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Unmanned Aerial Vehicle-Based Inspection in Infrastructure Maintenance

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

Deadline for manuscript submissions: 30 September 2025 | Viewed by 1154

Special Issue Editors

Key Laboratory for Wind and Bridge Engineering of Hunan Province, Hunan University, Changsha 410082, China
Interests: road inspection; bridge displacement; civil engineer; UAV; drones GNSS; Beidou; remote sensing

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Guest Editor
School of Geosciences and Info-Physics, Central South University, South Lushan Road, Changsha 410083, China
Interests: UAV inspection; machine vision; deep learning; deformation monitoring; precision navigation and positioning

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Guest Editor
College Civil Engineering & Architecture, Zhejiang University, Hangzhou 310058, China
Interests: deep learning; image analysis; robotics; structural inspection and evaluation; digital twin; building information modeling (BIM); automated construction
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Guest Editor
College of Civil Engineering, Fuzhou University, Fuzhou 350108, China
Interests: structural health monitoring; road damage inspection; beidou/GNSS positioning; deformation monitoring; UAV remote sensing

Special Issue Information

Dear Colleagues,

The rapid advancements in unmanned aerial vehicle (UAV) technology have revolutionized the field of infrastructure inspection. UAVs are now integral tools for performing detailed and efficient inspections of critical infrastructure, offering significant improvements over traditional methods. Their ability to access difficult-to-reach areas, coupled with advancements in sensor technologies (e.g., high-resolution imaging, LiDAR, thermal sensing), enables real-time, high-precision monitoring. This Special Issue explores the growing role of UAVs in infrastructure maintenance, focusing on their application in the monitoring, inspection, and assessment of structures such as bridges, roads, dams, and power lines.

This Special Issue aims to provide a comprehensive overview of the latest developments in UAV-based infrastructure inspection techniques. It seeks to highlight the potential of UAVs to enhance the accuracy, efficiency, and safety of infrastructure maintenance practices. This Special Issue aligns with the journal's scope, emphasizing the intersection of remote sensing technologies and infrastructure management. We invite contributions that address both the technological advancements and practical applications of UAVs in infrastructure maintenance. Articles may address, but are not limited to, the following topics:

  • UAV-based surface damage identification in bridges, roads, slopes, and dams;
  • UAVs for detecting corrosion and cracking in steel and concrete structures;
  • UAV-based infrastructure deformation monitoring;
  • Deep learning for detection of surface damage;
  • Machine vision-based methods for detection of surface damage in infrastructure;
  • Sensor technologies covering machine vision, multispectral, thermal, LiDAR, etc.;
  • Multi-source heterogeneous data fusion and damage detection;
  • Non-contact monitoring for infrastructure.

Dr. Jiayong Yu
Prof. Dr. Wujiao Dai
Prof. Dr. Jiangpeng Shu
Prof. Dr. Qian Fan
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

  • unmanned aerial vehicle (UAV)
  • infrastructure maintenance
  • remote sensing
  • inspection
  • LiDAR
  • thermal imaging
  • machine vision
  • structural health monitoring
  • multi-sensor technologies
  • deep learning

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Published Papers (1 paper)

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Research

28 pages, 13711 KiB  
Article
BIM-Based Trajectory Planning for Unmanned Aerial Vehicle-Enabled Box Girder Bridge Inspection
by Jiangpeng Shu, Zhe Xia and Yifan Gao
Remote Sens. 2025, 17(4), 682; https://doi.org/10.3390/rs17040682 - 17 Feb 2025
Viewed by 592
Abstract
Inspection is essential for bridge maintenance and has been supplemented by the use of unmanned aerial vehicle (UAV) photogrammetry. However, a review of the literature reveals that existing approaches require the intervention of a human operator to select waypoints in digital twin environments. [...] Read more.
Inspection is essential for bridge maintenance and has been supplemented by the use of unmanned aerial vehicle (UAV) photogrammetry. However, a review of the literature reveals that existing approaches require the intervention of a human operator to select waypoints in digital twin environments. Thus, existing studies are limited by either manual or semi-automatic control restrictions on UAV navigation settings, which is the main motivation for our work. This research developed a building information modelling (BIM)-based trajectory planning approach to enable fully autonomous UAV navigation for box girder bridge inspection, where the UAV follows a predetermined sequence to traverse the environmental space of a box girder bridge. The approach reflects the geometry properties of box girders as inspection characteristics and is designed with algorithms to determine a mathematical relationship between the box girders’ coordinates and inspection sequences. Field testing of the approach shows that it has satisfactory performance in terms of (1) navigation efficiency, (2) reasonableness of the sequence determined for trajectory feature points, (3) trajectory closeness and deviation, and (4) trajectory smoothness. Its satisfactory performance supports the practicability of fully autonomous UAV-enabled bridge inspection. Full article
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