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From Point Cloud Data to Building Information Modelling: An Automatic Parametric Workflow for Heritage

Remote sensing (Basel, Switzerland), 2020-04, Vol.12 (7), p.1094 [Peer Reviewed Journal]

2020. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs12071094

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  • Title:
    From Point Cloud Data to Building Information Modelling: An Automatic Parametric Workflow for Heritage
  • Author: Andriasyan, Mesrop ; Moyano, Juan ; Nieto-Julián, Juan Enrique ; Antón, Daniel
  • Subjects: Algorithms ; Architecture ; Building construction ; Building management systems ; Construction ; cultural heritage ; Cultural resources ; Data acquisition ; Geometry ; Historic buildings & sites ; Historical buildings ; Modelling ; Morphology ; parametric modelling ; point cloud data ; Remote sensing ; Restoration ; Scan-to-BIM ; Software ; Terrestrial environments ; Three dimensional models ; Workflow
  • Is Part Of: Remote sensing (Basel, Switzerland), 2020-04, Vol.12 (7), p.1094
  • Description: Building Information Modelling (BIM) is a globally adapted methodology by government organisations and builders who conceive the integration of the organisation, planning, development and the digital construction model into a single project. In the case of a heritage building, the Historic Building Information Modelling (HBIM) approach is able to cover the comprehensive restoration of the building. In contrast to BIM applied to new buildings, HBIM can address different models which represent either periods of historical interpretation, restoration phases or records of heritage assets over time. Great efforts are currently being made to automatically reconstitute the geometry of cultural heritage elements from data acquisition techniques such as Terrestrial Laser Scanning (TLS) or Structure From Motion (SfM) into BIM (Scan-to-BIM). Hence, this work advances on the parametric modelling from remote sensing point cloud data, which is carried out under the Rhino+Grasshopper-ArchiCAD combination. This workflow enables the automatic conversion of TLS and SFM point cloud data into textured 3D meshes and thus BIM objects to be included in the HBIM project. The accuracy assessment of this workflow yields a standard deviation value of 68.28 pixels, which is lower than other author’s precision but suffices for the automatic HBIM of the case study in this research.
  • Publisher: Basel: MDPI AG
  • Language: English
  • Identifier: ISSN: 2072-4292
    EISSN: 2072-4292
    DOI: 10.3390/rs12071094
  • Source: ROAD: Directory of Open Access Scholarly Resources
    ProQuest Central
    DOAJ Directory of Open Access Journals
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