FIGURE 3
3 The Z + F Imager 5003 phase-based high-speed laser scanner. (From Zoller + Fröhlich. With permission.)
Source publication
Similar publications
Citations
... Three-dimensional modelling can be performed by the use of range-based modelling or image-based techniques [4,5]. An example of range-based modelling can be performed by the Terrestrial Laser Scanner (TLS), which allows us to quickly determine the position of millions of points that accurately define and reproduce the surface and geometry of the objects detected [6,7]. Bertolini-Cestari et al. (2013) [8] propose an integration of innovative and consolidated investigation techniques for 3D metric modelling of the building heritage. ...
Artistic, architectural and Cultural Heritage (CH) structures are often exposed to a high risk of damage caused by seismic events, natural disasters and more by negligence and poor state of preservation and conservation; the use of a series of technologies, based on digital acquisition and high-level data processing, allows the realisation of a three-dimensional model of high detail. In order to preserve structures of particular historical and architectural value, it is necessary to assess their structural stability. In addition, many structures, such as statues, have rather complex geometries. Therefore, it is necessary to identify a methodology able to transform the point cloud generated through a geomatics approach into a model suitable for FEM (Finite Element Analysis) analysis. This process, known as Scan to FEM, is addressed in this paper. The paper shows the case study of the “Colossus of Barletta”, a bronze statue dating back to the 5th century A.D. located in the city of Barletta, Italy. To analyse this structure, a suitable methodology has been developed which is based on the optimisation of the surface model of the structure; in this way, it is possible to obtain an efficient transformation from a digital photogrammetric model with complex geometry into a model suitable for structural finite element analysis. The digital photogrammetry technique was applied for the survey of the structure, which allowed us to obtain a very high-resolution dense point cloud and a geometrically accurate three-dimensional mesh model, i.e., in a TIN (Triangulated Irregular Network) model. Subsequently, the TIN was transformed into a quad mesh model (identifying a suitable reduction value) and finally into NURBS (Non-Uniform Rational Basis-Splines) to be optimised and imported into a finite element calculation software. This geomatics approach has validated an efficient Scan to FEM process; in fact, thanks to this methodology, it is possible to elaborate three-dimensional models with complex geometry and draw a series of considerations related to structural behaviour or specific restoration interventions.
... The Scan task can be realized both with Image Based Method (IBM), i.e. by the use of passive sensor, such as digital camera, or by the use of the active sensors, such as the Terrestrial Laser Scanner (TLS) [1]. Two types of TLS are essentially used for the survey in the Architecture, Engineering and Construction (AEC) field: time-of-flight and phase modulation laser scanners, which allow the survey of even large surfaces with a level of detail with an accuracy of few millimeters and a relatively wide range of action [2]. Using both active and passive sensors, at the end of the Scan process, it is possible to obtain a dense point cloud that describes the geometry of an object or structure and, of consequence, to produce a 3D model [3,4]. ...
A reliable survey of the building geometry is a basic tool for the knowledge of the structure and the correct setting of numerical computational models. An accurate procedure of the method was applied to the build of the 3D model of church of San Nicola Montedoro in Martina Franca (Italy). In this case study, the survey of the church was performed using integrated geomatics techniques: TLS (Terrestrial Laser Scanner), terrestrial and UAV (Unmanned Aerial Vehicle) photogrammetry. In this way, it was possible to obtain an accurate and detailed geometric point cloud of the object. Subsequently, the 3D mesh model was generated from the point clouds. An adequate procedure of simplification and regularization of the meshes allowed to export and subsequently to import them into BIM (Building Information Modeling) software and structural analysis. In addition, a suitable procedure was implemented to produce a model based on Finite Element Method from a simplified model of polysurface mesh, which allowed quantifying the distortions of the building, through the knowledge of the details of each element, becoming the basis for subsequent analysis of the same.
... With the help of an algorithm, survey data is converted into 3D building model elements and building components in the native environment of the design software. The setup is based on the operational principles of terrestrial laser scanners (TLS) [4] With the help of a laser module, an "ultra-low-density" point cloud is produced by taking multiple point-to-point measurements on each surface or edge. This is then convertible into model elements that can be interpreted in architectural design software using a processing algorithm. ...
Building Information Modeling (BIM) has been the fastest growing methodology in architectural design, construction, preliminary works and in several other engineering activities in the past few years. It is mostly implemented in the fields of design, construction and building operation, however, there are still unexploited possibilities in further areas – such as building surveys. Many tools are available today to produce detailed and accurate 3D survey data, but specialists and custom software usually have to be involved in the process. Transforming this information into BIM models is also a time-consuming task, as their direct architectural design software integration is limited. The following article introduces a possible solution in order to improve communication and the modeling process.
... The LiDAR position or some georeferenced points on the ground called "Ground Control Points" (GCPs) are needed to georeferenced the point cloud. According to the platform characteristics, terrestrial or aerial, the issued point cloud is called "Terrestrial Laser Scanning" (TLS) (Gordon and Charles, 2008) or "Aerial Laser Scanning" (ALS) (Wehr and Lohr, 1999). It is important to note that a wet or water covered rock face alters the definition of the point cloud, while a dry surface tends to improve it. ...
2D and 3D imageries can allow the optimization of rock mass exploitation (quarries, roads, rail networks, open pit, potentially tunnels and underground mines networks). The increasingly common use of photogrammetry makes it possible to obtain georeferenced 3D point clouds that are useful for understanding the rock mass. Indeed, new structural analysis solutions have been proposed since the advent of the 3D technologies. These methods are essentially focused on the production of digital stereonet. Production of additional information from 3D point clouds are possible to better define the structure of the rock mass, in particular the quantification of the discontinuities density. The aim of this paper is to test and validate a new method that provides statistics on the distances between the discontinuity planes. This solution is based on exploiting the information previously extracted from the segmentation of the discontinuity planes of a point cloud and their classification in family. In this article, the proposed solution is applied on two multiscale examples, firstly to validate it with a virtual synthetic outcrop and secondly to test it on a real outcrop. To facilitate these analyses, a software called DiscontinuityLab has been developed and used for the treatments.
... Platforms for LiDAR data collection include terrestrial laser scanners (TLS) (e.g., static LiDAR-mounted tripods), mobile laser scanners (MLS) (e.g., mobile mapping vehicles), and airborne laser scanners (ALS) (e.g., aircrafts and unpiloted aerial vehicles (UAV)), and to a lesser extent, orbital platforms [14][15][16]. Each collection platform has a unique associated scanner orientation, scan angle, point spacing, and laser footprint size, resulting in differences in their collected data [14][15][16][17][18][19][20]. ...
... Platforms for LiDAR data collection include terrestrial laser scanners (TLS) (e.g., static LiDAR-mounted tripods), mobile laser scanners (MLS) (e.g., mobile mapping vehicles), and airborne laser scanners (ALS) (e.g., aircrafts and unpiloted aerial vehicles (UAV)), and to a lesser extent, orbital platforms [14][15][16]. Each collection platform has a unique associated scanner orientation, scan angle, point spacing, and laser footprint size, resulting in differences in their collected data [14][15][16][17][18][19][20]. ALS data typically exhibits an even point density distribution [19,21], a well-defined ground surface, a point spacing of roughly 0.5 m [22], and a laser footprint size of 10 cm-25 m [23]. ...
Previous literature has compared the performance of existing ground point classification (GPC) techniques on airborne LiDAR (ALS) data (LiDAR-light detection and ranging); however, their performance when applied to terrestrial LiDAR (TLS) data has not yet been addressed. This research tested the classification accuracy of five openly-available GPC algorithms on seven TLS datasets: Zhang et al.'s inverted cloth simulation (CSF), Kraus and Pfeiffer's hierarchical weighted robust interpolation classifier (HWRI), Axelsson's progressive TIN densification filter (TIN), Evans and Hudak's multiscale curvature classification (MCC), and Vosselman's modified slope-based filter (MSBF). Classification performance was analyzed using the kappa index of agreement (KIA) and rasterized spatial distribution of classification accuracy datasets generated through comparisons with manually classified reference datasets. The results identified a decrease in classification accuracy for the CSF and HWRI classification of low vegetation, for the HWRI and MCC classifications of variably sloped terrain, for the HWRI and TIN classifications of low outlier points, and for the TIN and MSBF classifications of off-terrain (OT) points without any ground points beneath. Additionally, the results show that while no single algorithm was suitable for use on all datasets containing varying terrain characteristics and OT object types, in general, a mathematical-morphology/slope-based method outperformed other methods, reporting a kappa score of 0.902.
... Therefore, deconvolving the subsurface and surface contributions to radar backscatter is difficult Editorial responsibility: G. Lube to do, particularly if the material properties are heterogeneous (Dierking 1999) or are viewed from multiple radar look directions (Greeley and Martel 1988). In contrast, light detection and ranging (LiDAR) directly measures surface positions by counting the two way travel time of a narrow spectrum pulse of light (e.g., Petrie and Toth 2009) and can also be used to derive surface properties. Consequently, LiDAR data are becoming an increasingly important tool in the study of volcanic regions (e.g., Mazzarini et al. 2007;Favalli et al. 2010;Deardorff and Cashman 2012;Cashman et al. 2013;Robinson et al. 2017). ...
We used light detection and ranging (LiDAR) data to calculate roughness patterns (homogeneity, mean-roughness, and entropy) for five lava types at two different resolutions (1.5 and 0.1 m/pixel). We found that end-member types (ʻaʻā and pāhoehoe) are separable (with 95% confidence) at both scales, indicating that roughness patterns are well suited for analyzing types of lava. Intermediate lavas were also explored, and we found that slabby-pāhoehoe is separable from the other end-members using 1.5 m/pixel data, but not in the 0.1 m/pixel analysis. This suggests that the conversion from pāhoehoe to slabby-pāhoehoe is a meter-scale process, and the finer roughness characteristics of pāhoehoe, such as ropes and toes, are not significantly affected. Furthermore, we introduce the ratio \( \frac{ENT}{HOM} \) (derived from lava roughness) as a proxy for assessing local lava flow rate from topographic data. High entropy and low homogeneity regions correlate with high flow rate while low entropy and high homogeneity regions correlate with low flow rate. We suggest that this relationship is not directional, rather it is apparent through roughness differences of the associated lava type emplaced at the high and low rates, respectively.
... TLS technology development has traditionally lagged behind that of airborne laser scanning (ALS) (Petrie and Toth, 2008) even though ALS systems are generally more expensive and complex to operate, given their requirement for integrated inertial motion unit and GNSS sensors for accurate point georeferencing. It is posited in (Petrie and Toth, 2008) that the delayed adoption of terrestrial laser scanning may be correlated with the high cost of laser scanning systems relative to traditional surveying equipment, such as total stations and GNSS receivers. ...
... TLS technology development has traditionally lagged behind that of airborne laser scanning (ALS) (Petrie and Toth, 2008) even though ALS systems are generally more expensive and complex to operate, given their requirement for integrated inertial motion unit and GNSS sensors for accurate point georeferencing. It is posited in (Petrie and Toth, 2008) that the delayed adoption of terrestrial laser scanning may be correlated with the high cost of laser scanning systems relative to traditional surveying equipment, such as total stations and GNSS receivers. Much of the surveying community consists of small, local firms with more limited purchasing power than that of organizations specializing in airborne sensor deployment where high equipment costs are the norm. ...
... The number of publications (left) and citations (right) that concern the use of TLS in Earth science disciplines by year. Fig. 2. A visual depiction of the difference between the field of view of these three scan patterns, camera, hybrid, and panoramic, which follow the conventions defined in Petrie and Toth (2008). Note that all three scanner types operate natively in a spherical coordinate system where each measured point is described by a horizontal angle, a vertical angle, and a range. ...
The application of advanced remote sensing technologies, including terrestrial laser scanning (TLS), to the Earth sciences has increased rapidly in the last two decades, improving the spatial and temporal resolution of data. Terrestrial laser scanning units have evolved into a common tool in studies of spectral and structural geology, seismology, natural hazards, geomorphology, and glaciology. Special consideration of the advantages and limitations of TLS in each of these fields is discussed in depth in the context of important work published in each field. The workflow used in a TLS survey is crucial to the success of the survey, and field-specific Earth science workflows are therefore also discussed. Products based on TLS data, such as triangulated irregular networks (TIN) and digital surface models (DSM), are commonplace tools throughout the Earth sciences and the use of these tools to measure slip distributions, fault geometries, aeolian transport, river bed morphologies and flows, and other research problems is expanded on where appropriate. The review concludes with a discussion of recent trends in TLS instrument development and their potential impact on the use of TLS in the Earth sciences in the future.
... Ground positioning also has the advantage of the ability to scan occlusions that cannot be reached using airborne LiDAR. However, airborne LiDAR scans larger areas of several square kilometers, doing so much faster than the terrestrial LiDAR (Abellán et al. 2014;Gordon and Charles 2008). ...
... Scanning is limited or proscribed in the event of high humidity, rain or snow. Moreover, the number of shadow areas may be important depending on whether or not the rock surface scanning is done from a limited number of LiDAR positions and/or scan shooting angles are insufficiently large (Abellán et al. 2014;Gordon and Charles 2008). Airborne LiDAR scanning can reduce the number of shadow areas when ground positioning constraints are too high. ...
A major mining slope failure occurred in July 2012 on the East wall of the LAB Chrysotile mine in Canada. The major consequence of this failure was the loss of the local highway (Road 112), the main economic link between the region and the Northeast USA. This paper is part of a proposed integrated remote sensing–numerical modelling methodology to analyze mining rock slope stability. This paper presents the Light Detection and Ranging (LiDAR) monitoring of this slope failure. The main focus is the investigation of that rock slide using both terrestrial (TLS) and airborne (ALS) LiDAR scanning. Since 2010, four ALS and 14 TLS were performed to characterize and monitor the slide. First, laser scanning was used to investigate the geometry of the slide. The failure zone was 1100 m by 250 m in size with a mobilized volume of 25 hm³. Laser scanning was then used to investigate the rock slide’s 3D displacement, thereby enabling a better understanding of the sliding kinematics. The results clearly demonstrate the ability of the proposed approach to monitor and quantify large-scale rock mass failure. The slope was monitored for a period of 5 years, and the total displacement was measured at every survey. The maximum cumulative total displacement reached was 145 m. This paper clearly shows the ability of LiDAR scanning to provide valuable quantitative information on large rock mass failures involving very large displacements.
... The distance measurement can be obtained based on the phase shift and the wavelength of the modulated continuous wave. Between these two techniques, the time-of-flight technique has a longer measurement distance while the phase-shift technique has higher measurement speed and higher accuracy [18]. ...
... More details on the scanning mechanism and measuring technique of TLS scanners can be found in Petrie andToth (2009), Reshetyuk (2009) and Vosselman and Maas (2011). ...
Decision making on forest resources relies on the precise information that is collected using inventory. There are many different kinds of forest inventory techniques that can be applied depending on the goal, scale, resources and the required accuracy. Most of the forest inventories are based on field sample. Therefore, the accuracy of the forest inventories depends on the quality and quantity of the field sample. Conventionally, field sample has been measured using simple tools. When map is required, remote sensing materials are needed. Terrestrial laser scanning (TLS) provides a measurement technique that can acquire millimeter-level of detail from the surrounding area, which allows rapid, automatic and periodical estimates of many important forest inventory attributes. It is expected that TLS will be operationally used in forest inventories as soon as the appropriate software becomes available, best practices become known and general knowledge of these findings becomes more wide spread. Meanwhile, mobile laser scanning, personal laser scanning, and image-based point clouds became capable of capturing similar terrestrial point cloud data as TLS. This paper reviews the advances of applying TLS in forest inventories, discusses its properties with reference to other related techniques and discusses the future prospects of this technique.
