scholarly journals Precision Evaluation and Fusion of Topographic Data Based on UAVs and TLS Surveys of a Loess Landslide

2021 ◽  
Vol 9 ◽  
Author(s):  
Zhonglei Mao ◽  
Sheng Hu ◽  
Ninglian Wang ◽  
Yongqing Long
Keyword(s):  
Point Cloud ◽  
Laser Scanner ◽  
Point Clouds ◽  
Terrestrial Laser Scanner ◽  
Point Cloud Data ◽  
Loess Landslide ◽  
Cloud Data ◽  
Topographic Data ◽  
Blind Area ◽  
Precision Evaluation

In recent years, low-cost unmanned aerial vehicles (UAVs) photogrammetry and terrestrial laser scanner (TLS) techniques have become very important non-contact measurement methods for obtaining topographic data about landslides. However, owing to the differences in the types of UAVs and whether the ground control points (GCPs) are set in the measurement, the obtained topographic data for landslides often have large precision differences. In this study, two types of UAVs (DJI Mavic Pro and DJI Phantom 4 RTK) with and without GCPs were used to survey a loess landslide. UAVs point clouds and digital surface model (DSM) data for the landslide were obtained. Based on this, we used the Geomorphic Change Detection software (GCD 7.0) and the Multiscale Model-To-Model Cloud Comparison (M3C2) algorithm in the Cloud Compare software for comparative analysis and accuracy evaluation of the different point clouds and DSM data obtained using the same and different UAVs. The experimental results show that the DJI Phantom 4 RTK obtained the highest accuracy landslide terrain data when the GCPs were set. In addition, we also used the Maptek I-Site 8,820 terrestrial laser scanner to obtain higher precision topographic point cloud data for the Beiguo landslide. However, owing to the terrain limitations, some of the point cloud data were missing in the blind area of the TLS measurement. To make up for the scanning defect of the TLS, we used the iterative closest point (ICP) algorithm in the Cloud Compare software to conduct data fusion between the point clouds obtained using the DJI Phantom 4 RTK with GCPs and the point clouds obtained using TLS. The results demonstrate that after the data fusion, the point clouds not only retained the high-precision characteristics of the original point clouds of the TLS, but also filled in the blind area of the TLS data. This study introduces a novel perspective and technical scheme for the precision evaluation of UAVs surveys and the fusion of point clouds data based on different sensors in geological hazard surveys.

scholarly journals Comparison of Depth Camera and Terrestrial Laser Scanner in Monitoring Structural Deflections

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 201
Author(s):  
Michael Bekele Maru ◽  
Donghwan Lee ◽  
Kassahun Demissie Tola ◽  
Seunghee Park
Keyword(s):  
Optical Sensors ◽  
Point Cloud ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Point Clouds ◽  
Depth Camera ◽  
Terrestrial Laser Scanner ◽  
Cloud Data ◽  
3D Point Clouds ◽  
3D Information

Modeling a structure in the virtual world using three-dimensional (3D) information enhances our understanding, while also aiding in the visualization, of how a structure reacts to any disturbance. Generally, 3D point clouds are used for determining structural behavioral changes. Light detection and ranging (LiDAR) is one of the crucial ways by which a 3D point cloud dataset can be generated. Additionally, 3D cameras are commonly used to develop a point cloud containing many points on the external surface of an object around it. The main objective of this study was to compare the performance of optical sensors, namely a depth camera (DC) and terrestrial laser scanner (TLS) in estimating structural deflection. We also utilized bilateral filtering techniques, which are commonly used in image processing, on the point cloud data for enhancing their accuracy and increasing the application prospects of these sensors in structure health monitoring. The results from these sensors were validated by comparing them with the outputs from a linear variable differential transformer sensor, which was mounted on the beam during an indoor experiment. The results showed that the datasets obtained from both the sensors were acceptable for nominal deflections of 3 mm and above because the error range was less than ±10%. However, the result obtained from the TLS were better than those obtained from the DC.

scholarly journals An Automatic Tree Skeleton Extracting Method Based on Point Cloud of Terrestrial Laser Scanner

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Ronghao Li ◽  
Guochao Bu ◽  
Pei Wang
Keyword(s):  
Topological Structure ◽  
Point Cloud ◽  
Laser Scanner ◽  
High Accuracy ◽  
Terrestrial Laser Scanner ◽  
Peach Tree ◽  
Point Cloud Data ◽  
Breadth First Search ◽  
Cloud Data ◽  
Real Tree

Tree skeleton could describe the shape and topological structure of a tree, which are useful to forest researchers. Terrestrial laser scanner (TLS) can scan trees with high accuracy and speed to acquire the point cloud data, which could be used to extract tree skeletons. An adaptive extracting method of tree skeleton based on the point cloud data of TLS was proposed in this paper. The point cloud data were segmented by artificial filtration and k-means clustering, and the point cloud data of trunk and branches remained to extract skeleton. Then the skeleton nodes were calculated by using breadth first search (BFS) method, quantifying method, and clustering method. Based on their connectivity, the skeleton nodes were connected to generate the tree skeleton, which would be smoothed by using Laplace smoothing method. In this paper, the point cloud data of a toona tree and peach tree were used to test the proposed method and for comparing the proposed method with the shortest path method to illustrate the robustness and superiority of the method. The experimental results showed that the shape of tree skeleton extracted was consistent with the real tree, which showed the method proposed in the paper is effective and feasible.

scholarly journals TERRAIN EXTRACTION BY INTEGRATING TERRESTRIAL LASER SCANNER DATA AND SPECTRAL INFORMATION

2015 ◽  
Vol XL-2/W4 ◽  
pp. 45-51 ◽  
Author(s):  
C. L. Lau ◽  
S. Halim ◽  
M. Zulkepli ◽  
A. M. Azwan ◽  
W. L. Tang ◽  
...  
Keyword(s):  
Point Cloud ◽  
Laser Scanner ◽  
Digital Camera ◽  
Digital Terrain Model ◽  
Point Clouds ◽  
Spectral Information ◽  
Terrestrial Laser Scanner ◽  
Cloud Data ◽  
Terrain Model ◽  
Colour Image

The extraction of true terrain points from unstructured laser point cloud data is an important process in order to produce an accurate digital terrain model (DTM). However, most of these spatial filtering methods just utilizing the geometrical data to discriminate the terrain points from nonterrain points. The point cloud filtering method also can be improved by using the spectral information available with some scanners. Therefore, the objective of this study is to investigate the effectiveness of using the three-channel (red, green and blue) of the colour image captured from built-in digital camera which is available in some Terrestrial Laser Scanner (TLS) for terrain extraction. In this study, the data acquisition was conducted at a mini replica landscape in Universiti Teknologi Malaysia (UTM), Skudai campus using Leica ScanStation C10. The spectral information of the coloured point clouds from selected sample classes are extracted for spectral analysis. The coloured point clouds which within the corresponding preset spectral threshold are identified as that specific feature point from the dataset. This process of terrain extraction is done through using developed Matlab coding. Result demonstrates that a higher spectral resolution passive image is required in order to improve the output. This is because low quality of the colour images captured by the sensor contributes to the low separability in spectral reflectance. In conclusion, this study shows that, spectral information is capable to be used as a parameter for terrain extraction.

scholarly journals SCAN PROFILES BASED METHOD FOR SEGMENTATION AND EXTRACTION OF PLANAR OBJECTS IN MOBILE LASER SCANNING POINT CLOUDS

2016 ◽  
Vol XLI-B3 ◽  
pp. 351-358 ◽  
Author(s):  
Hoang Long Nguyen ◽  
David Belton ◽  
Petra Helmholz
Keyword(s):  
Spatial Data ◽  
Point Cloud ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Point Clouds ◽  
Point Cloud Data ◽  
Segmentation Method ◽  
Cloud Data ◽  
Processing Steps ◽  
Carrier Vehicle

The demand for accurate spatial data has been increasing rapidly in recent years. Mobile laser scanning (MLS) systems have become a mainstream technology for measuring 3D spatial data. In a MLS point cloud, the point clouds densities of captured point clouds of interest features can vary: they can be sparse and heterogeneous or they can be dense. This is caused by several factors such as the speed of the carrier vehicle and the specifications of the laser scanner(s). The MLS point cloud data needs to be processed to get meaningful information e.g. segmentation can be used to find meaningful features (planes, corners etc.) that can be used as the inputs for many processing steps (e.g. registration, modelling) that are more difficult when just using the point cloud. Planar features are dominating in manmade environments and they are widely used in point clouds registration and calibration processes. There are several approaches for segmentation and extraction of planar objects available, however the proposed methods do not focus on properly segment MLS point clouds automatically considering the different point densities. This research presents the extension of the segmentation method based on planarity of the features. This proposed method was verified using both simulated and real MLS point cloud datasets. The results show that planar objects in MLS point clouds can be properly segmented and extracted by the proposed segmentation method.

scholarly journals STUDI PEMANFAATAN TEKNOLOGI TERRESTRIAL LASER SCANNER UNTUK MENGHITUNG VOLUME PENGUPASAN OVERBURDEN DI PIT 2 ELEKTRIFIKASI BANKO BARAT PT. BUKIT ASAM, TBK. TANJUNG ENIM, SUMATERA SELATAN

2019 ◽  
Vol 1 (1) ◽  
pp. 47-60
Author(s):  
Ezil Defri Maharfi ◽  
Taufik Arief ◽  
Diana Purbasari
Keyword(s):  
Point Cloud ◽  
Laser Scanner ◽  
Point Clouds ◽  
Terrestrial Laser Scanner ◽  
Total Station ◽  
Cloud Data ◽  
Data Point ◽  
Cut And Fill

PT. Bukit Asam, Tbk. merupakan perusahaan pertambangan batubara yang terletak di Tanjung Enim, Kabupaten Muara Enim, Provinsi Sumatera Selatan. Selama ini pengukuran volume pengupasan overburden dilakukan menggunakan alat Total Station. Pengukuran area overburden yang luas dan bentuk permukaan yang beragam menggunakan Total Station dinilai kurang efektif karena lamanya waktu yang dibutuhkan dan rendahnya tingkat ketelitian. Oleh kerena itu, diperlukan alat yang dapat mengukur volume dengan cepat serta menghasilkan data ukuran volume yang detail dan dengan kerapatan tinggi. Salah satunya yaitu penggunaan Terrestrial Laser Scanner. Metode yang digunakan dalam melakukan pengukuran yaitu metode occupation and backsight. Pengukuran menggunakan metode occupation and backsight diperlukan dua titik yang telah diketahui koordinatnya yang digunakan sebagai titik berdiri alat dan untuk titik acuan (backsight). Metode registrasi yang digunakan yaitu metode occupation and backsight dan metode cloud to cloud. Data point clouds yang telah diregistrasi perlu dilakukan filtering untuk menghilangkan noise dan objek asing yang bukan lapisan overburden. Perhitungan volume dilakukan dengan metode cut and fill terhadap model tiga dimensi dari point cloud yang terbentuk. Data hasil perhitungan didapatkan volume pengupasan overburden selama Desember 2017 sampai dengan Mei 2018 adalah sebesar 847.937 m3, dengan rincian 255.700 m3 di bulan Desember 2017, 299.120 m3 di bulan Januari 2018, 227.543 m3 di Bulan Februari 2018 dan 65.572 m3 di bulan Maret 2018.

scholarly journals DRAWING AND LANDSCAPE SIMULATION FOR JAPANESE GARDEN BY USING TERRESTRIAL LASER SCANNER

2015 ◽  
Vol XL-4/W5 ◽  
pp. 233-238
Author(s):  
R. Kumazaki ◽  
Y. Kunii
Keyword(s):  
Point Cloud ◽  
Landscape Architecture ◽  
Laser Scanner ◽  
Terrestrial Laser Scanner ◽  
3D Point Cloud ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Contour Lines ◽  
Japanese Garden ◽  
Laser Scanners

Recently, many laser scanners are applied for various measurement fields. This paper investigates that it was useful to use the terrestrial laser scanner in the field of landscape architecture and examined a usage in Japanese garden. As for the use of 3D point cloud data in the Japanese garden, it is the visual use such as the animations. Therefore, some applications of the 3D point cloud data was investigated that are as follows. Firstly, ortho image of the Japanese garden could be outputted for the 3D point cloud data. Secondly, contour lines of the Japanese garden also could be extracted, and drawing was became possible. Consequently, drawing of Japanese garden was realized more efficiency due to achievement of laborsaving. Moreover, operation of the measurement and drawing could be performed without technical skills, and any observers can be operated. Furthermore, 3D point cloud data could be edited, and some landscape simulations that extraction and placement of tree or some objects were became possible. As a result, it can be said that the terrestrial laser scanner will be applied in landscape architecture field more widely.

scholarly journals Methods and considerations to determine sphere center from terrestrial laser scanner point cloud data

2017 ◽  
Vol 28 (10) ◽  
pp. 105001 ◽  
Author(s):  
Prem Rachakonda ◽  
Bala Muralikrishnan ◽  
Luc Cournoyer ◽  
Geraldine Cheok ◽  
Vincent Lee ◽  
...  
Keyword(s):  
Point Cloud ◽  
Laser Scanner ◽  
Terrestrial Laser Scanner ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Sphere Center
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