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 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 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 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 Fitting Terrestrial Laser Scanner Point Clouds with T-Splines: Local Refinement Strategy for Rigid Body Motion

2021 ◽  
Vol 13 (13) ◽  
pp. 2494
Author(s):  
Gaël Kermarrec ◽  
Niklas Schild ◽  
Jan Hartmann
Keyword(s):  
Point Cloud ◽  
Goodness Of Fit ◽  
Laser Scanner ◽  
Point Clouds ◽  
Statistical Testing ◽  
Computational Time ◽  
Terrestrial Laser Scanner ◽  
Reference Surface ◽  
Local Refinement ◽  
Surface Approximation

T-splines have recently been introduced to represent objects of arbitrary shapes using a smaller number of control points than the conventional non-uniform rational B-splines (NURBS) or B-spline representatizons in computer-aided design, computer graphics and reverse engineering. They are flexible in representing complex surface shapes and economic in terms of parameters as they enable local refinement. This property is a great advantage when dense, scattered and noisy point clouds are approximated using least squares fitting, such as those from a terrestrial laser scanner (TLS). Unfortunately, when it comes to assessing the goodness of fit of the surface approximation with a real dataset, only a noisy point cloud can be approximated: (i) a low root mean squared error (RMSE) can be linked with an overfitting, i.e., a fitting of the noise, and should be correspondingly avoided, and (ii) a high RMSE is synonymous with a lack of details. To address the challenge of judging the approximation, the reference surface should be entirely known: this can be solved by printing a mathematically defined T-splines reference surface in three dimensions (3D) and modeling the artefacts induced by the 3D printing. Once scanned under different configurations, it is possible to assess the goodness of fit of the approximation for a noisy and potentially gappy point cloud and compare it with the traditional but less flexible NURBS. The advantages of T-splines local refinement open the door for further applications within a geodetic context such as rigorous statistical testing of deformation. Two different scans from a slightly deformed object were approximated; we found that more than 40% of the computational time could be saved without affecting the goodness of fit of the surface approximation by using the same mesh for the two epochs.

scholarly journals Displacement Study of a Large-Scale Freeform Timber Plate Structure Using a Total Station and a Terrestrial Laser Scanner

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 413 ◽  
Author(s):  
Anh Chi Nguyen ◽  
Yves Weinand
Keyword(s):  
Large Scale ◽  
Numerical Models ◽  
Laser Scanner ◽  
Experimental Tests ◽  
Point Clouds ◽  
Element Model ◽  
Experimental Investigations ◽  
Bottom Surface ◽  
Terrestrial Laser Scanner ◽  
Total Station

Recent advances in timber construction have led to the realization of complex timber plate structures assembled with wood-wood connections. Although advanced numerical modelling tools have been developed to perform their structural analysis, limited experimental tests have been carried out on large-scale structures. However, experimental investigations remain necessary to better understand their mechanical behaviour and assess the numerical models developed. In this paper, static loading tests performed on timber plate shells of about 25 m span are reported. Displacements were measured at 16 target positions on the structure using a total station and on its entire bottom surface using a terrestrial laser scanner. Both methods were compared to each other and to a finite element model in which the semi-rigidity of the connections was represented by springs. Total station measurements provided more consistent results than point clouds, which nonetheless allowed the visualization of displacement fields. Results predicted by the model were found to be in good agreement with the measurements compared to a rigid model. The semi-rigid behaviour of the connections was therefore proven to be crucial to precisely predict the behaviour of the structure. Furthermore, large variations were observed between as-built and designed geometries due to the accumulation of fabrication and construction tolerances.

scholarly journals Accuracy Analysis Of Three Dimensional Models Of Building Prof. H. Soedarto S. H. Using The Terrestrial Laser Scanner Technology Based On Traverse Method

Teknik ◽  
2019 ◽  
Vol 39 (2) ◽  
pp. 94
Author(s):  
Yudo Prasetyo
Keyword(s):  
Point Cloud ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Terrestrial Laser Scanner ◽  
Accuracy Analysis ◽  
Dimensional Models ◽  
Data Point ◽  
Three Dimensional Models

Teknologi dokumentasi gedung secara spasial untuk konservasi dan perencanaan tata ruang semakin berkembang pesat. Urgensi tingkat ketelitian dalam suatu pengukuran juga dituntut semakin tinggi. Salah satu teknologi pembentukan objek tiga dimensi yang berkembang saat ini adalah Terrestrial Laser Scanner (TLS). Metode pengukuran TLS terdiri atas 4 metode yaitu: Cloud to Cloud, Target to Target, Traverse, dan metode kombinasi. Penelitian ini bertujuan untuk menganalisa tingkat ketelitian metode Traverse dalam pengukuran suatu objek model tiga dimensi untuk keperluan dokumentasi gedung menggunakan TLS.Ketelitian metode Traverse akan diujikan pada Gedung Prof. H. Soedarto, S. H. Tingkat ketelitiannya diujikan pada dua parameter yakni hasil metode registrasi dan hasil visualisasi model tiga dimensi. Hasil analisis pengolahan data point cloud menunjukkan bahwa alat TLS dengan metode Traverse dapat digunakan untuk menghasilkan model tiga dimensi Gedung Prof. Sudarto, S. H. Nilai rata-rata validasi yang diperoleh adalah sebesar 0,004 meter dengan besaran ketelitian model RMSE sebesar ±0,00611 meter. 

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 PERSPECTIVE INTENSITY IMAGES FOR CO-REGISTRATION OF TERRESTRIAL LASER SCANNER AND DIGITAL CAMERA

2016 ◽  
Vol XLI-B3 ◽  
pp. 295-300
Author(s):  
Yubin Liang ◽  
Yan Qiu ◽  
Tiejun Cui
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Least Squares Method ◽  
Laser Scanner ◽  
Digital Camera ◽  
Point Clouds ◽  
Terrestrial Laser Scanner ◽  
Automatic Registration ◽  
Intensity Images ◽  
Intensity Image

Co-registration of terrestrial laser scanner and digital camera has been an important topic of research, since reconstruction of visually appealing and measurable models of the scanned objects can be achieved by using both point clouds and digital images. This paper presents an approach for co-registration of terrestrial laser scanner and digital camera. A perspective intensity image of the point cloud is firstly generated by using the collinearity equation. Then corner points are extracted from the generated perspective intensity image and the camera image. The fundamental matrix F is then estimated using several interactively selected tie points and used to obtain more matches with RANSAC. The 3D coordinates of all the matched tie points are directly obtained or estimated using the least squares method. The robustness and effectiveness of the presented methodology is demonstrated by the experimental results. Methods presented in this work may also be used for automatic registration of terrestrial laser scanning point clouds.

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