New Technology of Surveying and Mapping in the Application of Deformation Monitoring

2013 ◽  
Vol 333-335 ◽  
pp. 1492-1495 ◽  
Author(s):  
Yan Ping Feng ◽  
Tian Zhu Zheng
Keyword(s):  
Real Time ◽  
Laser Scanning ◽  
New Technology ◽  
Three Dimensional ◽  
Laser Scanner ◽  
High Accuracy ◽  
Deformation Monitoring ◽  
High Density ◽  
Monitoring Methods ◽  
Engineering Measurement

Deformation monitoring is one of the engineering measurement tasks. Three-dimensional laser scanning technology as a new technology has developed in recent years. With its high accuracy, high density, real-time and initiative, it wins great favor of people in the industry. Its unique technical advantages and characteristics make it widely used in many fields. The article summarizes the application of deformation monitoring methods and discusses the characteristics of ground 3D laser scanner, its working principles, its application in the field of deformation monitoring and some problems that should be considered.

scholarly journals Study on Real-Time Point Cloud Superimposition on Camera Image to Assist Environmental Three-Dimensional Laser Scanning

2021 ◽  
Vol 15 (3) ◽  
pp. 324-333
Author(s):  
Kenta Ohno ◽  
Hiroaki Date ◽  
Satoshi Kanai ◽  
◽  
Keyword(s):  
Real Time ◽  
Point Cloud ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Point Clouds ◽  
Laser Measurements ◽  
Attitude Error ◽  
Camera Image ◽  
Actual Environment

Recently, three-dimensional (3D) laser scanning technology using terrestrial laser scanner (TLS) has been widely used in the fields of plant manufacturing, civil engineering and construction, and surveying. It is desirable for the operator to be able to immediately and intuitively confirm the scanned point cloud to reduce unscanned regions and acquire scanned point clouds of high quality. Therefore, in this study, we developed a method to superimpose the point cloud on the actual environment to assist environmental 3D laser measurements, allowing the operator to check the scanned point cloud or unscanned regions in real time using the camera image. The method included extracting the correspondences of the camera image and the image generated by point clouds by considering unscanned regions, estimating the camera position and attitude in the point cloud by sampling correspondence points, and superimposing the scanned point cloud and unscanned regions on the camera image. When the proposed method was applied to two types of environments, that is, a boiler room and university office, the estimated camera image had a mean position error of approximately 150 mm and mean attitude error of approximately 1°, while the scanned point cloud and unscanned regions were superimposed on the camera image on a tablet PC at a rate of approximately 1 fps.

scholarly journals DATUM FEATURE EXTRACTION AND DEFORMATION ANALYSIS METHOD BASED ON NORMAL VECTOR OF POINT CLOUD

2018 ◽  
Vol XLII-3 ◽  
pp. 1601-1606
Author(s):  
W. Sun ◽  
J. Wang ◽  
F. Jin ◽  
Z. Liang ◽  
Y. Yang
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Large Scale ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Deformation Monitoring ◽  
Deformation Analysis ◽  
Normal Vector ◽  
Analysis Method ◽  
Data Set

In order to solve the problem lacking applicable analysis method in the application of three-dimensional laser scanning technology to the field of deformation monitoring, an efficient method extracting datum feature and analysing deformation based on normal vector of point cloud was proposed. Firstly, the kd-tree is used to establish the topological relation. Datum points are detected by tracking the normal vector of point cloud determined by the normal vector of local planar. Then, the cubic B-spline curve fitting is performed on the datum points. Finally, datum elevation and the inclination angle of the radial point are calculated according to the fitted curve and then the deformation information was analyzed. The proposed approach was verified on real large-scale tank data set captured with terrestrial laser scanner in a chemical plant. The results show that the method could obtain the entire information of the monitor object quickly and comprehensively, and reflect accurately the datum feature deformation.

scholarly journals Automated terrestrial laser scanning with near-real-time change detection – monitoring of the Séchilienne landslide

2017 ◽  
Vol 5 (2) ◽  
pp. 293-310 ◽  
Author(s):  
Ryan A. Kromer ◽  
Antonio Abellán ◽  
D. Jean Hutchinson ◽  
Matt Lato ◽  
Marie-Aurelie Chanut ◽  
...  
Keyword(s):  
Change Detection ◽  
Real Time ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Cost Effective ◽  
Deformation Monitoring ◽  
Time Change ◽  
High Temporal Resolution ◽  
Atmospheric Conditions ◽  
Detection Processing

Abstract. We present an automated terrestrial laser scanning (ATLS) system with automatic near-real-time change detection processing. The ATLS system was tested on the Séchilienne landslide in France for a 6-week period with data collected at 30 min intervals. The purpose of developing the system was to fill the gap of high-temporal-resolution TLS monitoring studies of earth surface processes and to offer a cost-effective, light, portable alternative to ground-based interferometric synthetic aperture radar (GB-InSAR) deformation monitoring. During the study, we detected the flux of talus, displacement of the landslide and pre-failure deformation of discrete rockfall events. Additionally, we found the ATLS system to be an effective tool in monitoring landslide and rockfall processes despite missing points due to poor atmospheric conditions or rainfall. Furthermore, such a system has the potential to help us better understand a wide variety of slope processes at high levels of temporal detail.

scholarly journals Assessment of the Accuracy of a Multi-Beam LED Scanner Sensor for Measuring Olive Canopies

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4406 ◽  
Author(s):  
Rafael Sola-Guirado ◽  
Sergio Bayano-Tejero ◽  
Antonio Rodríguez-Lizana ◽  
Jesús Gil-Ribes ◽  
Antonio Miranda-Fuentes
Keyword(s):  
Laboratory Test ◽  
Real Time ◽  
Relative Error ◽  
Laser Scanner ◽  
Field Tests ◽  
High Accuracy ◽  
Field Conditions ◽  
Canopy Trees ◽  
Canopy Volume

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.

scholarly journals USING MOBILE LASER SCANNING DATA FOR FEATURES EXTRACTION OF HIGH ACCURACY DRIVING MAPS

2016 ◽  
Vol XLI-B3 ◽  
pp. 433-439 ◽  
Author(s):  
Bisheng Yang ◽  
Yuan Liu ◽  
Fuxun Liang ◽  
Zhen Dong
Keyword(s):  
Laser Scanning ◽  
Human Error ◽  
Traffic Accidents ◽  
Three Dimensional ◽  
Point Clouds ◽  
High Accuracy ◽  
3D Point Clouds ◽  
Assistant Systems ◽  
Novel Method ◽  
High Flexibility

High Accuracy Driving Maps (HADMs) are the core component of Intelligent Drive Assistant Systems (IDAS), which can effectively reduce the traffic accidents due to human error and provide more comfortable driving experiences. Vehicle-based mobile laser scanning (MLS) systems provide an efficient solution to rapidly capture three-dimensional (3D) point clouds of road environments with high flexibility and precision. This paper proposes a novel method to extract road features (e.g., road surfaces, road boundaries, road markings, buildings, guardrails, street lamps, traffic signs, roadside-trees, power lines, vehicles and so on) for HADMs in highway environment. Quantitative evaluations show that the proposed algorithm attains an average precision and recall in terms of 90.6% and 91.2% in extracting road features. Results demonstrate the efficiencies and feasibilities of the proposed method for extraction of road features for HADMs.

scholarly journals 3D MODELS OF OBJECTS IN PROCESS OF RECONSTRUCTION

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Jovana Radović
Keyword(s):  
Laser Scanning ◽  
Laser System ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Terrestrial Laser Scanning ◽  
3D Models ◽  
Terrestrial Laser Scanner ◽  
Accurate Data ◽  
Final Model ◽  
Airborne Laser

Within the last years terrestrial and airborne laser scanning has become a powerful technique for fast and efficient three-dimensional data acquisition of different kinds of objects. Airborne laser system (LiDAR) collects accurate georeferenced data of extremely large areas very quickly while the terrestrial laser scanner produces dense and geometrically accurate data. The combination of these two segments of laser scanning provides different areas of application. One of the applications is in the process of reconstruction of objects. Objects recorded with laser scanning technology and transferred into the final model represent the basis for building an object as it was original. In this paper, there will be shown two case studies based on usage of airborne and terrestrial laser scanning and processing of the data collected by them.

scholarly journals On the utilization of novel spectral laser scanning for three-dimensional classification of vegetation elements

2018 ◽  
Vol 8 (2) ◽  
pp. 20170039 ◽  
Author(s):  
Zhan Li ◽  
Michael Schaefer ◽  
Alan Strahler ◽  
Crystal Schaaf ◽  
David Jupp
Keyword(s):  
Laser Scanning ◽  
Spatial Information ◽  
Information Source ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Biochemical Properties ◽  
Dual Wavelength ◽  
Wavelength Scanning ◽  
Spatial Attributes

The Dual-Wavelength Echidna Lidar (DWEL), a full waveform terrestrial laser scanner (TLS), has been used to scan a variety of forested and agricultural environments. From these scanning campaigns, we summarize the benefits and challenges given by DWEL's novel coaxial dual-wavelength scanning technology, particularly for the three-dimensional (3D) classification of vegetation elements. Simultaneous scanning at both 1064 nm and 1548 nm by DWEL instruments provides a new spectral dimension to TLS data that joins the 3D spatial dimension of lidar as an information source. Our point cloud classification algorithm explores the utilization of both spectral and spatial attributes of individual points from DWEL scans and highlights the strengths and weaknesses of each attribute domain. The spectral and spatial attributes for vegetation element classification each perform better in different parts of vegetation (canopy interior, fine branches, coarse trunks, etc.) and under different vegetation conditions (dead or live, leaf-on or leaf-off, water content, etc.). These environmental characteristics of vegetation, convolved with the lidar instrument specifications and lidar data quality, result in the actual capabilities of spectral and spatial attributes to classify vegetation elements in 3D space. The spectral and spatial information domains thus complement each other in the classification process. The joint use of both not only enhances the classification accuracy but also reduces its variance across the multiple vegetation types we have examined, highlighting the value of the DWEL as a new source of 3D spectral information. Wider deployment of the DWEL instruments is in practice currently held back by challenges in instrument development and the demands of data processing required by coaxial dual- or multi-wavelength scanning. But the simultaneous 3D acquisition of both spectral and spatial features, offered by new multispectral scanning instruments such as the DWEL, opens doors to study biophysical and biochemical properties of forested and agricultural ecosystems at more detailed scales.

scholarly journals A Model-Dependent Method for Monitoring Subtle Changes in Vegetation Height in the Boreal–Alpine Ecotone Using Bi-Temporal, Three Dimensional Point Data from Airborne Laser Scanning

2019 ◽  
Vol 11 (15) ◽  
pp. 1804
Author(s):  
Erik Næsset ◽  
Terje Gobakken ◽  
Ronald E. McRoberts
Keyword(s):  
Laser Scanning ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Tree Height ◽  
Residual Variance ◽  
Tree Line ◽  
Average Growth ◽  
Vegetation Height ◽  
Airborne Laser ◽  
Height Change

The boreal tree line is in many places expected to advance upwards into the mountains due to climate change. This study aimed to develop a general method for estimation of vegetation height change in general, and change in tree height more specifically, for small geographical domains utilizing bi-temporal airborne laser scanner (ALS) data. The domains subject to estimation may subsequently be used to monitor vegetation and tree height change with detailed temporal and geographical resolutions. A method was developed with particular focus on statistically rigorous estimators of uncertainty for change estimates. The method employed model-dependent statistical inference. The method was demonstrated in a 12 ha study site in a boreal–alpine tree line in southeastern Norway, in which 316 trees were measured on the ground in 2006 and 2012 and ALS data were acquired in two temporally coincident campaigns. The trees ranged from 0.11 m to 5.20 m in height. Average growth in height was 0.19 m. Regression models were used to predict and estimate change. By following the area-based approach, predictions were produced for every individual 2 m2 population element that tessellated the study area. Two demonstrations of the method are provided in which separate height change estimates were calculated for domains of size 1.5 ha or greater. Differences in height change estimates among such small domains illustrate how change patterns may vary over the landscape. Model-dependent mean square error estimates for the height change estimators that accounted for (1) model parameter uncertainty, (2) residual variance, and (3) residual covariance are provided. Findings suggested that the two latter sources of uncertainty could be ignored in the uncertainty analysis. The proposed estimators are likely to work well for estimation of differences in height change along a gradient of small monitoring units, like the 1.5 ha cells used for demonstration purposes, and thus may potentially be used to monitor tree line migration over time.

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