Using Video Acquired from an Unmanned Aerial Vehicle (UAV) to Measure Fracture Orientation in an Open-Pit Mine

GEOMATICA ◽  
2013 ◽  
Vol 67 (3) ◽  
pp. 173-180 ◽  
Author(s):  
T. McLeod ◽  
C. Samson ◽  
M. Labrie ◽  
K. Shehata ◽  
J. Mah ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Three Dimensional ◽  
Mining Industry ◽  
Point Clouds ◽  
Video Camera ◽  
Open Pit ◽  
Original Video ◽  
3D Point Clouds ◽  
Video Images ◽  
Aerial Vehicle

This project explored the feasibility of using video images acquired with an unmanned aerial vehicle (UAV) to obtain three-dimensional (3D) point clouds using structure from motion (SfM) software. Missions were flown using an Aeryon Scout: a lightweight, vertical take-off and landing quadrotor micro UAV with a miniature video camera. The initial mission captured urban scene images that were used to assess system performance while the main mission focused on rock walls where 3D images were used to successfully measure fracture orientations. Point clouds generated from this combination of technologies were sparse, but in the future, improvements in the resolution of original video images would cascade through the processing and improve the overall results. Such a system could have a multitude of applications in the mining industry, contributing to both safety and financial considerations.

scholarly journals Symmetry Analysis of Oriental Polygonal Pagodas Using 3D Point Clouds for Cultural Heritage

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1228
Author(s):  
Ting On Chan ◽  
Linyuan Xia ◽  
Yimin Chen ◽  
Wei Lang ◽  
Tingting Chen ◽  
...  
Keyword(s):  
Cultural Heritage ◽  
Unmanned Aerial Vehicle ◽  
Point Cloud ◽  
Geometric Model ◽  
Digital Camera ◽  
Point Clouds ◽  
Symmetry Analysis ◽  
3D Point Clouds ◽  
Transmission Towers ◽  
Aerial Vehicle

Ancient pagodas are usually parts of hot tourist spots in many oriental countries due to their unique historical backgrounds. They are usually polygonal structures comprised by multiple floors, which are separated by eaves. In this paper, we propose a new method to investigate both the rotational and reflectional symmetry of such polygonal pagodas through developing novel geometric models to fit to the 3D point clouds obtained from photogrammetric reconstruction. The geometric model consists of multiple polygonal pyramid/prism models but has a common central axis. The method was verified by four datasets collected by an unmanned aerial vehicle (UAV) and a hand-held digital camera. The results indicate that the models fit accurately to the pagodas’ point clouds. The symmetry was realized by rotating and reflecting the pagodas’ point clouds after a complete leveling of the point cloud was achieved using the estimated central axes. The results show that there are RMSEs of 5.04 cm and 5.20 cm deviated from the perfect (theoretical) rotational and reflectional symmetries, respectively. This concludes that the examined pagodas are highly symmetric, both rotationally and reflectionally. The concept presented in the paper not only work for polygonal pagodas, but it can also be readily transformed and implemented for other applications for other pagoda-like objects such as transmission towers.

scholarly journals Estimating forest uniformity in Eucalyptus spp. and Pinus taeda L. stands using field measurements and structure from motion point clouds generated from unmanned aerial vehicle (UAV) data collection

2018 ◽  
Vol 27 (2) ◽  
pp. e005 ◽  
Author(s):  
Ângela M. K. Hentz ◽  
Carlos A. Silva ◽  
Ana P. Dalla Corte ◽  
Sylvio P. Netto ◽  
Michael P. Strager ◽  
...  
Keyword(s):  
Pinus Taeda ◽  
Unmanned Aerial Vehicle ◽  
Digital Terrain Model ◽  
Tree Height ◽  
Point Clouds ◽  
Forest Monitoring ◽  
Surface Model ◽  
3D Point Clouds ◽  
Aerial Vehicle ◽  
Pinus Taeda L

Aim of study: In this study we applied 3D point clouds generated by images obtained from an Unmanned Aerial Vehicle (UAV) to evaluate the uniformity of young forest stands.Area of study: Two commercial forest stands were selected, with two plots each. The forest species studied were Eucalyptus spp. and Pinus taeda L. and the trees had an age of 1.5 years.Material and methods: The individual trees were detected based on watershed segmentation and local maxima, using the spectral values stored in the point cloud. After the tree detection, the heights were calculated using two approaches, in the first one using the Digital Surface Model (DSM) and a Digital Terrain Model, and in the second using only the DSM. We used the UAV-derived heights to estimate an uniformity index.Main results: The trees were detected with a maximum 6% of error. However, the height was underestimated in all cases, in an average of 1 and 0.7 m for Pinus and Eucalyptus stands. We proposed to use the models built herein to estimate tree height, but the regression models did not explain the variably within the data satisfactorily. Therefore, the uniformity index calculated using the direct UAV-height values presented results close to the field inventory, reaching better results when using the second height approach (error ranging 2.8-7.8%).Research highlights: The uniformity index using the UAV-derived height from the proposed methods was close to the values obtained in field. We noted the potential for using UAV imagery in forest monitoring.

scholarly journals Coupling Satellite Images and Unmanned Aerial Vehicle Data to Monitor the Exploitation of Open-Pit Mine

2020 ◽  
Vol 1 (2) ◽  
Author(s):  
Tong Si Son ◽  
Quang Toan LE ◽  
Thi-Huyen-Ai TONG ◽  
Vu Giang NGUYEN ◽  
Phan Long VU ◽  
...  
Keyword(s):  
Land Cover ◽  
Unmanned Aerial Vehicle ◽  
Satellite Images ◽  
Mining Industry ◽  
Open Pit Mine ◽  
Open Pit ◽  
Remote Sensing Technique ◽  
Vertical Range ◽  
High Resolution Satellite Images ◽  
Aerial Vehicle

Discovering the variation of an open-pit mine in vertical, horizontal, and temporal dimensions as well to characterize the stages and the trends of the exploitation are indispensable tasks which provide information supporting decision making and planning for sustainable development of the mining industry. Remote sensing technique with the advantages of multi-spatial, multi-spectral, multi-temporal resolution is a promising solution to meet the  information requirement. This study proposes an approach of coupling the high-resolution satellite images and Unmanned Aerial Vehicle (UAV) data to observe the variation of Tan An open rocky mine during its lifetime. Five satellite images with the resolution of 0.5 m acquired in 2006, 2012, 2014, 2016, 2018, and two ortho-images with 0.034 m resolution constructed from UAV photos captured in 2019, 2020 are used to make land cover maps. The analysis of land cover changes discovers 3 stages of open-pit mine exploitation consisting of unprompted exploitation, exploiting outbreak and stable exploitation corresponding to the changes in the mine. Besides, two Digital Surface Models (DSM) constructed by UAV photos are compared to calculate the elevation and volume changes. The assessment of the correlation between elevation change and land cover change indicates that the mineral exploitation is in the vertical range from 645 m to 660 m, and the exploitation trend is following the horizontal expansion rather than the deep excavation. Additionally, this experiment results in 79,422 m3 of mineral taken from the mine, and 34,022 m3 of soil used for the restoration within a year from June 2019 to June 2020.

scholarly journals Classification of 3D Point Clouds Using Color Vegetation Indices for Precision Viticulture and Digitizing Applications

2020 ◽  
Vol 12 (2) ◽  
pp. 317 ◽  
Author(s):  
Francisco-Javier Mesas-Carrascosa ◽  
Ana I. de Castro ◽  
Jorge Torres-Sánchez ◽  
Paula Triviño-Tarradas ◽  
Francisco M. Jiménez-Brenes ◽  
...  
Keyword(s):  
Management Strategies ◽  
Vegetation Indices ◽  
Three Dimensional ◽  
Point Clouds ◽  
Bare Soil ◽  
3D Point Clouds ◽  
Aerial Vehicle ◽  
Precision Viticulture ◽  
3D Information

Remote sensing applied in the digital transformation of agriculture and, more particularly, in precision viticulture offers methods to map field spatial variability to support site-specific management strategies; these can be based on crop canopy characteristics such as the row height or vegetation cover fraction, requiring accurate three-dimensional (3D) information. To derive canopy information, a set of dense 3D point clouds was generated using photogrammetric techniques on images acquired by an RGB sensor onboard an unmanned aerial vehicle (UAV) in two testing vineyards on two different dates. In addition to the geometry, each point also stores information from the RGB color model, which was used to discriminate between vegetation and bare soil. To the best of our knowledge, the new methodology herein presented consisting of linking point clouds with their spectral information had not previously been applied to automatically estimate vine height. Therefore, the novelty of this work is based on the application of color vegetation indices in point clouds for the automatic detection and classification of points representing vegetation and the later ability to determine the height of vines using as a reference the heights of the points classified as soil. Results from on-ground measurements of the heights of individual grapevines were compared with the estimated heights from the UAV point cloud, showing high determination coefficients (R² > 0.87) and low root-mean-square error (0.070 m). This methodology offers new capabilities for the use of RGB sensors onboard UAV platforms as a tool for precision viticulture and digitizing applications.

scholarly journals Forest Data Collection by UAV Lidar-Based 3D Mapping: Segmentation of Individual Tree Information from 3D Point Clouds

2021 ◽  
Vol 15 (3) ◽  
pp. 313-323
Author(s):  
Taro Suzuki ◽  
Shunichi Shiozawa ◽  
Atsushi Yamaba ◽  
Yoshiharu Amano ◽  
◽  
...  
Keyword(s):  
Point Cloud ◽  
Three Dimensional ◽  
Point Clouds ◽  
Forest Environment ◽  
Individual Tree ◽  
Single Tree ◽  
3D Point Clouds ◽  
Aerial Vehicle ◽  
Forest Measurement ◽  
Vertical Height

In this study, we develop a system for efficiently measuring detailed information of trees in a forest environment using a small unmanned aerial vehicle (UAV) equipped with light detection and ranging (lidar). The main purpose of forest measurement is to predict the volume of wood for harvesting and delineating forest boundaries by tree location. Herein, we propose a method for extracting the position, number of trees, and vertical height of trees from a set of three-dimensional (3D) point clouds acquired by a UAV lidar system. The point cloud obtained from a UAV is dense in the tree’s crown, and the trunk 3D points are sparse because the crown of the tree obstructs the laser beam. Therefore, it is difficult to extract single-tree information from 3D point clouds because the characteristics of 3D point clouds differ significantly from those of conventional 3D point clouds using ground-based laser scanners. In this study, we segment the forest point cloud into three regions with different densities of point clouds, i.e., canopy, trunk, and ground, and process each region individually to extract the target information. By comparing a ground laser survey and the proposed method in an actual forest environment, it is discovered that the number of trees in an area measuring 100 m × 100 m is 94.6% of the total number of trees. The root mean square error of the tree position is 0.3 m, whereas that of the vertical height is 2.3 m, indicating that single-tree information can be measured with sufficient accuracy for forest management.

scholarly journals Modeling Slope Topography Using Unmanned Aerial Vehicle Image Technique

2018 ◽  
Vol 147 ◽  
pp. 07002 ◽  
Author(s):  
Fu-Hsuan Yeh ◽  
Chun-Jia Huang ◽  
Jen-Yu Han ◽  
Louis Ge
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Spatial Information ◽  
Point Clouds ◽  
Image Feature ◽  
Superior Performance ◽  
Surface Model ◽  
Efficient Manner ◽  
3D Point Clouds ◽  
Wide Range ◽  
Aerial Vehicle

Nowadays, a wide range of site planning, field investigation and slope analysis need to be carried out for slope protection and landslide-related disaster reduction. To enhance the efficiency of topography modeling, unmanned aerial vehicle (UAV) has become a new surveying technique to obtain spatial information. This study aims to determine the topography of a slope by using a digital camera mounted on UAV to photograph with a high degree of overlap. The 3D point clouds data were generated through image feature point extraction integrated with accurate GPS ground control points. It is found in this study that the obtained Digital Surface Model (DSM) data, compared with the traditional field surveying techniques, has much superior performance. The resolution of the DSM has reached 1.58 cm. Also, the error of elevation and distance between DSM and actual 3D coordinates obtained by traditional total station survey is acceptance. It is clear that such a UAV surveying technique can replace conventional surveying methods and provide complete and accurate 3D topography information in automatic and highly efficient manner for most geotechnical applications.

Robotic motion compensation for bone movement, using ultrasound images

2015 ◽  
Vol 42 (5) ◽  
pp. 466-474 ◽  
Author(s):  
P.M.B. Torres ◽  
P. J. S. Gonçalves ◽  
J.M.M. Martins
Keyword(s):  
Motion Compensation ◽  
Optical Measurement ◽  
Three Dimensional ◽  
Point Clouds ◽  
Robotic System ◽  
Ultrasound Images ◽  
Bone Drilling ◽  
Content Type ◽  
3D Point Clouds ◽  
Robotic Motion

Purpose – The purpose of this paper is to present a robotic motion compensation system, using ultrasound images, to assist orthopedic surgery. The robotic system can compensate for femur movements during bone drilling procedures. Although it may have other applications, the system was thought to be used in hip resurfacing (HR) prosthesis surgery to implant the initial guide tool. The system requires no fiducial markers implanted in the patient, by using only non-invasive ultrasound images. Design/methodology/approach – The femur location in the operating room is obtained by processing ultrasound (USA) and computer tomography (CT) images, obtained, respectively, in the intra-operative and pre-operative scenarios. During surgery, the bone position and orientation is obtained by registration of USA and CT three-dimensional (3D) point clouds, using an optical measurement system and also passive markers attached to the USA probe and to the drill. The system description, image processing, calibration procedures and results with simulated and real experiments are presented and described to illustrate the system in operation. Findings – The robotic system can compensate for femur movements, during bone drilling procedures. In most experiments, the update was always validated, with errors of 2 mm/4°. Originality/value – The navigation system is based entirely on the information extracted from images obtained from CT pre-operatively and USA intra-operatively. Contrary to current surgical systems, it does not use any type of implant in the bone to track the femur movements.

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.

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