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Advances in Remote Sensing and Digital Twins for Management of Civil Infrastructure Assets

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: 30 November 2025 | Viewed by 10233

Special Issue Editors


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Guest Editor
Senior Lecturer, Centre for Infrastructure Engineering, Western Sydney University, Kingswood, NSW 2747, Australia
Interests: bridge engineering and asset management; digital twin development; unmanned aerial vehicle (UAV) based photogrammetry; terrestrial laser scanning (TLS); structural health monitoring (SHM), sustainability, and life cycle management.
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Guest Editor
Senior Research Assistant, Centre for Infrastructure Engineering, Western Sydney University, Kingswood, NSW 2747, Australia
Interests: advanced manufacturing; civil/structural engineering; bridge engineering; structural seismic dampers; digital twin development; bridge health monitoring; bridge information model (BrIM)
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Geoscience and Remote Sensing, Delft University of Technology, 2628 CD Delft, The Netherlands
Interests: building information modeling and digital twins
Special Issues, Collections and Topics in MDPI journals

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Co-Guest Editor
Centre for Infrastructure Engineering, Western Sydney University, Kingswood, NSW 2747, Australia
Interests: digital twin; quality evaluation; geometric accuracy; point cloud; UAV photogrammetry; terrestrial laser scanning (TLS); bridge inspection; 3D model extraction; bridge information model (brim); digitization; image matching; UAV map; tie point filtering; image keypoint selection; keypoint filtering; multi-criteria decision making; bundle block adjustment; image orientation

Special Issue Information

Dear Colleagues,

In recent years, emerging technologies such as Digital Twins and Artificial Intelligence (AI) have revolutionized the monitoring and management of civil infrastructures. Advances in remote sensing, including Unmanned Aerial Vehicles (UAVs), terrestrial laser scanning (TLS), and other sensing platforms, have resulted in efficient, accurate, and cost-effective alternatives to traditional inspection and maintenance methods. These technologies enable comprehensive monitoring of various civil structures, including bridges, tunnels, and buildings, throughout their lifecycle, encouraging the increased adoption of these methods for effective asset management.

This Special Issue welcomes contributions demonstrating innovative developments in technologies combining remote sensing with AI and Digital Twins for civil infrastructure asset management, as well as case studies highlighting their applications in the 3D modeling, assessment, and management of civil infrastructures across the fabrication, construction, operation, and maintenance phases.

Potential topics for this Special Issue include, but are not limited to, the following remote sensing applications:

  • Three-dimensional reconstruction and geometric modeling of civil structures using UAV photogrammetry, TLS, and other sensing technologies.
  • Quality inspection and condition assessment of structural elements using remote sensing and Artificial Intelligence.
  • Integration of remote sensing with Digital Twins for monitoring and predictive maintenance.
  • Advanced structural health monitoring (SHM) leveraging deep learning, computer vision, and image analysis techniques.
  • Development and utilization of Building and Bridge Information Models (BIM/BrIM) for infrastructure management.
  • Decision-support systems and process tracking for inspection, maintenance, and asset management.
  • Virtual Reality (VR) and Augmented Reality (AR) technologies.

Dr. Maria Rashidi
Dr. Masoud Mohammadi
Dr. Linh Truong-Hong
Dr. Vahid Mousavi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • digital twins
  • structural health monitoring (SHM)
  • artificial intelligence (AI)
  • UAV-based photogrammetry
  • terrestrial laser scanning (TLS)
  • building and bridge information modeling (BIM/BrIM)
  • 3D reconstruction and modeling
  • computer vision
  • bridge inspection
  • infrastructure inspection and assessment
  • infrastructure management systems
  • virtual reality (VR)
  • augmented reality (AR)

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Published Papers (1 paper)

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Review

38 pages, 7571 KB  
Review
Evolution of Digital Twin Frameworks in Bridge Management: Review and Future Directions
by Vahid Mousavi, Maria Rashidi, Masoud Mohammadi and Bijan Samali
Remote Sens. 2024, 16(11), 1887; https://doi.org/10.3390/rs16111887 - 24 May 2024
Cited by 24 | Viewed by 8718
Abstract
Over the last decade, the digital twin (DT) concept has effectively revolutionized conventional bridge monitoring and management. Despite their overall success, current bridge DTs encounter conceptual ambiguities, hindering their inherent potential for practical implementation. Moreover, intelligent decision support models have not been properly [...] Read more.
Over the last decade, the digital twin (DT) concept has effectively revolutionized conventional bridge monitoring and management. Despite their overall success, current bridge DTs encounter conceptual ambiguities, hindering their inherent potential for practical implementation. Moreover, intelligent decision support models have not been properly considered as a component of the bridge DTs framework to enhance the reliability of decisions for asset maintenance. Therefore, this paper conducts a scientometric analysis and a comprehensive state-of-the-art review, exploring current bridge DT research trends and architectures and introducing an enhanced conceptual framework for bridge DTs. To this end, more than 480 research publications have been reviewed, compared, and analyzed. The research result encompasses the redevelopment of a multilayer DT framework, fostering its implementation in the full lifecycle of bridge infrastructure while exploring the potential integration of decision support systems and data fusion from advanced technologies to improve the overall efficiency of implementing DT technology in bridges. Full article
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