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Lidar/Laser Scanning in Civil Engineering

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Optical Sensors".

Deadline for manuscript submissions: closed (31 August 2021) | Viewed by 4643

Special Issue Editors


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Guest Editor
Defense University Center, Spanish Naval Academy, Plaza de España, s/n. 36920 Marín, Spain
Interests: photogrammetry, laser scanning; multi-sensing imaging; geoinformation; spatial analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Light detection and ranging (LiDAR), also called laser scanning, is a high-accurate, remote-sensing technology for efficient 3D data capture in the form of point clouds. Continuous technological developments and reductions in data acquisition cost have triggered the interest in this technology over the years. Originally applied in airborne prototypes for atmospheric research and topographic mapping applications, laser scanning has since been adopted for many other uses, with promising potential to assist in mapping, monitoring and assessment of built-up infrastructure.

Civil engineering structures, which refer to the basic facilities that help society function, including bridges, tunnels, roads, buildings and other systems, begin to deteriorate once they are built and used. Therefore, their preservation and maintenance are crucial to ensure long service lives and laser scanning has been largely proposed as a suitable method to conduct such kinds of operations.

We would like to invite you to submit original research papers or technical or review articles to this Special Issue of Sensors, with emphasis on terrestrial, mobile and airborne laser scanners in combination with point cloud processing algorithms for a broad range of civil engineering applications. Potential topics include, but are not limited to, the following:

  • LiDAR data acquisition and processing for non-destructive evaluation
  • Data quality assessment
  • Dam monitoring
  • Volumetric calculations on dirt work
  • Bridge and tunnel surveys
  • Roadway surveys
  • Crack surveying and mapping
  • Deformation monitoring
  • Building maintenance requirements, building construction and building information modelling (BIM)
  • Quality control, supervision and surveying of construction sites
  • Health monitoring of civil infrastructure

Prof. Dr. Joaquín Martínez-Sánchez
Prof. Dr. Iván Puente Luna
Guest Editors

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 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

  • LiDAR
  • remote sensing
  • 3D modelling
  • infrastructure
  • point cloud processing

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Published Papers (1 paper)

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18 pages, 16161 KiB  
Letter
LiDAR-Based Bridge Displacement Estimation Using 3D Spatial Optimization
by Gichun Cha, Sung-Han Sim, Seunghee Park and Taekeun Oh
Sensors 2020, 20(24), 7117; https://doi.org/10.3390/s20247117 - 11 Dec 2020
Cited by 18 | Viewed by 3545
Abstract
As civil engineering structures become larger, non-contact inspection technology is required to measure the overall shape and size of structures and evaluate safety. Structures are easily exposed to the external environment and may not be able to perform their original functions depending on [...] Read more.
As civil engineering structures become larger, non-contact inspection technology is required to measure the overall shape and size of structures and evaluate safety. Structures are easily exposed to the external environment and may not be able to perform their original functions depending on the continuous load for a long time. Therefore, in this study, we propose a method for estimating the vertical displacement of structures using light detection and ranging, which enables non-contact measurement. The point cloud acquired through laser scanning was rearranged into a three-dimensional space, and internal nodes were created by continuously dividing the space. The generated node has its own location information, and the vertical displacement value was calculated by searching for the node where the deformation occurred. The performance of the proposed displacement estimation technique was verified through static loading experiments, and the octree space partitioning method is expected to be applied and utilized in structural health monitoring. Full article
(This article belongs to the Special Issue Lidar/Laser Scanning in Civil Engineering)
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