scholarly journals Assessing the capability of terrestrial laser scanning for monitoring slow moving landslides

2009 ◽  
Vol 9 (6) ◽  
pp. 1921-1928 ◽  
Author(s):  
A. Prokop ◽  
H. Panholzer
Keyword(s):  
Laser Scanning ◽  
Mass Movement ◽  
Terrestrial Laser Scanning ◽  
Movement Patterns ◽  
Slope Movement ◽  
Post Processing ◽  
Cloud Data ◽  
Movement Rates ◽  
Point Density ◽  
Processing Steps

Abstract. Digital elevation models (DEM) are widely used to determine characteristics of mass movement processes such as accumulation and deposition of material, volume estimates or the orientation of discontinuities. To create such DEMs point cloud data is provided by terrestrial laser scanning (TLS) and recently used for analysis of mass movements. Therefore the reliability of TLS data was investigated in a comparative study with tachymetry. The main focus was on the possibility of determining movement patterns of landslides <100 mm. Therefore, several post processing steps are needed and the reliability of those were analyzed. The post processing steps that were investigated include: (1) The registration process is a crucial step considering long term TLS monitoring of an object and can be significantly improved using an iterative closest point (ICP) algorithm; (2) Filtering methods are necessary to create DEMs in order to separate favored laser points on the terrain surface (ground points) from topographically irrelevant points (non-ground-points). Therefore GIS tools were applied. Surfaces with and without vegetation cover were differentiated; (3) Displacement vectors are used to determine slope movement rates. They were created from TLS data after the computation of true orthophotos. Using the methodology presented it was not possible to determine movement rates <50 mm per period. However, if the quality of the point density is described and areas with very low point density are detected, reliable conclusions can be made regarding slope movement patterns and erosion and deposition of material for changes <100 mm for the investigated slope.

scholarly journals Monitoring of the Production Process of Graded Concrete Component Using Terrestrial Laser Scanning

2021 ◽  
Vol 13 (9) ◽  
pp. 1622
Author(s):  
Yihui Yang ◽  
Laura Balangé ◽  
Oliver Gericke ◽  
Daniel Schmeer ◽  
Li Zhang ◽  
...  
Keyword(s):  
Production Process ◽  
Laser Scanning ◽  
Hollow Spheres ◽  
Terrestrial Laser Scanning ◽  
Region Growing ◽  
Casting Process ◽  
Concrete Surface ◽  
Cloud Data ◽  
Sphere Detection ◽  
Concrete Component

Accepting the ecological necessity of a drastic reduction of resource consumption and greenhouse gas emissions in the building industry, the Institute for Lightweight Structures and Conceptual Design (ILEK) at the University of Stuttgart is developing graded concrete components with integrated concrete hollow spheres. These components weigh a fraction of usual conventional components while exhibiting the same performance. Throughout the production process of a component, the positions of the hollow spheres and the level of the fresh concrete have to be monitored with high accuracy and in close to real-time, so that the quality and structural performance of the component can be guaranteed. In this contribution, effective solutions of multiple sphere detection and concrete surface modeling based on the technology of terrestrial laser scanning (TLS) during the casting process are proposed and realized by the Institute of Engineering Geodesy (IIGS). A complete monitoring concept is presented to acquire the point cloud data fast and with high-quality. The data processing method for multiple sphere segmentation based on the efficient combination of region growing and random sample consensus (RANSAC) exhibits great performance on computational efficiency and robustness. The feasibility and reliability of the proposed methods are verified and evaluated by an experiment monitoring the production of an exemplary graded concrete component. Some suggestions to improve the monitoring performance and relevant future work are given as well.

scholarly journals Denoising of Laser Scanning Data Using Wavelet

2014 ◽  
Vol 12 ◽  
pp. 41-47 ◽  
Author(s):  
Petr Jašek ◽  
Martin Štroner
Keyword(s):  
Image Processing ◽  
Laser Scanning ◽  
Wavelet Transformation ◽  
Terrestrial Laser Scanning ◽  
Range Image ◽  
Regular Matrix ◽  
Post Processing ◽  
Spatial Coordinates ◽  
Measured Distance ◽  
Made In

Regarding the terrestrial laser scanning accuracy, one of the main problems is the noise in measured distance which is necessary for the spatial coordinates´ determination. In this paper the technique of using the wavelet transformation for the reduction of the noise in the laser scanning data is described. This method of filtration is made in “post processing” and due to this fact any changes in the measuring procedure in the field shouldn´t be done. The creation of the regular matrix is needed to apply image processing. This matrix then makes the range image. In the paper real and simulated efficiency tests of wavelet transformation, the final summary and advantages or disadvantages of this method are introduced.

scholarly journals Study of Subtropical Forestry Index Retrieval Using Terrestrial Laser Scanning and Hemispherical Photography

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Ting Yun ◽  
Weizheng Li ◽  
Yuan Sun ◽  
Lianfeng Xue
Keyword(s):  
Laser Scanning ◽  
Estimation Method ◽  
Terrestrial Laser Scanning ◽  
Tangent Plane ◽  
Transfer Model ◽  
Normal Vector ◽  
Plant Canopy ◽  
Hemispherical Photography ◽  
Area Index ◽  
Cloud Data

In order to retrieve gap fraction, leaf inclination angle, and leaf area index (LAI) of subtropical forestry canopy, here we acquired forestry detailed information by means of hemispherical photography, terrestrial laser scanning, and LAI-2200 plant canopy analyzer. Meanwhile, we presented a series of image processing and computer graphics algorithms that include image and point cloud data (PCD) segmentation methods for branch and leaf classification and PCD features, such as normal vector, tangent plane extraction, and hemispherical projection method for PCD coordinate transformation. In addition, various forestry mathematical models were proposed to deduce forestry canopy indexes based on the radiation transfer model of Beer-Lambert law. Through the comparison of the experimental results on many plot samples, the terrestrial laser scanner- (TLS-) based index estimation method obtains results similar to digital hemispherical photograph (HP) and LAI-2200 plant canopy analyzer taken of the same stands and used for validation. It indicates that the TLS-based algorithm is able to capture the variability in LAI of forest stands with a range of densities, and there is a high chance to enhance TLS as a calibration tool for other devices.

scholarly journals Development of Image Processing for Crack Detection on Concrete Structures through Terrestrial Laser Scanning Associated with the Octree Structure

2018 ◽  
Vol 8 (12) ◽  
pp. 2373 ◽  
Author(s):  
Soojin Cho ◽  
Seunghee Park ◽  
Gichun Cha ◽  
Taekeun Oh
Keyword(s):  
Image Processing ◽  
Laser Scanning ◽  
Crack Detection ◽  
Surface Condition ◽  
Terrestrial Laser Scanning ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Morphological Operations ◽  
Cloud Data ◽  
Remote Sensing Technique

Terrestrial laser scanning (TLS) provides a rapid remote sensing technique to model 3D objects but can also be used to assess the surface condition of structures. In this study, an effective image processing technique is proposed for crack detection on images extracted from the octree structure of TLS data. To efficiently utilize TLS for the surface condition assessment of large structures, a process was constructed to compress the original scanned data based on the octree structure. The point cloud data obtained by TLS was converted into voxel data, and further converted into an octree data structure, which significantly reduced the data size but minimized the loss of resolution to detect cracks on the surface. The compressed data was then used to detect cracks on the surface using a combination of image processing algorithms. The crack detection procedure involved the following main steps: (1) classification of an image into three categories (i.e., background, structural joints and sediments, and surface) using K-means clustering according to color similarity, (2) deletion of non-crack parts on the surface using improved subtraction combined with median filtering and K-means clustering results, (3) detection of major crack objects on the surface based on Otsu’s binarization method, and (4) highlighting crack objects by morphological operations. The proposed technique was validated on a spillway wall of a concrete dam structure in South Korea. The scanned data was compressed up to 50% of the original scanned data, while showing good performance in detecting cracks with various shapes.

scholarly journals Intelligent crack extraction based on terrestrial laser scanning measurement

2020 ◽  
Vol 53 (3-4) ◽  
pp. 416-426 ◽  
Author(s):  
Hao Yang ◽  
Xiangyang Xu
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Cloud Data ◽  
Time Cost ◽  
Visual Examination ◽  
Average Width ◽  
Cloud Data ◽  
Novel Method

The hazards of cracks, which could badly decrease reliability and safety of structures, are receiving increasing attention with the popularity of tunnel constructions. Traditional crack inspection relies on visual examination, which is time-, cost- and labor-intensive. Therefore, how to identify and measure cracks intelligently is significantly essential. The paper focuses on the Canny method to extract cracks of tunnel structures by the intensity value of reflectivity. We propose and investigate a novel method which combines dilation and the Canny algorithm to identify and extract the cracks automatically and intelligently based on the point cloud data of terrestrial laser scanning measurement. In order for measurement of cracks, the projection of summed edge pixels is adopted, where a synthesis is carried out on the detection results with all sampling parameters. Based on the synthesized image, vertical crack presents two sharp peaks where the space of the peaks indicates the average width of the crack, as well as its position. The advantage of the method is that it does not require determination of Canny detector parameters. The deviation between manual measurement and Canny detection is 2.92%.

Research on the Point Cloud Data Processing Method of 3D Terrestrial Laser Scanning in Existing Railway Track

2015 ◽  
Vol 744-746 ◽  
pp. 1298-1302 ◽  
Author(s):  
Feng Han ◽  
Xiao Feng Duan
Keyword(s):  
Laser Scanning ◽  
Structural Characteristics ◽  
Data Extraction ◽  
Three Dimensional ◽  
Terrestrial Laser Scanning ◽  
Railway Track ◽  
Cloud Data ◽  
Railway Line ◽  
Data Processing Method ◽  
Static Detection

Characterized with efficient, accurate and non-contact measurement, and the fast and three-dimensional visualization features, using 3D terrestrial laser scanning technology in track static detection has attracted widespread attention. Based on the structural characteristics of the railway line, use Geomagic software and Cyclone software in the pre-processing stage, remove the noise and redundancy, package the data after registration, get the initial line model finally. In the data extraction stage, combined with professional needs, respectively research the data extraction of track pitch and direction, and the bed section, from line, plane, and body. Which have provided a good research idea for using 3D terrestrial laser scanning technology in track static detection, acceptance, and some other aspects.

scholarly journals MULTIPARAMETER CORRECTION INTENSITY OF TERRESTRIAL LASER SCANNING DATA AS AN INPUT FOR ROCK SURFACE MODELLING

2016 ◽  
Vol XLI-B3 ◽  
pp. 367-372
Author(s):  
V. Paleček ◽  
P. Kubíček
Keyword(s):  
Spatial Data ◽  
Laser Scanning ◽  
Incidence Angle ◽  
Rapid Development ◽  
Digital Terrain Model ◽  
Terrestrial Laser Scanning ◽  
3D Models ◽  
Noise Removal ◽  
Rock Surface ◽  
Cloud Data

A large increase in the creation of 3D models of objects all around us can be observed in the last few years; thanks to the help of the rapid development of new advanced technologies for spatial data collection and robust software tools. A new commercially available airborne laser scanning data in Czech Republic, provided in the form of the Digital terrain model of the fifth generation as irregularly spaced points, enable locating the majority of rock formations. However, the positional and height accuracy of this type of landforms can reach huge errors in some cases. Therefore, it is necessary to start mapping using terrestrial laser scanning with the possibility of adding a point cloud data derived from ground or aerial photogrammetry. Intensity correction and noise removal is usually based on the distance between measured objects and the laser scanner, the incidence angle of the beam or on the radiometric and topographic characteristics of measured objects. This contribution represents the major undesirable effects that affect the quality of acquisition and processing of laser scanning data. Likewise there is introduced solutions to some of these problems.

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