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Special Issue "Terrestrial Laser Scanning"

A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: 30 April 2019

Special Issue Editors

Guest Editor
Prof. Dr. Joan R. Rosell Polo

Research Group in AgroICT & Precision Agriculture, University of Lleida – Agrotecnio Center, Catalonia (Spain)
Website | E-Mail
Phone: +34 973 702861
Interests: precision agriculture; remote sensing in agriculture; robotics and automation; sensors; energy
Guest Editor
Dr. Eduard Gregorio López

Research Group in AgroICT & Precision Agriculture, University of Lleida – Agrotecnio Center, Catalonia (Spain)
Website | E-Mail
Interests: sensors; robotics and automation; precision agriculture; LiDAR; energy
Guest Editor
Dr. Jordi Llorens Calveras

Research Group in AgroICT & Precision Agriculture, University of Lleida – Agrotecnio Center, Catalonia (Spain)
Website | E-Mail
Interests: precision agriculture; machinery; sensors; open hardware and software

Special Issue Information

Dear Colleagues,

Since their availability a few decades ago, the applications of LiDAR sensors in 3D scanning have been growing steadily and have been extended to an increasing number of human activity areas and research fields. Specifically, an important effort has been devoted to the characterization of terrestrial targets, both through LiDAR sensors carried by aircrafts and spacecrafts or by terrestrial vehicles. The decrease in size and cost of many LiDAR sensors has led to their popularization among researchers and specialized companies. Simultaneously, the emerging of autonomous vehicles research and development by many car making companies has driven even more the search for more advanced, miniaturized and cheaper LiDAR systems.

The aim of this Special Issue is to bring together innovative developments and applications of Terrestrial Laser Scanning, TLS, understood in a broad sense, i.e. involving the use of Laser-based systems (such as 3D and 2D LiDAR, Flash LiDAR and RGB-D/Depth cameras, etc.) for the measurement and characterization of terrestrial targets. Laser-based systems can be either statically placed on the ground or in motion after being mounted on a moving terrestrial vehicle (mobile terrestrial laser scanners, MTLS). Papers addressing new insights in the development, application and benefits of TLS methods and technology are welcome. Articles may include, but are not limited to, the following topics:

  • New developments of LiDAR and RGB-D sensors and TLS Systems
  • Integration of TLS with other sensors (sensor fusion)
  • Applications of multiple-returns TLS
  • Mobile terrestrial Laser scanner applications (i.e., man-carried and ground-based vehicle-carried)
  • TLS data processing
  • Point cloud creation and processing
  • New applications of LiDAR for the characterization of terrestrial targets
  • Uses and applications from autonomous/unmanned vehicles
  • Agriculture, forestry and geosciences applications
  • Architecture and industrial applications
  • Cultural heritage and archaeological applications

Prof. Dr. Joan R. Rosell Polo
Dr. Eduard Gregorio López
Dr. Jordi Llorens Calveras
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 papers will be 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. Sensors 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 1800 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
  • Laser Scanning
  • 3D modelling
  • Point cloud
  • Multiple-returns TLS
  • RGB-D sensors
  • SLAM methods
  • Data processing
  • Mobile terrestrial laser scanners

Published Papers (9 papers)

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Research

Open AccessArticle Multitemporal Terrestrial Laser Scanning for Marble Extraction Assessment in an Underground Quarry of the Apuan Alps (Italy)
Sensors 2019, 19(3), 450; https://doi.org/10.3390/s19030450
Received: 19 December 2018 / Revised: 14 January 2019 / Accepted: 18 January 2019 / Published: 22 January 2019
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Abstract
This article focuses on the use of Terrestrial Laser Scanning (TLS) for change detection analysis of multitemporal point clouds datasets. Two topographic surveys were carried out during the years 2016 and 2017 in an underground marble quarry of the Apuan Alps (Italy) combining [...] Read more.
This article focuses on the use of Terrestrial Laser Scanning (TLS) for change detection analysis of multitemporal point clouds datasets. Two topographic surveys were carried out during the years 2016 and 2017 in an underground marble quarry of the Apuan Alps (Italy) combining TLS with Global Navigation Satellite System (GNSS) and Total Station (TS) studies. Multitemporal 3D point clouds were processed and compared with the aim of identifying areas subjected to significant material extraction. Point clouds representing changed areas were converted into triangular meshes in order to compute the volume of extracted material over one year of quarrying activities. General purpose of this work is to show a valid method to examine the morphological changes due to raw material extraction with the focus of highlighting benefits, accuracies and drawbacks. The purpose of the executed survey was that of supporting the planning of quarrying activities in respect of regional rules, safety and commercial reasons. Full article
(This article belongs to the Special Issue Terrestrial Laser Scanning)
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Open AccessArticle Assessment of the Accuracy of a Multi-Beam LED Scanner Sensor for Measuring Olive Canopies
Sensors 2018, 18(12), 4406; https://doi.org/10.3390/s18124406
Received: 31 October 2018 / Revised: 7 December 2018 / Accepted: 10 December 2018 / Published: 13 December 2018
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Abstract
Canopy characterization has become important when trying to optimize any kind of agricultural operation in high-growing crops, such as olive. Many sensors and techniques have reported satisfactory results in these approaches and in this work a 2D laser scanner was explored for measuring [...] Read more.
Canopy characterization has become important when trying to optimize any kind of agricultural operation in high-growing crops, such as olive. Many sensors and techniques have reported satisfactory results in these approaches and in this work a 2D laser scanner was explored for measuring canopy trees in real-time conditions. The sensor was tested in both laboratory and field conditions to check its accuracy, its cone width, and its ability to characterize olive canopies in situ. The sensor was mounted on a mast and tested in laboratory conditions to check: (i) its accuracy at different measurement distances; (ii) its measurement cone width with different reflectivity targets; and (iii) the influence of the target’s density on its accuracy. The field tests involved both isolated and hedgerow orchards, in which the measurements were taken manually and with the sensor. The canopy volume was estimated with a methodology consisting of revolving or extruding the canopy contour. The sensor showed high accuracy in the laboratory test, except for the measurements performed at 1.0 m distance, with 60 mm error (6%). Otherwise, error remained below 20 mm (1% relative error). The cone width depended on the target reflectivity. The accuracy decreased with the target density. Full article
(This article belongs to the Special Issue Terrestrial Laser Scanning)
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Open AccessArticle Towards Efficient Implementation of an Octree for a Large 3D Point Cloud
Sensors 2018, 18(12), 4398; https://doi.org/10.3390/s18124398
Received: 22 October 2018 / Revised: 10 December 2018 / Accepted: 11 December 2018 / Published: 12 December 2018
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Abstract
The present study introduces an efficient algorithm to construct a file-based octree for a large 3D point cloud. However, the algorithm was very slow compared with a memory-based approach, and got even worse when using a 3D point cloud scanned in longish objects [...] Read more.
The present study introduces an efficient algorithm to construct a file-based octree for a large 3D point cloud. However, the algorithm was very slow compared with a memory-based approach, and got even worse when using a 3D point cloud scanned in longish objects like tunnels and corridors. The defects were addressed by implementing a semi-isometric octree group. The approach implements several semi-isometric octrees in a group, which tightly covers the 3D point cloud, though each octree along with its leaf node still maintains an isometric shape. The proposed approach was tested using three 3D point clouds captured in a long tunnel and a short tunnel by a terrestrial laser scanner, and in an urban area by an airborne laser scanner. The experimental results showed that the performance of the semi-isometric approach was not worse than a memory-based approach, and quite a lot better than a file-based one. Thus, it was proven that the proposed semi-isometric approach achieves a good balance between query performance and memory efficiency. In conclusion, if given enough main memory and using a moderately sized 3D point cloud, a memory-based approach is preferable. When the 3D point cloud is larger than the main memory, a file-based approach seems to be the inevitable choice, however, the semi-isometric approach is the better option. Full article
(This article belongs to the Special Issue Terrestrial Laser Scanning)
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Open AccessArticle Deformation Analysis of a Composite Bridge during Proof Loading Using Point Cloud Processing
Sensors 2018, 18(12), 4332; https://doi.org/10.3390/s18124332
Received: 31 October 2018 / Revised: 3 December 2018 / Accepted: 5 December 2018 / Published: 7 December 2018
Cited by 1 | PDF Full-text (19621 KB) | HTML Full-text | XML Full-text
Abstract
Remote sensing in structural diagnostics has recently been gaining attention. These techniques allow the creation of three-dimensional projections of the measured objects, and are relatively easy to use. One of the most popular branches of remote sensing is terrestrial laser scanning. Laser scanners [...] Read more.
Remote sensing in structural diagnostics has recently been gaining attention. These techniques allow the creation of three-dimensional projections of the measured objects, and are relatively easy to use. One of the most popular branches of remote sensing is terrestrial laser scanning. Laser scanners are fast and efficient, gathering up to one million points per second. However, the weakness of terrestrial laser scanning is the troublesome processing of point clouds. Currently, many studies deal with the subject of point cloud processing in various areas, but it seems that there are not many clear procedures that we can use in practice, which indicates that point cloud processing is one of the biggest challenges of this issue. To tackle that challenge we propose a general framework for studying the structural deformations of bridges. We performed an advanced object shape analysis of a composite foot-bridge, which is subject to spatial deformations during the proof loading process. The added value of this work is the comprehensive procedure for bridge evaluation, and adaptation of the spheres translation method procedure for use in bridge engineering. The aforementioned method is accurate for the study of structural element deformation under monotonic load. The study also includes a comparative analysis between results from the spheres translation method, a total station, and a deflectometer. The results are characterized by a high degree of convergence and reveal the highly complex state of deformation more clearly than can be concluded from other measurement methods, proving that laser scanning is a good method for examining bridge structures with several competitive advantages over mainstream measurement methods. Full article
(This article belongs to the Special Issue Terrestrial Laser Scanning)
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Open AccessArticle Accuracy Assessment of Semi-Automatic Measuring Techniques Applied to Displacement Control in Self-Balanced Pile Capacity Testing Appliance
Sensors 2018, 18(11), 4067; https://doi.org/10.3390/s18114067
Received: 27 September 2018 / Revised: 13 November 2018 / Accepted: 16 November 2018 / Published: 21 November 2018
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Abstract
Static load tests of foundation piles are the basic method for the designing or verification of adopted design solutions which concern the foundation of a building structure. Preparation of a typical test station using the so-called inverted beam method is very expensive and [...] Read more.
Static load tests of foundation piles are the basic method for the designing or verification of adopted design solutions which concern the foundation of a building structure. Preparation of a typical test station using the so-called inverted beam method is very expensive and labor-intensive. The settlement values of the loaded pile are usually recorded using accurate dial gauges. These gauges are attached to a reference beam located in close proximity to the pile under test, which may cause systematic errors (difficult to detect) caused by the displacement of the adopted reference beam. The application of geodetic methods makes it possible to maintain an independent, external reference system, and to verify the readouts from dial gauges. The article presents an innovative instrumentation for a self-balanced stand for the static load test made from a closed-end, double steel pipe. Instead of typical, precise geometric leveling, the semi-automatic measuring techniques were used: motorized total station measurement and terrestrial laser scanning controlled by a computer. The processing of the acquired data made it possible to determine the vertical displacements of both parts of the examined pile and compare displacements with the results from the dial gauges. On the basis of the excess of the collected observations, it was possible to assess the accuracy, which confirmed the usefulness of measuring techniques under study. Full article
(This article belongs to the Special Issue Terrestrial Laser Scanning)
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Open AccessArticle Evaluation of Object Surface Edge Profiles Detected with a 2-D Laser Scanning Sensor
Sensors 2018, 18(11), 4060; https://doi.org/10.3390/s18114060
Received: 5 September 2018 / Revised: 7 November 2018 / Accepted: 7 November 2018 / Published: 21 November 2018
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Abstract
Canopy edge profile detection is a critical component of plant recognition in variable-rate spray control systems. The accuracy of a high-speed 270° radial laser sensor was evaluated in detecting the surface edge profiles of six complex-shaped objects. These objects were toy balls with [...] Read more.
Canopy edge profile detection is a critical component of plant recognition in variable-rate spray control systems. The accuracy of a high-speed 270° radial laser sensor was evaluated in detecting the surface edge profiles of six complex-shaped objects. These objects were toy balls with a pink smooth surface, light brown rectangular cardboard boxes, black and red texture surfaced basketballs, white smooth cylinders, and two different sized artificial plants. Evaluations included reconstructed three-dimensional (3-D) images for the object surfaces with the data acquired from the laser sensor at four different detection heights (0.25, 0.50, 0.75, and 1.00 m) above each object, five sensor travel speeds (1.6, 2.4, 3.2, 4.0, and 4.8 km h−1), and 8 to 15 horizontal distances to the sensor ranging from 0 to 3.5 m. Edge profiles of the six objects detected with the laser sensor were compared with images taken with a digital camera. The edge similarity score (ESS) was significantly affected by the horizontal distances of the objects, and the influence became weaker when the objects were placed closer to each other. The detection heights and travel speeds also influenced the ESS slightly. The overall average ESS ranged from 0.38 to 0.95 for all the objects under all the test conditions, thereby providing baseline information for the integration of the laser sensor into future development of greenhouse variable-rate spray systems to improve pesticide, irrigation, and nutrition application efficiencies through watering booms. Full article
(This article belongs to the Special Issue Terrestrial Laser Scanning)
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Open AccessArticle On the Sensitivity of the Parameters of the Intensity-Based Stochastic Model for Terrestrial Laser Scanner. Case Study: B-Spline Approximation
Sensors 2018, 18(9), 2964; https://doi.org/10.3390/s18092964
Received: 12 July 2018 / Revised: 28 August 2018 / Accepted: 3 September 2018 / Published: 5 September 2018
Cited by 1 | PDF Full-text (1616 KB) | HTML Full-text | XML Full-text
Abstract
For a trustworthy least-squares (LS) solution, a good description of the stochastic properties of the measurements is indispensable. For a terrestrial laser scanner (TLS), the range variance can be described by a power law function with respect to the intensity of the reflected [...] Read more.
For a trustworthy least-squares (LS) solution, a good description of the stochastic properties of the measurements is indispensable. For a terrestrial laser scanner (TLS), the range variance can be described by a power law function with respect to the intensity of the reflected signal. The power and scaling factors depend on the laser scanner under consideration, and could be accurately determined by means of calibrations in 1d mode or residual analysis of LS adjustment. However, such procedures complicate significantly the use of empirical intensity models (IM). The extent to which a point-wise weighting is suitable when the derived variance covariance matrix (VCM) is further used in a LS adjustment remains moreover questionable. Thanks to closed loop simulations, where both the true geometry and stochastic model are under control, we investigate how variations of the parameters of the IM affect the results of a LS adjustment. As a case study, we consider the determination of the Cartesian coordinates of the control points (CP) from a B-splines curve. We show that a constant variance can be assessed to all the points of an object having homogeneous properties, without affecting the a posteriori variance factor or the loss of efficiency of the LS solution. The results from a real case scenario highlight that the conclusions of the simulations stay valid even for more challenging geometries. A procedure to determine the range variance is proposed to simplify the computation of the VCM. Full article
(This article belongs to the Special Issue Terrestrial Laser Scanning)
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Open AccessArticle Robust Segmentation of Planar and Linear Features of Terrestrial Laser Scanner Point Clouds Acquired from Construction Sites
Sensors 2018, 18(3), 819; https://doi.org/10.3390/s18030819
Received: 1 December 2017 / Revised: 10 February 2018 / Accepted: 5 March 2018 / Published: 8 March 2018
Cited by 2 | PDF Full-text (11071 KB) | HTML Full-text | XML Full-text
Abstract
Automated segmentation of planar and linear features of point clouds acquired from construction sites is essential for the automatic extraction of building construction elements such as columns, beams and slabs. However, many planar and linear segmentation methods use scene-dependent similarity thresholds that may [...] Read more.
Automated segmentation of planar and linear features of point clouds acquired from construction sites is essential for the automatic extraction of building construction elements such as columns, beams and slabs. However, many planar and linear segmentation methods use scene-dependent similarity thresholds that may not provide generalizable solutions for all environments. In addition, outliers exist in construction site point clouds due to data artefacts caused by moving objects, occlusions and dust. To address these concerns, a novel method for robust classification and segmentation of planar and linear features is proposed. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a new robust clustering method, the robust complete linkage method. A robust method is also proposed to extract the points of flat-slab floors and/or ceilings independent of the aforementioned stages to improve computational efficiency. The applicability of the proposed method is evaluated in eight datasets acquired from a complex laboratory environment and two construction sites at the University of Calgary. The precision, recall, and accuracy of the segmentation at both construction sites were 96.8%, 97.7% and 95%, respectively. These results demonstrate the suitability of the proposed method for robust segmentation of planar and linear features of contaminated datasets, such as those collected from construction sites. Full article
(This article belongs to the Special Issue Terrestrial Laser Scanning)
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Open AccessArticle Vertical Optical Scanning with Panoramic Vision for Tree Trunk Reconstruction
Sensors 2017, 17(12), 2791; https://doi.org/10.3390/s17122791
Received: 2 November 2017 / Revised: 29 November 2017 / Accepted: 30 November 2017 / Published: 2 December 2017
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Abstract
This paper presents a practical application of a technique that uses a vertical optical flow with a fisheye camera to generate dense point clouds from a single planimetric station. Accurate data can be extracted to enable the measurement of tree trunks or branches. [...] Read more.
This paper presents a practical application of a technique that uses a vertical optical flow with a fisheye camera to generate dense point clouds from a single planimetric station. Accurate data can be extracted to enable the measurement of tree trunks or branches. The images that are collected with this technique can be oriented in photogrammetric software (using fisheye models) and used to generate dense point clouds, provided that some constraints on the camera positions are adopted. A set of images was captured in a forest plot in the experiments. Weighted geometric constraints were imposed in the photogrammetric software to calculate the image orientation, perform dense image matching, and accurately generate a 3D point cloud. The tree trunks in the scenes were reconstructed and mapped in a local reference system. The accuracy assessment was based on differences between measured and estimated trunk diameters at different heights. Trunk sections from an image-based point cloud were also compared to the corresponding sections that were extracted from a dense terrestrial laser scanning (TLS) point cloud. Cylindrical fitting of the trunk sections allowed the assessment of the accuracies of the trunk geometric shapes in both clouds. The average difference between the cylinders that were fitted to the photogrammetric cloud and those to the TLS cloud was less than 1 cm, which indicates the potential of the proposed technique. The point densities that were obtained with vertical optical scanning were 1/3 less than those that were obtained with TLS. However, the point density can be improved by using higher resolution cameras. Full article
(This article belongs to the Special Issue Terrestrial Laser Scanning)
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