scholarly journals APPLICABILITY ASSESSMENT OF UAV MAPPING FOR DISASTER DAMAGE INVESTIGATION IN KOREA

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 209-214
Author(s):  
S. S. Kim ◽  
T. H. Kim ◽  
J. S. Sim
Keyword(s):  
Natural Disaster ◽  
Disaster Recovery ◽  
Field Survey ◽  
Central Government ◽  
Three Dimensional ◽  
Aerial Photographs ◽  
Mapping Technique ◽  
Cloud Data ◽  
Damage Area ◽  
Damage Investigation

<p><strong>Abstract.</strong> As natural disaster occurs, the local and the central government should investigate the damaged fields promptly, analyze quantitatively the degree of damage, and establish an appropriate disaster recovery plan in accordance with Framework Act on the Management of Disasters and Safety in Korea. The purpose of this study is to assess the applicability of UAV photogrammetry for the management of natural disaster. First, we suggest small easy-to-use UAV-based investigation procedure for natural disaster damaged area in the phase of disaster recovery in Korea. Before drone-based aerial surveying, the field survey can be performed with DGPS RTK for GCPs setting-up around disaster site. In this paper, we generate three dimensional terrain information and high-resolution ortho-imagery and then analyse quantitatively damage degree by natural disaster using commercial UAVs and drone mapping technique. Finally, we evaluate the mapping accuracy and work efficiency of drone mapping for disaster investigation application through comparing with traditional investigation work process which was dependent on labour-intensive field survey. The resolution ortho-image map of within less 5cm of GSD generated by aerial photographs acquired from UAVs at the altitude of 100m~250m enabled us to check damage information such as facilities destroy or the trace of soil erosion around the river flooded and reservoir collapsed area. In addition, three dimensional point cloud data of landslide-damaged areas enabled us to more accurately measure the width and the depth of outflows caused by landslides, soil runoff distance, and landslide damage area. The photogrammetry-based drone mapping technology for the disaster damage investigation is expected to be an alternative approach to support or replace the labour-intensive disaster site survey that needs to investigate the disaster site quickly and timely.</p>

scholarly journals Multi-Dimensional Underwater Point Cloud Detection Based on Deep Learning

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 884
Author(s):  
Chia-Ming Tsai ◽  
Yi-Horng Lai ◽  
Yung-Da Sun ◽  
Yu-Jen Chung ◽  
Jau-Woei Perng
Keyword(s):  
Deep Learning ◽  
Point Cloud ◽  
Three Dimensional ◽  
Point Clouds ◽  
Training Data ◽  
Network Architectures ◽  
Point Cloud Data ◽  
Data Types ◽  
Raw Data ◽  
Cloud Data

Numerous sensors can obtain images or point cloud data on land, however, the rapid attenuation of electromagnetic signals and the lack of light in water have been observed to restrict sensing functions. This study expands the utilization of two- and three-dimensional detection technologies in underwater applications to detect abandoned tires. A three-dimensional acoustic sensor, the BV5000, is used in this study to collect underwater point cloud data. Some pre-processing steps are proposed to remove noise and the seabed from raw data. Point clouds are then processed to obtain two data types: a 2D image and a 3D point cloud. Deep learning methods with different dimensions are used to train the models. In the two-dimensional method, the point cloud is transferred into a bird’s eye view image. The Faster R-CNN and YOLOv3 network architectures are used to detect tires. Meanwhile, in the three-dimensional method, the point cloud associated with a tire is cut out from the raw data and is used as training data. The PointNet and PointConv network architectures are then used for tire classification. The results show that both approaches provide good accuracy.

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.

Epitaxial Ni nanoparticles on CaF2(001), (110) and (111) surfaces studied by three-dimensional RHEED, GIXD and GISAXS reciprocal-space mapping techniques

2017 ◽  
Vol 50 (3) ◽  
pp. 830-839 ◽  
Author(s):  
S. M. Suturin ◽  
V. V. Fedorov ◽  
A. M. Korovin ◽  
N. S. Sokolov ◽  
A. V. Nashchekin ◽  
...  
Keyword(s):  
Lattice Structure ◽  
Three Dimensional ◽  
Grazing Incidence ◽  
High Energy ◽  
Reciprocal Space ◽  
Mapping Technique ◽  
Face Centered Cubic ◽  
X Ray ◽  
Cubic Lattice ◽  
Face Centered

The development of growth techniques aimed at the fabrication of nanoscale heterostructures with layers of ferroic 3dmetals on semiconductor substrates is very important for their potential usage in magnetic media recording applications. A structural study is presented of single-crystal nickel island ensembles grown epitaxially on top of CaF2/Si insulator-on-semiconductor heteroepitaxial substrates with (111), (110) and (001) fluorite surface orientations. The CaF2buffer layer in the studied multilayer system prevents the formation of nickel silicide, guides the nucleation of nickel islands and serves as an insulating layer in a potential tunneling spin injection device. The present study, employing both direct-space and reciprocal-space techniques, is a continuation of earlier research on ferromagnetic 3dtransition metals grown epitaxially on non-magnetic and magnetically ordered fluorides. It is demonstrated that arrays of stand-alone faceted nickel islands with a face-centered cubic lattice can be grown controllably on CaF2surfaces of (111), (110) and (001) orientations. The proposed two-stage nickel growth technique employs deposition of a thin seeding layer at low temperature followed by formation of the islands at high temperature. The application of an advanced three-dimensional mapping technique exploiting reflection high-energy electron diffraction (RHEED) has proved that the nickel islands tend to inherit the lattice orientation of the underlying fluorite layer, though they exhibit a certain amount of {111} twinning. As shown by scanning electron microscopy, grazing-incidence X-ray diffraction (GIXD) and grazing-incidence small-angle X-ray scattering (GISAXS), the islands are of similar shape, being faceted with {111} and {100} planes. The results obtained are compared with those from earlier studies of Co/CaF2epitaxial nanoparticles, with special attention paid to the peculiarities related to the differences in lattice structure of the deposited metals: the dual-phase hexagonal close-packed/face-centered cubic lattice structure of cobalt as opposed to the single-phase face-centered cubic lattice structure of nickel.

Research on Generation Rules of Chest Width Point Curve Based on 3D Female Mannequin

2013 ◽  
Vol 796 ◽  
pp. 513-518
Author(s):  
Rong Jin ◽  
Bing Fei Gu ◽  
Guo Lian Liu
Keyword(s):  
Point Cloud ◽  
Three Dimensional ◽  
Upper Body ◽  
Secondary Development ◽  
Linear Regression Method ◽  
Point Cloud Data ◽  
Body Type ◽  
Cloud Data ◽  
Engineering Software ◽  
The Individual

In this paper 110 female undergraduates in Soochow University are measured by using 3D non-contact measurement system and manual measurement. 3D point cloud data of human body is taken as research objects by using anti-engineering software, and secondary development of point cloud data is done on the basis of optimizing point cloud data. In accordance with the definition of the human chest width points and other feature points, and in the operability of the three-dimensional point cloud data, the width, thickness, and length dimensions of the curve through the chest width point are measured. Classification of body type is done by choosing the ratio values as classification index which is the ratio between thickness and width of the curve. The generation rules of the chest curve are determined for each type by using linear regression method. Human arm model could be established by the computer automatically. Thereby the individual model of the female upper body mannequin modeling can be improved effectively.

Automated Surface Inspection Using 3D Point Cloud Data in Manufacturing: A Case Study

2018 ◽  
Author(s):  
Romina Dastoorian ◽  
Ahmad E. Elhabashy ◽  
Wenmeng Tian ◽  
Lee J. Wells ◽  
Jaime A. Camelio
Keyword(s):  
Point Cloud ◽  
Surface Defect ◽  
Fault Location ◽  
Three Dimensional ◽  
Practical Case ◽  
3D Point Cloud ◽  
Point Cloud Data ◽  
Defect Inspection ◽  
Cloud Data

With the latest advancements in three-dimensional (3D) measurement technologies, obtaining 3D point cloud data for inspection purposes in manufacturing is becoming more common. While 3D point cloud data allows for better inspection capabilities, their analysis is typically challenging. Especially with unstructured 3D point cloud data, containing coordinates at random locations, the challenges increase with higher levels of noise and larger volumes of data. Hence, the objective of this paper is to extend the previously developed Adaptive Generalized Likelihood Ratio (AGLR) approach to handle unstructured 3D point cloud data used for automated surface defect inspection in manufacturing. More specifically, the AGLR approach was implemented in a practical case study to inspect twenty-seven samples, each with a unique fault. These faults were designed to cover an array of possible faults having three different sizes, three different magnitudes, and located in three different locations. The results show that the AGLR approach can indeed differentiate between non-faulty and a varying range of faulty surfaces while being able to pinpoint the fault location. This work also serves as a validation for the previously developed AGLR approach in a practical scenario.

scholarly journals Prospects of the WSR-88D Radar for Cloud Studies

2011 ◽  
Vol 50 (4) ◽  
pp. 859-872 ◽  
Author(s):  
Valery M. Melnikov ◽  
Dusan S. Zrnić ◽  
Richard J. Doviak ◽  
Phillip B. Chilson ◽  
David B. Mechem ◽  
...  
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Three Dimensional ◽  
High Sensitivity ◽  
Doppler Velocity ◽  
Cloud Data ◽  
Three Dimensional Mapping ◽  
Spectrum Width ◽  
Differential Reflectivity ◽  
Dimensional Mapping

AbstractSounding of nonprecipitating clouds with the 10-cm wavelength Weather Surveillance Radar-1988 Doppler (WSR-88D) is discussed. Readily available enhancements to signal processing and volume coverage patterns of the WSR-88D allow observations of a variety of clouds with reflectivities as low as −25 dBZ (at a range of 10 km). The high sensitivity of the WSR-88D, its wide velocity and unambiguous range intervals, and the absence of attenuation allow accurate measurements of the reflectivity factor, Doppler velocity, and spectrum width fields in clouds to ranges of about 50 km. Fields of polarimetric variables in clouds, observed with a research polarimetric WSR-88D, demonstrate an abundance of information and help to resolve Bragg and particulate scatter. The scanning, Doppler, and polarimetric capabilities of the WSR-88D allow real-time, three-dimensional mapping of cloud processes, such as transformations of hydrometeors between liquid and ice phases. The presence of ice particles is revealed by high differential reflectivities and the lack of correlation between reflectivity and differential reflectivity in clouds in contrast to that found for rain. Pockets of high differential reflectivities are frequently observed in clouds; maximal values of differential reflectivity exceed 8 dB, far above the level observed in rain. The establishment of the WSR-88D network consisting of 157 polarimetric radars can be used to collect cloud data at any radar site, making the network a potentially powerful tool for climatic studies.

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