Characterization of Similar Areas of Two 2D Point Clouds

2012 ◽  
pp. 509-516
Author(s):  
Sébastien Mavromatis ◽  
Christophe Palmann ◽  
Jean Sequeira
Keyword(s):  
Point Clouds

2D quantitative analysis of fractures from high-resolution photos for the geomechanical characterization of rock masses

2021 ◽  
Author(s):  
Emmanuel Wyser ◽  
Lidia Loiotine ◽  
Charlotte Wolff ◽  
Gioacchino Francesco Andriani ◽  
Michel Jaboyedoff ◽  
...  
Keyword(s):  
High Resolution ◽  
Point Clouds ◽  
Mitigation Measures ◽  
Future Perspective ◽  
Rock Masses ◽  
Sampling Errors ◽  
Discontinuity Sets ◽  
Adverse Weather ◽  
Geomechanical Characterization

<p>The identification of discontinuity sets and their properties is among the key factors for the geomechanical characterization of rock masses, which is fundamental for performing stability analyses, and for planning prevention and mitigation measures as well.<br>In practice, discontinuity data are collected throughout difficult and time-consuming field surveys, especially when dealing with areas of wide extension, difficult accessibility, covered by dense vegetation, or with adverse weather conditions. Consequently, even experienced operators may introduce sampling errors or misinterpretations, leading to biased geomechanical models for the investigated rock mass.<br>In the last decades, new remote techniques such as photogrammetry,<em> Light Detection and Ranging</em> (LiDAR), <em>Unmanned Aerial Vehicle</em> (UAV) and <em>InfraRed Thermography </em>(IRT) have been introduced to overcome the limits of conventional surveys. We propose here a new tool for extracting information on the fracture pattern in rock masses, based on <em>remote sensing </em>methods, with particular reference to the analysis of high-resolution georeferenced photos. The first step consists in applying the <em>Structure from Motion</em> (SfM) technique on photos acquired by means of digital cameras and UAV techniques. Once aligned and georeferenced, the orthophotos are exported in a GIS software, to draw the fracture traces at an appropriate scale. We developed a MATLAB routine to extract information on the geostructural setting of rock masses by performing a quantitative 2D analysis of the fracture traces, based on formulas reported in the literature. The code was written by testing few experimental and simple traces and was successively validated on an orthophoto from a real case study.<br>Currently, the script plots the fracture traces as polylines and calculates their orientation (strike) and length. Subsequently, it detects the main discontinuity sets by fitting an experimental composite Gaussian curve on histograms showing the number of discontinuities according to their orientation, and splitting the curve in simpler Gaussian curves, with peaks corresponding to the main discontinuity sets.<br>Then, for each set, a linear scanline intersecting the highest number of traces is plotted, and the apparent and real spacing are calculated. In a second step, a grid of circular scanlines covering the whole area where the traces are located is plotted, and the mean trace intensity, trace density and trace length estimators are calculated.<br>It is expected to test the presented tools on other case studies, in order to optimize them and calculate additional metrics, such as persistence and block sizes, useful to the geomechanical characterization of rock masses.<br>As a future perspective, a similar approach could be investigated for 3D analyses from point clouds.</p>

scholarly journals Structure from Motion Multisource Application for Landslide Characterization and Monitoring: The Champlas du Col Case Study, Sestriere, North-Western Italy

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2364 ◽  
Author(s):  
Martina Cignetti ◽  
Danilo Godone ◽  
Aleksandra Wrzesniak ◽  
Daniele Giordan
Keyword(s):  
Structure From Motion ◽  
Winter Season ◽  
Cost Effective ◽  
Point Clouds ◽  
Slope Instability ◽  
Ski Resorts ◽  
Area Of Interest ◽  
3D Point Clouds ◽  
North Western

Structure from Motion (SfM) is a powerful tool to provide 3D point clouds from a sequence of images taken from different remote sensing technologies. The use of this approach for processing images captured from both Remotely Piloted Aerial Vehicles (RPAS), historical aerial photograms, and smartphones, constitutes a valuable solution for the identification and characterization of active landslides. We applied SfM to process all the acquired and available images for the study of the Champlas du Col landslide, a complex slope instability reactivated in spring 2018 in the Piemonte Region (north-western Italy). This last reactivation of the slide, principally due to snow melting at the end of the winter season, interrupted the main road used to reach Sestriere, one of the most famous ski resorts in north-western Italy. We tested how SfM can be applied to process high-resolution multisource datasets by processing: (i) historical aerial photograms collected from five diverse regional flights, (ii) RGB and multi-spectral images acquired by two RPAS, taken in different moments, and (iii) terrestrial sequences of the most representative kinematic elements due to the evolution of the landslide. In addition, we obtained an overall framework of the historical development of the area of interest, and distinguished several generations of landslides. Moreover, an in-depth geomorphological characterization of the Champlas du Col landslide reactivation was done, by testing a cost-effective and rapid methodology based on SfM principles, which is easily repeatable to characterize and investigate active landslides.

scholarly journals LiDAR-Based Wildfire Prevention in WUI: The Automatic Detection, Measurement and Evaluation of Forest Fuels

Forests ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 148 ◽  
Author(s):  
Marta Fernández-Álvarez ◽  
Julia Armesto ◽  
Juan Picos
Keyword(s):  
Point Clouds ◽  
Individual Tree ◽  
Forest Fuels ◽  
Gis Tools ◽  
Biomass Management ◽  
Measurement And Evaluation ◽  
The Individual ◽  
Individual Trees ◽  
Height Model

This paper describes a methodology using LiDAR point clouds with an ultra-high resolution in the characterization of forest fuels for further wildfire prevention and management. Biomass management strips were defined in three case studies using a particular Spanish framework. The data were acquired through a UAV platform. The proposed methodology allows for the detection, measurement and characterization of individual trees, as well as the analysis of shrubs. The individual tree segmentation process employed a canopy height model, and shrub cover LiDAR-derived models were used to characterize the vegetation in the strips. This way, the verification of the geometric legal restrictions was performed automatically and objectively using decision trees and GIS tools. As a result, priority areas, where wildfire prevention efforts should be concentrated in order to control wildfires, can be identified.

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.

Automatic characterization of rock mass discontinuities using 3D point clouds

2019 ◽  
Vol 259 ◽  
pp. 105131 ◽  
Author(s):  
Xiaojun Li ◽  
Ziyang Chen ◽  
Jianqin Chen ◽  
Hehua Zhu
Keyword(s):  
Rock Mass ◽  
Point Clouds ◽  
3D Point Clouds

scholarly journals AN ENERGY-BASED APPROACH FOR DETECTION AND CHARACTERIZATION OF SUBTLE ENTITIES WITHIN LASER SCANNING POINT-CLOUDS

2016 ◽  
Vol XLI-B3 ◽  
pp. 167-171
Author(s):  
Reuma Arav ◽  
Sagi Filin
Keyword(s):  
Laser Scanning ◽  
Optimization Problem ◽  
Point Clouds ◽  
Urban Environments ◽  
Natural Environments ◽  
Detection Scheme ◽  
Airborne Laser ◽  
The Common ◽  
Geomorphological Features

Airborne laser scans present an optimal tool to describe geomorphological features in natural environments. However, a challenge arises in the detection of such phenomena, as they are embedded in the topography, tend to blend into their surroundings and leave only a subtle signature within the data. Most object-recognition studies address mainly urban environments and follow a general pipeline where the data are partitioned into segments with uniform properties. These approaches are restricted to man-made domain and are capable to handle limited features that answer a well-defined geometric form. As natural environments present a more complex set of features, the common interpretation of the data is still manual at large. In this paper, we propose a data-aware detection scheme, unbound to specific domains or shapes. We define the recognition question as an energy optimization problem, solved by variational means. Our approach, based on the level-set method, characterizes geometrically local surfaces within the data, and uses these characteristics as potential field for minimization. The main advantage here is that it allows topological changes of the evolving curves, such as merging and breaking. We demonstrate the proposed methodology on the detection of collapse sinkholes.

scholarly journals A sensor skid for precise 3D modeling of production lines

2014 ◽  
Vol II-5 ◽  
pp. 117-122 ◽  
Author(s):  
J. Elseberg ◽  
D. Borrmann ◽  
J. Schauer ◽  
A. Nüchter ◽  
D. Koriath ◽  
...  
Keyword(s):  
3D Modeling ◽  
Production Line ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Production Lines ◽  
3D Point Clouds ◽  
Laser Scanners ◽  
Rapid Characterization

Motivated by the increasing need of rapid characterization of environments in 3D, we designed and built a sensor skid that automates the work of an operator of terrestrial laser scanners. The system combines terrestrial laser scanning with kinematic laser scanning and uses a novel semi-rigid SLAMmethod. It enables us to digitize factory environments without the need to stop production. The acquired 3D point clouds are precise and suitable to detect objects that collide with items moved along the production line.

scholarly journals 3D-MODELING OF VEGETATION FROM LIDAR POINT CLOUDS AND ASSESSMENT OF ITS IMPACT ON FAÇADE SOLAR IRRADIATION

2016 ◽  
Vol XLII-2/W2 ◽  
pp. 67-70 ◽  
Author(s):  
G. Peronato ◽  
E. Rey ◽  
M. Andersen
Keyword(s):  
Confidence Intervals ◽  
Complex Shape ◽  
Energy Systems ◽  
Point Clouds ◽  
Urban Environments ◽  
Solar Irradiation ◽  
3D Geometry ◽  
Building Surfaces ◽  
3D Surfaces

The presence of vegetation can significantly affect the solar irradiation received on building surfaces. Due to the complex shape and seasonal variability of vegetation geometry, this topic has gained much attention from researchers. However, existing methods are limited to rooftops as they are based on 2.5D geometry and use simplified radiation algorithms based on view-sheds. This work contributes to overcoming some of these limitations, providing support for 3D geometry to include facades. Thanks to the use of ray-tracing-based simulations and detailed characterization of the 3D surfaces, we can also account for inter-reflections, which might have a significant impact on façade irradiation. <br><br> In order to construct confidence intervals on our results, we modeled vegetation from LiDAR point clouds as 3D convex hulls, which provide the biggest volume and hence the most conservative obstruction scenario. The limits of the confidence intervals were characterized with some extreme scenarios (e.g. opaque trees and absence of trees). <br><br> Results show that uncertainty can vary significantly depending on the characteristics of the urban area and the granularity of the analysis (sensor, building and group of buildings). We argue that this method can give us a better understanding of the uncertainties due to vegetation in the assessment of solar irradiation in urban environments, and therefore, the potential for the installation of solar energy systems.

Mineralogical and structural characterization of massive sulphide deposits in the Iberian Pyrite Belt using hyperspectral digital outcrops

2020 ◽  
Author(s):  
Moritz Kirsch ◽  
Sandra Lorenz ◽  
Samuel Thiele ◽  
Robert Zimmermann ◽  
Mahdi Khodadadzadeh ◽  
...  
Keyword(s):  
Point Clouds ◽  
Iberian Pyrite Belt ◽  
Short Wave ◽  
Massive Sulphide ◽  
Open Pit ◽  
Infrared Range ◽  
Volcanogenic Massive Sulphide ◽  
Host Rocks ◽  
Digital Outcrop

&lt;p&gt;In this contribution, we present integrated hyperspectral and photogrammetric models from three abandoned open pit mines in the Iberian Pyrite Belt: Corta Atalaya, Tharsis, and Pe&amp;#241;a de Hierro. On those three examples, we showcase the usefulness of these data for the characterization of volcanogenic massive sulphide (VMS) mineral deposits. The digital outcrop models are generated by co-registering Structure-from-Motion photogrammetric point clouds of the mine faces with radiometrically corrected hyperspectral images in the visible&amp;#8211;near and short-wave infrared range. We then use advanced unmixing and supervised classification techniques to distinguish and map the massive sulphide and stockwork mineralization, their sedimentary, volcanic and volcaniclastic host rocks, and domains of hydrothermal and supergene alteration. The enhanced outcrop models also enable a semi-automatic delineation of discontinuities on the point clouds guided by changes in the hyperspectral attributes, and an estimation of structure orientations from their intersection with the surface to derive simple 3D geological models.&lt;/p&gt;

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