BIM lightening; on the other hand, it can fully discover the potential value of BIM and assist the decision analysis by realizing the integration of the core value of BIM information – life cycle process information and 3DGIS.

4. Experimental analysis

Through the application in the actual operation and maintenance project of building concealed facilities, the effectiveness and feasibility of the integration method of 3DGIS and BIM proposed in this paper are verified. In this application process, through the integration of 3DGIS and BIM, give full play to the space management advantages of 3DGIS and the component management advantages of BIM, realize the effective management of building concealed facilities and convenient and efficient visual detection to provide technical support for the further realization of building intelligent operation and maintenance.

4.1. Experimental data

Presently, many big designing institutes are promoting 3D design, and an increasing number of BIM achievements are available. The large number of BIM with high accuracy can be regarded as an important data source of 3DGIS. In this paper, the experimental data came from the building LOD300 data generated by Revit by Changjiang Institute of Survey, Planning, Design and Research. The surrounding geographical environment data of the institute’s building was acquired through the inclined image data shot by an unmanned aerial vehicle, with an accuracy of 5 cm.

4.2. Experimental process and result analysis

For a building in the experimental data (as shown in Figure 7), the data simplification method considering the geometric characteristics of BIM proposed in this paper is used for processing, and the patch merging threshold is set to 10°, and the included angle threshold of collinearity of adjacent three points is set to 160°. After merging and simplifying the borderline and triangular facets, the original data amount was reduced from 1948 kB to 253 kB, and the simplified data have little difference with the original data on visual effect, which can entirely satisfy the practical visual requirements. In addition, the data amount was compressed to around one-eighth of the original amount of data.

Figure 7. A comparison of visual effects before and after data simplification.

In order to more clearly illustrate the advantages of the data reduction method designed in this paper considering the geometric characteristics of BIM compared with the existing BIM reduction methods, the reduction effect of BIM data of doors and windows of unloading room in the experimental data is compared, as shown in Figure 8.

Figure 8. Comparison of BIM data simplification effect.

In the process of building concealed facilities detection, virtual building facilities components and physical space entities need to be located together, which involves the problems of location tracking, location tracking and proportion. At present, the accuracy of building facilities component level positioning cannot meet the needs of practical application. Therefore, it is necessary to design a method to assist the accurate positioning of building concealed facilities. Through the BIM data coordinate conversion method designed in this paper, the BIM is loaded into the real three-dimensional scene, so as to obtain the geospatial location and orientation information of key parts of the building, and realize the collaborative and accurate positioning of building facility components and physical spatial entities (as shown in Figure 9).

Figure 9. Visualization of the underground hidden pipeline information.

From the above results, the following can be observed

1. In this paper, the three-point method is used to quickly simplify the triangular patch and boundary of the geometric data of BIM. Through the judgment of the shape after merging, the original geometric features of BIM can be retained, which effectively avoids the problem of failure to maintain the original geometric features and surface breaking after simplifying the geometric data of BIM.

2. Through BIM data simplification, attribute information mapping of BIM and 3DGIS based on IFC and CityGML, and functional integration of 3DGIS and BIM, it can smoothly browse and manage large-scale model data while retaining the geometric features and necessary attribute information of BIM, which can effectively solve the high requirements for computer hardware caused by the large amount of BIM data, and it is easy to cause the program to get stuck and crash.

3. Through the coordinate transformation of BIM, the geospatial position and direction of key parts of buildings are calculated and obtained, which can effectively assist the rapid and accurate positioning of BIM in virtual 3D scene.

5. Conclusion

In this paper, the data integration and function integration methods of 3DGIS and BIM are designed. In order to avoid the breaking problems caused by attribute information loss and excessive simplification in the process of data integration, the attribute mapping between 3DGIS and BIM based on IFC and CityGML, and the data simplification method considering the geometric characteristics of BIM are designed. By setting the relevant preconditions and thresholds of patch merging, On the premise of maintaining the structural characteristics of BIM data surface, reduce the amount of model data to improve the efficiency of BIM data loading, rendering and display effect in 3D geospatial scene. Through the data and function integration of 3DGIS and BIM, we can effectively manage the data of large-scale model, and calculate and obtain the geospatial location and direction of buildings through the coordinate transformation of BIM, which can effectively assist the rapid and accurate positioning of BIM in virtual 3D scene and expand the visualization ability of 3DGIS. The rationality and operability of this method are verified by its application in the operation and maintenance management project of concealed facilities in actual buildings.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author, [Mingxia Xie, E-mail: [email protected]], upon reasonable request https://figshare.com/s/b1505733c79b703659bc.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work is supported by the Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources [grant number KF-2018-03-050], and China Postdoctoral Science Foundation [grant number 2018M642800].

Notes on contributors

Xiaoyu Wang

Xiaoyu Wang received her master degree from the University of Queensland. Her research interests are geospatial data analysis and remote sensing.

Mingxia Xie is a senior engineer of Changjiang institute of survey, planning, design and research. She received her PhD degree from Wuhan University. Her research interests are geospatial data and BIM processing and analysis.