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Book Chapter: The Fusion of GIS and Building Information Modeling for Big Data Analytics in Managing Development Sites

TitleThe Fusion of GIS and Building Information Modeling for Big Data Analytics in Managing Development Sites
Authors
Issue Date2017
PublisherElsevier
Citation
The Fusion of GIS and Building Information Modeling for Big Data Analytics in Managing Development Sites. In Reference Module in Earth Systems and Environmental Sciences. Amsterdam: Elsevier, 2017 How to Cite?
AbstractDue to increasing complexity of contemporary site development, more information about sites themselves and their related environmental, geographical, and surrounding infrastructure is highly desired to support informed decision-making. Fusion of Geographic Information Systems (GIS) and Building Information Modeling (BIM) to support decision-making in site development has gained momentum from both academia and practitioners. Nevertheless, innovative applications of GIS and BIM integration are yet to be fully explored. Using several cases in Hong Kong Special Administrative Region (SAR), this article demonstrates how to integrate GIS and BIM to derive big data for decision-making in construction logistics and supply chain management (LSCM) and construction waste management in site development. In addition, this article proposes a conceptual framework of integrating BIM and GIS for better site development and urban management. The cases in this article not only shed light on big data analytics in a site development setting but also provide useful references to GIS and BIM fusion for better urban management.
Persistent Identifierhttp://hdl.handle.net/10722/241831
ISBN

 

DC FieldValueLanguage
dc.contributor.authorLu, W-
dc.contributor.authorPeng, Y-
dc.contributor.authorXue, F-
dc.contributor.authorChen, K-
dc.contributor.authorNiu, Y-
dc.contributor.authorChen, X-
dc.date.accessioned2017-06-20T01:49:09Z-
dc.date.available2017-06-20T01:49:09Z-
dc.date.issued2017-
dc.identifier.citationThe Fusion of GIS and Building Information Modeling for Big Data Analytics in Managing Development Sites. In Reference Module in Earth Systems and Environmental Sciences. Amsterdam: Elsevier, 2017-
dc.identifier.isbn9780124095489-
dc.identifier.urihttp://hdl.handle.net/10722/241831-
dc.description.abstractDue to increasing complexity of contemporary site development, more information about sites themselves and their related environmental, geographical, and surrounding infrastructure is highly desired to support informed decision-making. Fusion of Geographic Information Systems (GIS) and Building Information Modeling (BIM) to support decision-making in site development has gained momentum from both academia and practitioners. Nevertheless, innovative applications of GIS and BIM integration are yet to be fully explored. Using several cases in Hong Kong Special Administrative Region (SAR), this article demonstrates how to integrate GIS and BIM to derive big data for decision-making in construction logistics and supply chain management (LSCM) and construction waste management in site development. In addition, this article proposes a conceptual framework of integrating BIM and GIS for better site development and urban management. The cases in this article not only shed light on big data analytics in a site development setting but also provide useful references to GIS and BIM fusion for better urban management.-
dc.languageeng-
dc.publisherElsevier-
dc.relation.ispartofReference Module in Earth Systems and Environmental Sciences-
dc.titleThe Fusion of GIS and Building Information Modeling for Big Data Analytics in Managing Development Sites-
dc.typeBook_Chapter-
dc.identifier.emailLu, W: wilsonlu@hku.hk-
dc.identifier.emailXue, F: xuef@hku.hk-
dc.identifier.authorityLu, W=rp01362-
dc.identifier.authorityXue, F=rp02189-
dc.identifier.doi10.1016/B978-0-12-409548-9.09677-9-
dc.identifier.scopuseid_2-s2.0-85082345802-
dc.identifier.hkuros272518-
dc.publisher.placeAmsterdam-

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