scholarly journals Systematic Approach for Tunnel Deformation Monitoring with Terrestrial Laser Scanning

2021 ◽  
Vol 13 (17) ◽  
pp. 3519
Author(s):  
Dongfeng Jia ◽  
Weiping Zhang ◽  
Yanping Liu
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
High Accuracy ◽  
Deformation Monitoring ◽  
Reference Plane ◽  
Shield Tunnel ◽  
Cloud Processing ◽  
Point Cloud Processing

The use of terrestrial laser scanning (TLS) point clouds for tunnel deformation measurement has elicited much interest. However, general methods of point-cloud processing in tunnels are still under investigation, given the high accuracy and efficiency requirements in this area. This study discusses a systematic method of analyzing tunnel deformation. Point clouds from different stations need to be registered rapidly and with high accuracy before point-cloud processing. An orientation method of TLS in tunnels that uses a positioning base made in the laboratory is proposed for fast point-cloud registration. The calibration methods of the positioning base are demonstrated herein. In addition, an improved moving least-squares method is proposed as a way to reconstruct the centerline of a tunnel from unorganized point clouds. Then, the normal planes of the centerline are calculated and are used to serve as the reference plane for point-cloud projection. The convergence of the tunnel cross-section is analyzed, based on each point cloud slice, to determine the safety status of the tunnel. Furthermore, the results of the deformation analysis of a particular shield tunnel site are briefly discussed.

scholarly journals Special Issue on “Terrestrial Laser Scanning”: Editors’ Notes

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4569
Author(s):  
Joan R. Rosell-Polo ◽  
Eduard Gregorio ◽  
Jordi Llorens
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Special Issue ◽  
Alternative Technologies ◽  
Cloud Processing ◽  
3D Point Clouds ◽  
Point Cloud Processing

In this editorial, we provide an overview of the content of the special issue on “Terrestrial Laser Scanning”. The aim of this Special Issue is to bring together innovative developments and applications of terrestrial laser scanning (TLS), understood in a broad sense. Thus, although most contributions mainly involve the use of laser-based systems, other alternative technologies that also allow for obtaining 3D point clouds for the measurement and the 3D characterization of terrestrial targets, such as photogrammetry, are also considered. The 15 published contributions are mainly focused on the applications of TLS to the following three topics: TLS performance and point cloud processing, applications to civil engineering, and applications to plant characterization.

scholarly journals COMPARING MULTI-SOURCE PHOTOGRAMMETRIC DATA DURING THE EXAMINATION OF VERTICALITY IN A MONUMENTAL TOWER

2017 ◽  
Vol XLII-2/W3 ◽  
pp. 475-480
Author(s):  
J. Markiewicz ◽  
D. Zawieska ◽  
P. Podlasiak
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Cloud Processing ◽  
Point Cloud Processing ◽  
Aerial Vehicles ◽  
Geometric Quality

This paper presents an analysis of source photogrammetric data in relation to the examination of verticality in a monumental tower. In the proposed data processing methodology, the geometric quality of the point clouds relating to the monumental tower of the castle in Iłżawas established by using terrestrial laser scanning (Z+F 5006h, Leica C10), terrestrial photographs and digital images sourced via unmanned aerial vehicles (UAV) (Leica Aibot X6 Hexacopter). Tests were performed using the original software, developed by the authors, which allows for the automation of 3D point cloud processing. The software also facilitates the verification of the verticality of the tower and the assessment of the quality of utilized data.

scholarly journals Deformation Analysis of a Composite Bridge during Proof Loading Using Point Cloud Processing

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4332 ◽  
Author(s):  
Patryk Ziolkowski ◽  
Jakub Szulwic ◽  
Mikolaj Miskiewicz
Keyword(s):  
Remote Sensing ◽  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Measurement Methods ◽  
Added Value ◽  
Translation Method ◽  
Cloud Processing ◽  
Point Cloud Processing

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.

scholarly journals Deformation monitoring using laser scanned point clouds and BIM

2018 ◽  
Vol 245 ◽  
pp. 01002 ◽  
Author(s):  
Vladimir Badenko ◽  
Dmitry Volgin ◽  
Sergey Lytkin
Keyword(s):  
Laser Scanning ◽  
Point Clouds ◽  
Deformation Monitoring ◽  
Future Research ◽  
Cloud Processing ◽  
3D Point Clouds ◽  
Point Cloud Processing ◽  
Informational Model ◽  
Technology Gaps

Laser scanning is an essential method for monitoring of the operation of buildings or structures. It involves creating as-is BIM from point clouds obtained from laser scanning. In this article we present our workflow for the generation of information model from 3D point clouds of concrete tetrapod blocks on navigable structure C-1. Point cloud processing method for making informational model for long term monitoring is described. As a result of the research BIM model with each tetrapod was created for deformational monitoring in the comparison with next year model. Finally, we identify and discuss technology gaps that need to be addressed in future research.

scholarly journals Semi-automatic extraction of sectional view from point clouds – The case of Ottmarsheim's abbey-church

2014 ◽  
Vol XL-5 ◽  
pp. 343-348 ◽  
Author(s):  
T. Landes ◽  
S. Bidino ◽  
R. Guild
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Cutting Plane ◽  
Mean Deviation ◽  
Surfaces Of Revolution ◽  
Cloud Processing ◽  
Point Cloud Processing ◽  
Heritage Buildings ◽  
Time Required

Today, elevations or sectional views of buildings are often produced from terrestrial laser scanning. However, due to the amount of data to process and because usually 2D maps are required by customers, the 3D point cloud is often degraded into 2D slices. In a sectional view, not only the portions of the objet which are intersected by the cutting plane but also edges and contours of other parts of the object which are visible behind the cutting plane are represented. To avoid the tedious manual drawing, the aim of this work is to propose a semi-automatic approach for creating sectional views by point cloud processing. The extraction of sectional views requires in a first step the segmentation of the point cloud into planar and non-planar entities. Since in cultural heritage buildings, arches, vaults, columns can be found, the position and the direction of the sectional view must be taken into account before contours extraction. Indeed, the edges of surfaces of revolution depend on the chosen view. The developed extraction approach is detailed based on point clouds acquired inside and outside churches. The resulting sectional view has been evaluated in a qualitative and quantitative way by comparing it with a reference sectional view made by hand. A mean deviation of 3 cm between both sections proves that the proposed approach is promising. Regarding the processing time, despite a few manual corrections, it has saved 40% of the time required for manual drawing.

scholarly journals Development of Improved Semi-Automated Processing Algorithms for the Creation of Rockfall Databases

2021 ◽  
Vol 13 (8) ◽  
pp. 1479
Author(s):  
Heather Schovanec ◽  
Gabriel Walton ◽  
Ryan Kromer ◽  
Adam Malsam
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Rock Slope ◽  
Terrestrial Laser Scanning ◽  
Multiscale Model ◽  
Current Data ◽  
Cloud Data ◽  
Cloud Processing ◽  
Point Cloud Processing ◽  
The Creation

While terrestrial laser scanning and photogrammetry provide high quality point cloud data that can be used for rock slope monitoring, their increased use has overwhelmed current data analysis methodologies. Accordingly, point cloud processing workflows have previously been developed to automate many processes, including point cloud alignment, generation of change maps and clustering. However, for more specialized rock slope analyses (e.g., generating a rockfall database), the creation of more specialized processing routines and algorithms is necessary. More specialized algorithms include the reconstruction of rockfall volumes from clusters and points and automatic classification of those volumes are both processing steps required to automate the generation of a rockfall database. We propose a workflow that can automate all steps of the point cloud processing workflow. In this study, we detail adaptions to commonly used algorithms for rockfall monitoring use cases, such as Multiscale Model to Model Cloud Comparison (M3C2). This workflow details the entire processing pipeline for rockfall database generation using terrestrial laser scanning.

scholarly journals POINT CLOUD PROCESSING SOFTWARE SOLUTIONS

AГГ+ ◽  
2020 ◽  
Vol 1 (8) ◽  
Author(s):  
Miroslav Vujasinović ◽  
Miodrag Regodić ◽  
Stefan Kecman
Keyword(s):  
Data Collection ◽  
Spatial Data ◽  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Engineering Profession ◽  
Cloud Processing ◽  
Specialized Software ◽  
Point Cloud Processing ◽  
Processing Software

Spatial data collection has been considerably improved with the invention of LiDAR and other laser scanning technologies. The result of surveying with these methods is a 3D point cloud. The amount of data obtained requires specialized software solutions to solve the tasks set before the engineering profession in this field. The paper describes data collection technologies resulting in point clouds, commercial software solutions for point cloud processing, and presents an open source Cloud Compare software solution and its advantages.

scholarly journals Revealing Changes in the Stem Form and Volume Allocation in Diverse Boreal Forests Using Two-Date Terrestrial Laser Scanning

Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 835
Author(s):  
Ville Luoma ◽  
Tuomas Yrttimaa ◽  
Ville Kankare ◽  
Ninni Saarinen ◽  
Jiri Pyörälä ◽  
...  
Keyword(s):  
Tree Growth ◽  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Stem Volume ◽  
Accurate Information ◽  
Stem Form ◽  
Monitoring Period ◽  
Significant Difference

Tree growth is a multidimensional process that is affected by several factors. There is a continuous demand for improved information on tree growth and the ecological traits controlling it. This study aims at providing new approaches to improve ecological understanding of tree growth by the means of terrestrial laser scanning (TLS). Changes in tree stem form and stem volume allocation were investigated during a five-year monitoring period. In total, a selection of attributes from 736 trees from 37 sample plots representing different forest structures were extracted from taper curves derived from two-date TLS point clouds. The results of this study showed the capability of point cloud-based methods in detecting changes in the stem form and volume allocation. In addition, the results showed a significant difference between different forest structures in how relative stem volume and logwood volume increased during the monitoring period. Along with contributing to providing more accurate information for monitoring purposes in general, the findings of this study showed the ability and many possibilities of point cloud-based method to characterize changes in living organisms in particular, which further promote the feasibility of using point clouds as an observation method also in ecological studies.

scholarly journals Automatic Processing of Aerial LiDAR Data to Detect Vegetation Continuity in the Surroundings of Roads

2020 ◽  
Vol 12 (10) ◽  
pp. 1677 ◽  
Author(s):  
Ana Novo ◽  
Noelia Fariñas-Álvarez ◽  
Joaquin Martínez-Sánchez ◽  
Higinio González-Jorge ◽  
Henrique Lorenzo
Keyword(s):  
Point Cloud ◽  
Point Clouds ◽  
Light Detection And Ranging ◽  
Applicable Law ◽  
Cloud Processing ◽  
Point Cloud Processing ◽  
Preventive Actions ◽  
Total Study Area ◽  
Processing Techniques ◽  
Flammable Material

The optimization of forest management in the surroundings of roads is a necessary task in term of wildfire prevention and the mitigation of their effects. One of the reasons why a forest fire spreads is the presence of contiguous flammable material, both horizontally and vertically and, thus, vegetation management becomes essential in preventive actions. This work presents a methodology to detect the continuity of vegetation based on aerial Light Detection and Ranging (LiDAR) point clouds, in combination with point cloud processing techniques. Horizontal continuity is determined by calculating Cover Canopy Fraction (CCF). The results obtained show 50% of shrubs presence and 33% of trees presence in the selected case of study, with an error of 5.71%. Regarding vertical continuity, a forest structure composed of a single stratum represents 81% of the zone. In addition, the vegetation located in areas around the roads were mapped, taking into consideration the distances established in the applicable law. Analyses show that risky areas range from a total of 0.12 ha in a 2 m buffer and 0.48 ha in a 10 m buffer, representing a 2.4% and 9.5% of the total study area, respectively.

scholarly journals Combined Use of Terrestrial Laser Scanning and UAV Photogrammetry in Mapping Alpine Terrain

2019 ◽  
Vol 11 (18) ◽  
pp. 2154 ◽  
Author(s):  
Ján Šašak ◽  
Michal Gallay ◽  
Ján Kaňuk ◽  
Jaroslav Hofierka ◽  
Jozef Minár
Keyword(s):  
High Resolution ◽  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Mutual Orientation ◽  
Close Range Photogrammetry ◽  
Combined Use ◽  
Wide Range ◽  
Close Range

Airborne and terrestrial laser scanning and close-range photogrammetry are frequently used for very high-resolution mapping of land surface. These techniques require a good strategy of mapping to provide full visibility of all areas otherwise the resulting data will contain areas with no data (data shadows). Especially, deglaciated rugged alpine terrain with abundant large boulders, vertical rock faces and polished roche-moutones surfaces complicated by poor accessibility for terrestrial mapping are still a challenge. In this paper, we present a novel methodological approach based on a combined use of terrestrial laser scanning (TLS) and close-range photogrammetry from an unmanned aerial vehicle (UAV) for generating a high-resolution point cloud and digital elevation model (DEM) of a complex alpine terrain. The approach is demonstrated using a small study area in the upper part of a deglaciated valley in the Tatry Mountains, Slovakia. The more accurate TLS point cloud was supplemented by the UAV point cloud in areas with insufficient TLS data coverage. The accuracy of the iterative closest point adjustment of the UAV and TLS point clouds was in the order of several centimeters but standard deviation of the mutual orientation of TLS scans was in the order of millimeters. The generated high-resolution DEM was compared to SRTM DEM, TanDEM-X and national DMR3 DEM products confirming an excellent applicability in a wide range of geomorphologic applications.

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