Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1
Cesar Alejandro Carrasco Payero
 -- 3091 2022-11-08 12:41:25 |
2 format corrected.
Beatrix Zheng
 Meta information modification 3091 2022-11-09 03:27:40 | |
3 format corrected.
Beatrix Zheng
 + 9 word(s) 3100 2022-11-09 03:30:06 |

Video Upload Options

Do you have a full video?
Send video materials Upload full video

Confirm

Are you sure to Delete?
Yes No
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Carrasco, C.A.;  Lombillo, I.;  Sánchez-Espeso, J.M.;  Balbás, F.J. GIS and BIM and HBIM Integration. Encyclopedia. Available online: https://encyclopedia.pub/entry/33529 (accessed on 27 July 2024).
Carrasco CA,  Lombillo I,  Sánchez-Espeso JM,  Balbás FJ. GIS and BIM and HBIM Integration. Encyclopedia. Available at: https://encyclopedia.pub/entry/33529. Accessed July 27, 2024.
Carrasco, César A., Ignacio Lombillo, Javier M. Sánchez-Espeso, Francisco Javier Balbás. "GIS and BIM and HBIM Integration" Encyclopedia, https://encyclopedia.pub/entry/33529 (accessed July 27, 2024).
Carrasco, C.A.,  Lombillo, I.,  Sánchez-Espeso, J.M., & Balbás, F.J. (2022, November 08). GIS and BIM and HBIM Integration. In Encyclopedia. https://encyclopedia.pub/entry/33529
Carrasco, César A., et al. "GIS and BIM and HBIM Integration." Encyclopedia. Web. 08 November, 2022.
GIS and BIM and HBIM Integration
Edit
This entry is adapted from the peer-reviewed paper 10.3390/buildings12101672

3D virtual management is a topic of growing interest. The AEC industry is undergoing a real revolution because of the technological changes that are taking place. Synchronized 3D visualization is one of the tools being deployed at an accelerated pace. This, together with collaborative work, contributes to optimal management for all stakeholders. The integration of geographic information systems and building information modeling and heritage building information modeling (BIM) is one of the most innovative concepts; it enables the generation of collaborative, fluid systems. 

building information modeling BIM heritage building information modeling HBIM

1. Technical Progress

The technical progress regarding the integration of geographic information systems (GIS)  and building information modeling (BIM) and HBIM models is based on 3D representation and interoperability. In what follows, aspects related to file formats, 3D model geometry and its semantics, data, and the internet of things are developed.

1.1. File Format

In GIS and in BIM and HBIM environments there are many formats for storing 3D geometry. Among others, the formats proposed by European Directive 2007/2/CE for the Infrastructure for Spatial Information in Europe (INSPIRE) are available [1][2], namely gbXML, Open Geospatial Consortium (OGC) [3][4], LandInfra, and IFC. Among these, the most recognized and widely used open standard in GIS is the one issued by the OGC, the “City Geography Markup Language (CityGML)”; in BIM, they are IFC formats [5].
The CityGML format is an open, standardized geometry model based on XML [1][4][6]. This format is still suitable for GIS and BIM integration because of its data interchangeability [7]. It is the most widely used international standard for storing and exchanging three-dimensional city models with semantics [8][9][10][11] in the geospatial domain [2]. The CityGML core module defines the basic concepts and components of the data model; therefore, it is unique and must be implemented by any system.
The IFC standard has been developed by building smart [1] as an open international standard for BIM [9]. It is a standard and interoperable format that is object oriented and capable of representing objects semantically [12]. It serves as an exchange format between different platforms, allowing BIM models to preserve all the details that are integrated in that model [5][10].
There are still many problems and technical barriers related to integration; the fundamental one is the recognition of the nature that characterizes a project when the researchers try to link a BIM model (IFC) and a GIS model (cityGML), causing loss of information. The reality is that an IFC file, by itself, does not contain all the information of the model from which it was extracted, and, additionally, there is a difference in the nature of the BIM and GIS models; that is, a BIM model is structured with geometric figures whose representation depends directly on parameters (width, length, thickness, texture, etc.)—a quite light model; on the other hand, the GIS model is made up of meshes (junctions of points/triangulations) that, although quite flexible, have the disadvantage that a triangulation represents more than one element of the model, which makes the individualized treatment of the characteristics of an element impossible. Additionally, the file is weighty because of the amount of information that needs to be managed to generate the mesh. It is therefore necessary to continue working on an intermediate mechanism between the two types of models to achieve an integration that enables both models to interact under a nature common to both.

1.2. Geometry of the 3D Model and Its Semantics

In the GIS and BIM and HBIM integration, the geometry of the model is directly defined with its semantics. The semantics refers to the levels with which the 3D model is represented in the different preforms. These levels are parameters to measure the degree of semantics of the objects. They are divided into LOD (levels of detail)—more often referred to as “LoD” with lowercase “o”—for a GIS system, LOD (levels of development) for a BIM element, and LOK (levels of knowledge) in HBIM. The latter arise from the fact that authors wish to define levels of detail applicable to the management and conservation of built heritage [13].
The LoDs (from GIS) are developed in five levels of detail, from LoD0 to LoD4 (Figure 1), having different precisions and minimum dimensions, which are used to represent objects in the model of a three-dimensional city (El-Mekawy et al., 2012; Fan et al., 2011). Thus, LoD0 represents a terrain region in 2.5D; LoD1 are simple volumetric model representations, that is, “boxes”; LoD2 add the roof structure (flat or sloping) to the previous one; LoD3 present the architectural details on the exterior of the model, such as openings and wall textures; and, finally, LoD4 includes the representation of details of the interior of the model, such as the partitions and the delimitation of different spaces [10]. LoD3 and LoD4 levels containing architectural details such as balconies, windows, and rooms rarely exist because, unlike LODs (from BIM), their modeling requires multiple datasets that must be acquired with different technologies, and, often, this requires a lot of manual work [11]; hence, today, most buildings on an urban scale are represented, at best, in LoD3 [14].
/media/item_content/202211/636b0e0fd6099buildings-12-01672-g009.png
Figure 1. Qualities of levels of detail LoD/LOD CityGML (adapted from Consortium, 1994).
Inappropriately, BIM LODs are often interpreted as being associated with a level of detail rather than a level of development. As a project goes through different phases, its semantics increase at different levels of development [9] classified into five groups, from LOD100 to LOD500 [13] Popovic et al., 2017) (Figure 2). LOD100, LOD200, and LOD300 refer, respectively, to the conceptual, schematic, and detailed designs, while the LOD400 and LOD500 refer to a level of development associated with the complex documentation of the project, reaching the final character of an as-built [9].
Buildings 12 01672 g010 550
Figure 2. Knowledge levels (LOK)—HBIM and levels of development (LOD)—BIM.
LOK knowledge levels represent the semantics of heritage management [13], classifying from LOK100 to LOK500. LOK100 is associated with the identification of the heritage asset and its basic characterization; LOK200 enables the graphic characterization and sufficient information for the development of actions related to the legal protection of the asset and its strategic planning; LOK300 provides greater detail about the characterization of graphic entities to the point of being able to show the results of specialized investigations carried out using archaeological methodology or other specific disciplinary follow-up and diagnosis studies; LOK400 includes specific conservation and intervention actions on the asset’s elements; and finally LOK500 deals with efficient management of HBIM models.

1.3. Data Generated by Surveying Activities

The collaboration between various stakeholders involved in a project consists of sharing data through interaction, communication, exchange, and coordination [15]. Feeding a model with existing data enables not only better visualization but also coordination between views and efficient construction management with considerable cost reduction, whether in the construction, rehabilitation, operation, or maintenance phase.
Today, the most widespread dimensions of a BIM model range from 3D to 7D. 3D represents the three-dimensional model of the project, 4D includes the information about its time sequence [16], 5D refers to the costs of the model elements, 6D contains information on sustainability, and, finally, 7D includes aspects of the management programs in the operation and maintenance phase [13].
As for the HBIM models, and with the objective of coordinating all existing information, another five dimensions are usually adopted, coinciding in name with those referred to for BIM models, 3D–7D, but with somewhat different concepts. Thus, the 3D HBIM model, in addition to being related to the three-dimensional model, considers the data collection performed on the building. 4D is related to historical evolution. 5D cannot be directly related to the actual construction costs as in BIM, since, obviously, the building is already constructed; therefore, the transfer of this dimension from BIM to HBIM is not direct, and a parallelism is usually established with the estimated cost of the associated intervention process [13]. 6D includes the cultural context, and, finally, 7D addresses preventive programs and conservation of the building. Figure 3 illustrates the relationship between the BIM and HBIM dimensions.
Buildings 12 01672 g011 550
Figure 3. Dimensions BIM vs. HBIM.

1.4. Applicability of the Model under the Concept of Smart City

Smart city has been a well-adopted concept in urban development worldwide [17][18][19], being, by analogy, the “motherboard” where smart buildings should be inserted, generating a new public–private relationship [7]. It encompasses different definitions, but all of them share, as a basic pillar, the use of technology [20], constituting a facilitating element in the improvement of public services, sustainability, and efficiency [15]. Smart city 3D [4][21], part of the digital twin concept, which was introduced in 2003 within a manufacturing concept and life-cycle management [16][22]. Digital twins integrate IoT, machine learning, artificial intelligence, and big data analysis to create digital simulation and feedback models, which interact with their physical counterparts, updating themselves [23]. Figure 4 lists several application cases and technologies developed in the field of digital twins of cities, extracted from the bibliographic consultation carried out.
Buildings 12 01672 g012 550
Figure 4. Some examples and application cases of digital twins extracted from the bibliography [1][9][10][12][20][21][24][25][26][27][28][29][30][31][32][33][34][35][36].

2. SWOT Analysis

In summary, a digital model can be given a number of applications that correspond to the model of reality. To identify the main aspects that could affect the application of GIS and BIM and HBIM integration in the above possible uses organized according to their relationships with the key-concepts of application of the model of the co-occurrence analysis qualitative results (heritage conservation, cost and quality control, construction project, life-cycle analysis, facilities management, sustainability and energy efficiency, interoperability and semantics, and urban and transport planning) a SWOT analysis is proposed (Figure 5). The result of this SWOT analysis is shown in Table 1.
/media/item_content/202211/636b0e6aaaa09buildings-12-01672-g013.png
Figure 5. Data source for SWOT analysis.
Table 1. SWOT analysis of GIS and BIM and HBIM integration.
Strenghts
Heritage Conservation Cost and Quality Control Construction
Project		 Life Cycle Analysis
Manage semantic knowledge information Reduce costs [14] Synchronize design and planning [37] Evaluate model changes over time [38]
Be able to contain geometric or semantic information [9][39] Improving product quality and optimizing management [30] Simulate the environment surrounding the project and its reactions [36] Plan the maintenance and renewal of assets
Modeling quantitative and qualitative information [37] Managing risk and safety [40][41][42][43][44][45] Manage all project information Simplify and reduce the time to obtain and update information
Integrate and digitally manage heritage Improve productivity [46][47] Enable the process to be more dynamic and efficient [38] Analyze decision making [48]
Automating performance evaluation and heritage conservation Save time Plan the project according to its local environment, and not only at the level of the uniqueness of a building Analyze buildings throughout their life cycle, considering the surrounding environment [45]
Optimize the dissemination of heritage   Planning decision making [46] Virtual building management [44]
Improving risk management   Manage construction [42] Facilitate monitoring processes
Facilities Management Sustainability and Energy Efficiency Interoperability and Semantics Urban and Transport Planning
Predicting maintenance through simulation [31][39] Integrally improving urban sustainability [49] Automate the production of 3D digital documentation Facilitating the improvement of public services
Optimize, through HBIM, the management and maintenance of historic buildings Planning and managing the sustainability of cities [50][51] Sharing and exchange of information between BIM and geospatial objects [52] Improved 3D visualization and use of virtual reality (VR) and augmented reality (AR) [37][53]
Organize in a 3D environment the information generated throughout the design and construction process [54] Reducing the time required for environmental impact assessment of projects [55][56][57] Enabling extended communication between stakeholders to manage a common data environment Create digital simulation models that are updated based on their physical counterparts [58]
Managing public spaces [59][60] Designing smart neighborhoods in an ecological and efficient way [61][62][63][64][65] Sharing of information, knowledge and communications among all stakeholders [15] Enabling simulation of urban phenomena or designs based on a real city
Infrastructure maintenance [60] Perform urban microclimate analysis [61] Integrating IoT Integrating machine learning and artificial intelligence
Monitoring systems through 3D simulation Reducing construction and demolition waste (CDW) [62] Accessing and updating information Enable exploration and analysis of the management tasks in a city [10]
Inventorying large-scale equipment Designing community energy systems [66][67][68][69] Predicting trends Smart city management and human trafficking within them
Calculate demand and large-scale production Forecast energy costs of the building/city Visualize and compare on a large scale the project and finishes of your materials Simulation of natural disasters and intelligent response systems in urban disasters [66][67][70]
Weaknesses
Heritage Conservation Cost and Quality Control Construction Project Life-Cycle Analisis
Uncertainty when dealing with historical buildings Specialized professional training of employees is required High cost of implementation of GIS/BIM technology in company [69] Require a well-fed model
Uniqueness of the components of the heritage asset 3D model management is an arduous and continuous task over time Difficulty to supply the model with the information generated during the construction process Unfeasibility of many projects due to IoT requirements
Limited historical, semantic and graphic information Customers are reluctant to pay the high cost of managing the model Require very powerful hardware for integrated project modeling Failure to upgrade CMMS (computerized maintenance management system/software) systems to 3D formats
Absence of life cycle information Lack of clarity in the legal framework for BIM technology Lack of free licenses for model integration Lack of financial resources on the part of the public administration to generate and manage these models
High cost of data capture High maintenance cost of an integrated quality management system Lack of information management orientation of the model High cost of updating the BIM model throughout the life cycle [14]
Facilities Management Sustainability and Energy Efficiency Interoperability and Semantics Urban and Transport Planning
Requirement to manage and use complex and disparate data [14] Lack of semantic information for the creation and management of the energy model Limitation in representing the semantics of the models in different platforms Insufficient sensor technology to create a smart city
Lack or insufficiency of information for Facility Management Models very far from reality Incompatibility between models Lack or absence of quality LIDAR data available in public administrations
Losing information between construction and operation phases Restriction of access to user energy consumption information Requirement for constant software upgrades by stakeholders Extremely high cost of data acquisition to generate the model
BIM software is not designed to perform Facility Management Few urban-scale 3D models are at the LoD4 as-built level of development Poor stakeholder training in interoperability and coding concepts Preference of the public administration to finance 2D GIS models, due to their lower cost, in relation to 3D GIS
Difficulty in data transmission for bidirectional integration with management software Low level of development of energy efficiency software at the macro-urban level Lack of all BIM model information in the IFC models High number of working hours in the elaboration of an adequate city model
Incompatibility between models Lack of sensor technology for the management of as-built models There is no universal platform [69] Errors in the actual representation of the model [69]
Opportunities
Heritage Conservation Cost and Quality Control Construction
Project		 Life-Cycle Analisis
Take the opportunity to virtualize the management/visit heritage assets through digital models as a consequence of certain risks (for example, pandemics) Globally widespread standardization to facilitate collaboration and data integration [71] The availability of BIM methods and routes for the implementation of digitization of buildings and structures [72] The growing interest in passing management CMMS 2D to 3D
High number of historic buildings in need of intervention [27] Optimization in 3D visualization of production cycle control The existing need for information exchange and cooperative work at a global development level [38] The need for access to asset information through a 3D virtual library
The need for easy access to historical and heritage information The use of simulation as a tool for reducing maintenance costs The need for effective building management Constant development of monitoring technology
The extensive development in virtual and augmented reality for representing heritage The need to remotely manage and supervise the production process The requirement to optimize design time The requirement of public entities in transparent and collaborative management
Overall interest in managing and preserving historic buildings   Need to optimize the bidding process for the project The growing need for remote asset management
Facilities Management Sustainability and Energy Efficiency Interoperability and Semantics Urban and Transport Planning
The need to optimize digital asset management The need for an integrated element to facilitate sustainability and efficiency improvements Requirements to improve risk sharing among stakeholders [73] The possibility of 3D representation in disaster management
The need to optimize the Computerized Maintenance Management Systems/Software (CMMS) The availability of solar incidence simulation tools at city scale The need of stakeholders to increase the capacity to face rapid technological change in the AEC sector [74] The development of new technologies and the use of the smartphones for the interrelation of the user and the city
Improved accessibility of high-capacity Internet services Global requirements to promote energy control and resource savings The existing need to improve trust among stakeholders [73] The creation of regulations to motivate the use of BIM models in structures and public buildings
Potential development of applicable sensorics The need for tools for global and comparative 3D statistical control of energy expenditure The wide range of software and plug-ins GIS and BIM and HBIM will be increasingly in demand in urban planning/regeneration
Threats
Heritage Conservation Cost and Quality Control Construction
Project		 Life-Cycle Analisis
Reliance on laser scanning for the capture of certain data Few professionals with training and accreditation in BIM supervision Unwillingness of contractors, clients and users to employ digital BIM modeling [69] High cost of implementation of a BIM system for life cycle management
Loss of historical information due to inadequate management Increased project cost, due to quality control with BIM Lack of customers requesting the digital 3D service because of its price Non-availability of historical information on structures and their maintenance
Lack of interest in disseminating heritage Difficult accessibility and expensive 3D quality control equipment. The resources required are expensive High cost of sensor technology required for monitoring during operation/intervention phase
Need for significant investments [73] Lack of idiosyncrasy to promote monitoring and control of the project with 3D models Lack of regulatory requirements for the development of private projects in BIM Requirement for highly qualified human resources for remote monitoring of assets
Facilities Management Sustainability and Energy Efficiency Interoperability and Semantics Urban and Transport Planning
Lack of resources for 3D modeling of installations Lack of initiative on the part of technicians to switch to the use of 3D software for energy calculations High cost of software Lack of initiative on the part of public administrations to transform their 2D GIS to 3D.
3D models are usually architectural. Deficiency in the characterization of materials in historic buildings High cost of software [74] Representation in LoD 3 and LoD 4 still very expensive
The high cost of software licenses CMMS The reduced practice of sustainable design in many countries Lack of standardization [73] Lack of requirements from authorities to submit regeneration/urban planning proposals in GIS and BIM and HBIM
Incompatibility of 2D and 3D model connection formats   Difficult relationship between stakeholders Stakeholder limitations in programming language training

References

  1. El-Mekawy, M.; Östman, A.; Hijazi, I. A unified building model for 3D urban GIS. ISPRS Int. J. Geo-Inf. 2012, 1, 120–145.
  2. Sholeh, M.N.; Nurdiana, A.; Setiabudi, B.; Suharjono. Identification of Potential Uses of Building Information Modeling (BIM) for Construction Supply Chain Management: Preliminary Studies. IOP Conf. Ser. Earth Environ. Sci. 2020, 448, 012064.
  3. Noardo, F.; Harrie, L.; Ohori, K.A.; Biljecki, F.; Ellul, C.; Krijnen, T.; Eriksson, H.; Guler, D.; Hintz, D.; Jadidi, M.; et al. Tools for BIM-GIS integration (IFC georeferencing and conversions): Results from the GeoBIM benchmark 2019. ISPRS Int. J. Geo-Inf. 2020, 9, 502.
  4. Sharkawi, K.H.; Abdul-Rahman, A. Improving semantic updating method on 3D city models using hybrid semantic-geometric 3D segmentation technique. In ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences; Copernicus GmbH: Göttingen, Germany, 2013; Volume 2, pp. 261–268.
  5. Hijazi, I.H.; Krauth, T.; Donaubauer, A.; Kolbe., T. 3D CITY DB4 BIM: A system architecture for linking bim server and 3d citydb for bim-gis-integration. In ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences; Copernicus GmbH: Göttingen, Germany, 2020; Volume 5, pp. 195–202.
  6. Open Geospatial Consortium. 1994. Available online: https://www.ogc.org/standards/citygml (accessed on 10 January 2021).
  7. Ren, S.; Mao, J.; Ye, L.; Liu, X. 3D building modeling and indoor fire event representation in CityGML. Appl. Mech. Mater. 2012, 166–169, 2631–2636.
  8. Przybyla, J. The Next Frontier for BIM: Interoperability with GIS; National Institute of Building Sciences: Washington, DC, USA, 2010.
  9. Buyuksalih, I.; Isikdag, U.; Zlatanova, S. Exploring the processes of generating LOD (0-2) CityGML models in greater municipality of Istanbul. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences—ISPRS Archives; International Society for Photogrammetry and Remote Sensing: Istanbul, Turkey, 2013; Volume XL-2/W2, pp. 19–24.
  10. Andrianesi, D.E.; Dimopoulou, E. An Integrated BIM-GIS Platform for Representing and Visualizing 3D Cadastral Data. In ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences; Copernicus GmbH: Göttingen, Germany, 2020; Volume 6, pp. 3–11.
  11. Fan, H.; Mao, B.; Shen, J.; Meng, L. Shell model representation as a substitute of LoD3 for 3D modeling in CityGML. In Proceedings of the Joint ISPRS Workshop on 3D City Modelling and Applications and the 6th 3D GeoInfo, 3DCMA 2011, Wuhan, China, 26–28 June 2011; pp. 79–84.
  12. Dore, C.; Murphy, M. Integration of Historic Building Information Modeling (HBIM) and 3D GIS for recording and managing cultural heritage sites. In Proceedings of the 2012 18th International Conference on Virtual Systems and Multimedia; VSMM 2012: Virtual Systems in the Information Society, Milan, Italy, 2–5 September 2012; UNESCO: Paris, France, 2012; pp. 369–376.
  13. Castellano-Román, M.; Pinto-Puerto, F. Dimensions and Levels of Knowledge in Heritage Building Information Modelling, HBIM: The model of the Charterhouse of Jerez (Cádiz, Spain). Digit. Appl. Archaeol. Cult. Herit. 2019, 14, e00110.
  14. Popovic, D.; Govedarica, M.; Jovanovic, D.; Radulovic, A.; Simeunovic, V. 3D Visualization of Urban Area Using Lidar Technology and CityGML. In IOP Conference Series: Earth and Environmental Science; Institute of Physics Publishing: Bristol, UK, 2017; Volume 95.
  15. Goyal, L.K.; Chauhan, R.; Kumar, R.; Rai, H.S. Use of BIM in Development of Smart Cities: A Review. In IOP Conference Series: Materials Science and Engineering; IOP Publishing Ltd.: Bristol, UK, 2020; Volume 955.
  16. Donkers, S.; Ledoux, H.; Zhao, J.; Stoter, J. Automatic conversion of IFC datasets to geometrically and semantically correct CityGML LOD3 buildings. Trans. GIS 2016, 20, 547–569.
  17. Boje, C.; Guerriero, A.; Kubicki, S.; Rezgui, Y. Towards a semantic Construction Digital Twin: Directions for future research. Autom. Constr. 2020, 114, 103179.
  18. Fan, H.; Meng, L. A three-step approach of simplifying 3D buildings modeled by cityGML. Int. J. Geogr. Inf. Sci. 2012, 26, 1091–1107.
  19. Hämäläinen, M. Smart City Development with Digital Twin Technology. 2020. Available online: https://www.researchgate.net/publication/350460052_Smart_city_based_on_digital_twins (accessed on 17 September 2021).
  20. Arcuri, N.; De Ruggiero, M.; Salvo, F.; Zinno, R. Automated valuation methods through the cost approach in a BIM and GIS integration framework for smart city appraisals. Sustainability 2020, 12, 7546.
  21. Döllner, J.; Hagedorn, B. Integrating urban GIS, CAD, and BIM data by service-based virtual 3D city models. In Urban and Regional Data Management—UDMS Annual 2007; CRC Press: Boca Raton, FL, USA, 2008; pp. 157–170.
  22. Lee, A.; Kim, J.; Jang, I. Movable Dynamic Data Detection and Visualization for Digital Twin City. In Proceedings of the International Conference on Consumer Electronics-Asia (ICCE-Asia), Seoul, Korea, 1–3 November 2020; Institute of Electrical and Electronics Engineers: Piscataway, NJ, USA, 2020. INSPEC Accession Number: 20257668.
  23. Grieves, M. Digital Twin: Manufacturing Excellence through Virtual Factory Replication. 2015. Available online: https://www.3ds.com/fileadmin/Products-Services/Delmia/Pdf/Whitepaper/DELMIA-APRISO-Digital-Twin-Whitepaper.pdf (accessed on 25 October 2021).
  24. Abd, A.M.; Hameed, A.H.; Nsaif, B.M. Documentation of construction project using integration of BIM and GIS technique. Asian J. Civ. Eng. 2020, 21, 1249–1257.
  25. Hwang, J.R.; Kang, H.Y.; Hong, C.H. A Study on the Platform Design for Efficient Interoperability of BIM and GIS. J. Korea Spat. Inf. Soc. 2012, 20, 99–107.
  26. Del Giudice, M.; Osello, A.; Patti, E. BIM and GIS for district modeling. In EWork and EBusiness in Architecture, Engineering and Construction, Proceedings of the 10th European Conference on Product and Process Modelling, ECPPM 2014, Vienna, Austria, 17–19 September 2014; CRC Press/Balkema: Boca Raton, FL, USA, 2015; pp. 851–854.
  27. Palomar, I.J.; García Valldecabres, J.L.; Tzortzopoulos, P.; Pellicer, E. An online platform to unify and synchronise heritage architecture information. Autom. Constr. 2020, 110, 103008.
  28. Zhang, H.; Tang, R.; Qiu, J.; Qiu, X. Design and Implementation of GIS+BIM-Based Digital Campus System. In Proceedings of the 2019 International Conference on Artificial Intelligence and Advanced Manufacturing, AIAM 2019, Dublin, Ireland, 16–18 October 2019; Institute of Electrical and Electronics Engineers Inc.: Piscataway, NJ, USA, 2019; pp. 329–335.
  29. Baik, A.; Yaagoubi, R.; Boehm, J. Integration of jeddah historical bim and 3D GIS for documentation and restoration of historical monument. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences; ISPRS Archives; International Society for Photogrammetry and Remote Sensing: Taipei, Taiwan, 2015; Volume 40, pp. 29–34.
  30. White, G.; Zink, A.; Codecá, L.; Clarke, S. A digital twin smart city for citizen feedback. Cities 2021, 110, 103064.
  31. Cambridge GIS. Model GIS City of Cambridge/Citywide 3D Model. 1999. Available online: https://www.cambridgema.gov/GIS/3D/citywide3dmodel (accessed on 7 December 2020).
  32. Helsinki. Helsingin Kaupunki. 2015. Available online: https://www.hel.fi/helsinki/en/administration/information/general/3d/view/view-the-models (accessed on 5 December 2020).
  33. National Research Foundation. Virtual Singapore. 2018. Available online: https://www.nrf.gov.sg/programmes/virtual-singapore (accessed on 26 May 2021).
  34. Universidad de Cambridge. Center for Digital Built Britain. 2017. Available online: https://www.cdbb.cam.ac.uk/ (accessed on 20 January 2021).
  35. Redondo, F.J.M.; Menéndez, L.V.; Álvarez, A.R.; Fernández, A.A.; Fernández-Jardón, B.G. Plataforma virtual para el diseño, planificación, control, intervención y mantenimiento en el ámbito de la conservación del patrimonio histórico ‘Petrobim. Rehabend 2016, 2016, 1374–1382.
  36. Kassem, M.; Kelly, G.; Dawood, N.; Serginson, M.; Lockley, S. BIM in facilities management applications: A case study of a large university complex. Built. Environ. Proj. Asset. Manag. 2015, 5, 261–277.
  37. Antwi-Afari, M.F.; Li, H.; Pärn, E.A.; Edwards, D.J. Critical success factors for implementing building information modelling (BIM): A longitudinal review. Autom. Constr. 2018, 91, 100–110.
  38. Mol, A.; Cabaleiro, M.; Sousa, H.S.; Branco, J.M. HBIM for storing life-cycle data regarding decay and damage in existing timber structures. Autom. Constr. 2020, 117, 103262.
  39. Yang, X.; Grussenmeyer, P.; Koehl, M.; Macher, H.; Murtiyoso, A.; Landes, T. Review of built heritage modelling: Integration of HBIM and other information techniques. J. Cult. Herit. 2020, 46, 350–360.
  40. Trisyanti, S.W.; Suwardhi, D.; Murtiyoso, A.; Grussenmeyer, P. Low-cost web-application for management of 3D digital building and complex based on BIM and GIS. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences—ISPRS Archives; International Society for Photogrammetry and Remote Sensing: Istanbul, Turkey, 2019; Volume 42, pp. 371–375.
  41. Lin, Y.-C.; Cheung, W.-F. Developing WSN/BIM-Based Environmental Monitoring Management System for Parking Garages in Smart Cities. J. Manag. Eng. 2020, 36, 04020012.
  42. Amirebrahimi, S.; Rajabifard, A.; Mendis, P.; Ngo, T. A BIM-GIS integration method in support of the assessment and 3D visualisation of flood damage to a building. J. Spat. Sci. 2016, 61, 317–350.
  43. Park, E.S.; Seo, H.C. Risk analysis for earthquake-damaged buildings using point cloud and bim data: A case study of the Daeseong apartment complex in Pohang, South Korea. Sustainability 2021, 13, 456.
  44. Ma, G.; Tan, S.; Shang, S. The evaluation of building fire emergency response capability based on the CMM. Int. J. Environ. Res. Public Health 2019, 16, 1962.
  45. Liu, Z.; Zhang, A.; Wang, W. A framework for an indoor safety management system based on digital twin. Sensors 2020, 20, 5771.
  46. Lyu, H.M.; Wang, G.F.; Shen, J.S.; Lu, L.H.; Wang, G.Q. Analysis and GIS mapping of flooding hazards on 10 May 2016, Guangzhou, China. Water 2016, 8, 447.
  47. Bao, L.X.; Wang, Y.Q. Research on expressway network tolling platform technology based on GIS+BIM. In Smart Innovation, Systems and Technologies; Springer: Berlin/Heidelberg, Germany, 2019; Volume 127, pp. 241–250.
  48. Wang, X.; Wang, J.; Wu, C.; Xu, S.; Ma, W.; Wang, X.; Wang, J.; Wu, C.; Xu, S.; Ma, W. Engineering Brain: Metaverse for future engineering. AI Civ. Eng. 2022, 1, 1–18.
  49. Song, Y.; Wang, X.; Tan, Y.; Wu, P.; Cheng, J.C.P.; Hampson, K. Trends and opportunities of BIM-GIS integration in the architecture, engineering and construction industry: A review from a spatio-temporal statistical perspective. ISPRS Int. J. Geo-Inf. 2017, 6, 397.
  50. Akob, Z.; Abang Hipni, M.Z.; Abd Razak, A. Deployment of GIS + BIM in the construction of Pan Borneo Highway Sarawak, Malaysia. In IOP Conference Series: Materials Science and Engineering; Institute of Physics Publishing: Bristol, UK, 2019; Volume 512.
  51. Demir, K.; Ergen, B.; Ergen, Z.; Çabuk, S. Diseño 3D colaborativo con el método BDMUD: Efectos de un edificio en reflexiones de paisaje urbano en planificacion urbana. Archit. City Environ. 2016, 11, 61–80.
  52. Wei, J.; Chen, G.; Huang, J.; Xu, L.; Yang, Y.; Wang, J.; Sadick, A.; Wei, J.; Chen, G.; Huang, J.; et al. BIM and GIS Applications in Bridge Projects: A Critical Review. Appl. Sci. 2021, 11, 6207.
  53. Dou, S.Q.; Zhang, H.H.; Zhao, Y.Q.; Wang, A.M.; Xiong, Y.T.; Zuo, J.M. Research on Construction of Spatio-Temporal Data Visualization Platform for Gis And BIM Fusion. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences—ISPRS Archives; International Society for Photogrammetry and Remote Sensing: Guilin, China, 2020; Volume 42, pp. 555–563.
  54. Han, Z.H.; Wang, Z.K.; Gao, C.; Wang, M.X.; Li, S.T. Application of GIS and BIM Integration Technology in Construction Management. In IOP Conference Series: Earth and Environmental Science; Institute of Physics Publishing: Bristol, UK, 2020; Volume 526.
  55. Dall’O’, G.; Zichi, A.; Torri, M. Green BIM and CIM: Sustainable Planning Using Building Information Modelling. In Research for Development; Springer: Berlin/Heidelberg, Germany, 2020; pp. 383–409.
  56. Zaballos, A.; Briones, A.; Massa, A.; Centelles, P.; Caballero, V. A smart campus’ digital twin for sustainable comfort monitoring. Sustainability 2020, 12, 9196.
  57. Eleftheriadis, S.; Mumovic, D.; Greening, P. Life cycle energy efficiency in building structures: A review of current developments and future outlooks based on BIM capabilities. Renew. Sustain. Energy Rev. 2017, 67, 811–825.
  58. Fernández, R. MSI Estudio: Cuáles son los Principales Softwares BIM Para la Gestión del Facility Management. 2019. Available online: https://www.msistudio.com/cuales-son-los-principales-softwares-bim-para-la-gestion-del-facility-management/ (accessed on 12 January 2021).
  59. Van Eldik, M.A.; Vahdatikhaki, F.; Dos Santos, J.M.O.; Visser, M.; Doree, A. BIM-based environmental impact assessment for infrastructure design projects. Autom. Constr. 2020, 120, 103379.
  60. Delval, T.; Geffroy, B.; Rezoug, M.; Jolibois, A.; Oliveira, F.; Carré, S.; Tual, M.; Soula, J. BIM to Develop Integrated, Incremental and Multiscale Methods to Assess Comfort and Quality of Public Spaces. In Lecture Notes in Civil Engineering; Springer: Berlin/Heidelberg, Germany, 2021; Volume 98, pp. 160–179.
  61. Zhu, C.; Zheng, L.; Liu, Y.; Li, R.; Zhang, Z.; Xie, Y.; Feng, J. The application of bim technology in landscape garden engineering projects. In Advances in Intelligent Systems and Computing; Springer: Berlin/Heidelberg, Germany, 2021; Volume 1244, pp. 550–556.
  62. Dutt, F.; Quan, S.J.; Woodworth, E.; Castro-Lacouture, D.; Stuart, B.J.; Yang, P.P.J. Modeling algae powered neighborhood through GIS and BIM integration. In Energy Procedia; Elsevier Ltd.: Amsterdam, The Netherlands, 2017; Volume 105, pp. 3830–3836.
  63. Yamamura, S.; Fan, L.; Suzuki, Y. Assessment of Urban Energy Performance through Integration of BIM and GIS for Smart City Planning. In Procedia Engineering; Elsevier Ltd.: Amsterdam, The Netherlands, 2017; Volume 180, pp. 1462–1472.
  64. Ge, L.; Xiong, Y. Interaction and application of bim technology in urban rail transit design phase. In ICTE 2019—Proceedings of the 6th International Conference on Transportation Engineering; American Society of Civil Engineers (ASCE): Reston, VI, USA, 2019; pp. 95–100.
  65. Kardinal Jusuf, S.; Mousseau, B.; Godfroid, G.; Soh Jin Hui, V. Integrated modeling of CityGML and IFC for city/neighborhood development for urban microclimates analysis. In Energy Procedia; Elsevier Ltd.: Amsterdam, The Netherlands, 2017; Volume 122, pp. 145–150.
  66. Wang, T.; Krijnen, T.; De Vries, B. Combining GIS and BIM for facility reuse: A profiling approach. Res. Urban Ser. 2016, 4, 185–203.
  67. Cecchini, C.; Magrini, A.; Gobbi, L. A 3d platform for energy data visualization of building assets. In IOP Conference Series: Earth and Environmental Science; Institute of Physics Publishing: Bristol, UK, 2019; Volume 296.
  68. Wetter, M.; Van Treeck, C.; Helsen, L.; Maccarini, A.; Saelens, D.; Robinson, D.; Schweiger, G. IBPSA Project 1: BIM/GIS and Modelica framework for building and community energy system design and operation—Ongoing developments, lessons learned and challenges. In IOP Conference Series: Earth and Environmental Science; Institute of Physics Publishing: Bristol, UK, 2019; Volume 323.
  69. O’Donnell, J.; Truong-Hong, L.; Boyle, N.; Corry, E.; Cao, J.; Laefer, D.F. LiDAR point-cloud mapping of building façades for building energy performance simulation. Autom. Constr. 2019, 107, 102905.
  70. Lei, Y.; Rao, Y.; Wu, J.; Lin, C.H. BIM based cyber-physical systems for intelligent disaster prevention. J. Ind. Inf. Integr. 2020, 20, 100171.
  71. Quattrini, R.; Pierdicca, R.; Morbidoni, C. Knowledge-based data enrichment for HBIM: Exploring high-quality models using the semantic-web. J. Cult. Herit. 2017, 28, 129–139.
  72. Yin, X.; Liu, H.; Chen, Y.; Al-Hussein, M. Building information modelling for off-site construction: Review and future directions. Autom. Constr. 2019, 101, 72–91.
  73. Cui, B.; Wen, X.; Zhang, D. The application of intelligent emergency response system for urban underground space disasters based on 3D GIS, BIM and internet of things. In ACM International Conference Proceeding Series; Association for Computing Machinery: New York, NY, USA, 2019; pp. 745–749.
  74. Rong, Y.; Zhang, T.; Zheng, Y.; Hu, C.; Peng, L.; Feng, P. Three-dimensional urban flood inundation simulation based on digital aerial photogrammetry. J. Hydrol. 2020, 584, 124308.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license; additional terms may apply. By using this site, you agree to the Terms and Conditions and Privacy Policy.
Upload a video for this entry
Information
Subjects: Engineering, Civil
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
César A. Carrasco
,
Ignacio Lombillo
,
Javier M. Sánchez-Espeso
,
Francisco Javier Balbás
View Times: 624
Revisions: 3 times (View History)
Update Date: 09 Nov 2022
Table of Contents
    1000/1000
    Hot Most Recent
    Video Production Service
    Feedback