Implementation of Building Information Modelling for Road Rehabilitation and Reconstruction Project: Liquefaction Disaster of Palu Area

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Published Jul 31, 2022
DOI https://doi.org/10.29138/ijebd.v5i4.1914

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Andri Irfan Rifai
1Faculty of Engineering & Planning, University of Internasional Batam
Hikmawati Thalib
Directorate General of Highway, Indonesia
Muhamad Isradi
Faculty of Engineering, University of Mercubuana, Indonesia
Joewono Prasetijo
Faculty of Engineering Technology, Universiti Tun Hussein Onn Malaysia

Abstract

Purpose: Utilization of Building Information Modeling (BIM) is believed to improve planning accuracy, mitigate construction risks, and better plan the entire life cycle of infrastructure asset projects. The application of BIM technology in post-disaster management can combine GIS technology (Geographic Information System) with BIM technology itself, or commonly referred to as geospatial BIM. The purpose of this paper is to apply BIM technology, explain the stages of road planning and modeling with BIM, and identify the advantages of using BIM compared to conventional methods. The road planning location is the location of the Jono Oge liquefaction disaster, Palu, Indonesia.


Design/methodology/approach: Data collection, data processing with Agisoft Metashape, DEM data input, and orthophoto image data processed by Agisoft Metashape to Autodesk® InfraWorks®, road planning with Autodesk® InfraWorks®, road planning model output and field data presentation. 3D models, IMX format files, FGDB format files, and animation videos.


Findings: The application of BIM technology in planning and modeling road projects at liquefaction locations can be made using Agisoft Metashape software to process aerial photo data taken using drones and using Autodesk® InfraWorks® software for planning and modeling of the road.


Research limitations/implications: Modeling Road design in the application of BIM and the use of Autodesk® InfraWorks® applications on the project. We are not modeling the pavement, just visualizing the geometry of the road.


Practical implications: BIM implementation can drive time, effort, and realistic 3D visualization.


Originality/value: Original paper


Paper type: A case study

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Article Details

Issue
Vol 5 No 4 (2022): July 2022
Section
Articles
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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

References

Rifai, A. I., 2021. Data Mining Applied for Community Satisfaction Prediction of Rehabilitation and Reconstruction Project (Learn from Palu Disasters). In: C. Thomas, ed. Data Mining-Concepts and Applications. s.l.:IntechOpen, p. 187.
Rifai, A., Hendra & Prasetyo, E., 2020. Data Mining Applied for Liquefaction Mapping and Prediction Learn from Palu Earthquakes. Civil Engineering and Architecture, 8(4), pp. 507-514.
Haria, K., de Farago, M., Dawood, T. & Bush, M., 2019. Integration of regional and asset satellite observations for assessment of infrastructure resilience. s.l., In International Conference on Smart Infrastructure and Construction 2019 (ICSIC) Driving data-informed decision-making (pp. 29-34).
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