Ground Deformation Data from GEER Investigations of Ridgecrest Earthquake Sequence

2020 ◽  
Vol 91 (4) ◽  
pp. 2024-2034 ◽  
Author(s):  
Scott J. Brandenberg ◽  
Jonathan P. Stewart ◽  
Pengfei Wang ◽  
Chukwuebuka C. Nweke ◽  
Kenneth Hudson ◽  
...  
Keyword(s):  
Ground Deformation ◽  
Point Clouds ◽  
Earthquake Sequence ◽  
Digital Cameras ◽  
Fault Rupture ◽  
Ground Deformations ◽  
Measuring Devices ◽  
Surface Models ◽  
Data Products ◽  
Aerial Vehicle

Abstract Following the Ridgecrest earthquake sequence, consisting of an M 6.4 foreshock and M 7.1 mainshock along with many other events, the Geotechnical Extreme Events Reconnaissance association deployed a team to gather perishable data. The team focused their efforts on documenting ground deformations including surface fault rupture south of the Naval Air Weapons Station China Lake, and liquefaction features in Trona and Argus. The team published a report within two weeks of the M 7.1 mainshock. This article presents data products gathered by the team, which are now published and publicly accessible. The data products presented herein include ground-based observations using Global Positioning System trackers, digital cameras, and hand-measuring devices, as well as unmanned aerial vehicle-based imaging products using Structure from Motion to create point clouds and digital surface models. The article describes the data products, as well as tools available for interacting with the products.

Documentation of Surface Fault Rupture and Ground-Deformation Features Produced by the 4 and 5 July 2019 Mw 6.4 and Mw 7.1 Ridgecrest Earthquake Sequence

2020 ◽  
Vol 91 (5) ◽  
pp. 2942-2959 ◽  
Author(s):  
Daniel J. Ponti ◽  
James Luke Blair ◽  
Carla M. Rosa ◽  
Kate Thomas ◽  
Alexandra J. Pickering ◽  
...  
Keyword(s):  
Slope Failure ◽  
Ground Deformation ◽  
Field Measurements ◽  
Earthquake Hazard ◽  
Earthquake Sequence ◽  
Digital Data ◽  
Fault Rupture ◽  
Ground Failure ◽  
Eastern California Shear Zone ◽  
Deformation Features

Abstract The Mw 6.4 and Mw 7.1 Ridgecrest earthquake sequence occurred on 4 and 5 July 2019 within the eastern California shear zone of southern California. Both events produced extensive surface faulting and ground deformation within Indian Wells Valley and Searles Valley. In the weeks following the earthquakes, more than six dozen scientists from government, academia, and the private sector carefully documented the surface faulting and ground-deformation features. As of December 2019, we have compiled a total of more than 6000 ground observations; approximately 1500 of these simply note the presence or absence of fault rupture or ground failure, but the remainder include detailed descriptions and other documentation, including tens of thousands of photographs. More than 1100 of these observations also include quantitative field measurements of displacement sense and magnitude. These field observations were supplemented by mapping of fault rupture and ground-deformation features directly in the field as well as by interpreting the location and extent of surface faulting and ground deformation from optical imagery and geodetic image products. We identified greater than 68 km of fault rupture produced by both earthquakes as well as numerous sites of ground deformation resulting from liquefaction or slope failure. These observations comprise a dataset that is fundamental to understanding the processes that controlled this earthquake sequence and for improving earthquake hazard estimates in the region. This article documents the types of data collected during postearthquake field investigations, the compilation effort, and the digital data products resulting from these efforts.

scholarly journals IMPROVING VERTICAL ACCURACY OF UAV DIGITAL SURFACE MODELS BY INTRODUCING TERRESTRIAL LASER SCANS ON A POINT-CLOUD LEVEL

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 457-463
Author(s):  
T. Ivelja ◽  
B. Bechor ◽  
O. Hasan ◽  
S. Miko ◽  
D. Sivan ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Point Clouds ◽  
Scene Reconstruction ◽  
Control Points ◽  
Ground Control Points ◽  
Surface Models ◽  
Aerial Vehicle ◽  
Vertical Accuracy ◽  
3D Scene ◽  
3D Scene Reconstruction

Abstract. Digital Surface Models (DSM) generated by image-based scene reconstruction from Unmanned Aerial Vehicle (UAV) and Terrestrial Laser Scanning (TLS)point clouds are highly distinguished in terms of resolution and accuracy. This leads to a situation where users have to choose the most beneficial product to fulfill their needs. In the current study, these techniques no longer compete but complement each other. Experiments were implemented to verify the improvement of vertical accuracy by introducing different amounts and configurations of Terrestrial Laser scans in the photogrammetric Structure from Motion (SfM) workflow for high-resolution 3D-scene reconstruction. Results show that it is possible to significantly improve (∼ 49% ) the vertical accuracy of DSMs by introducing a TLS point clouds. However, accuracy improvement is highly associated with the number of introduced Ground Control Points (GCP) in the SfM workflow procedure.

scholarly journals Unmanned Aerial Vehicle Surveying For Monitoring Road Construction Earthworks

2019 ◽  
Vol 14 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Kalev Julge ◽  
Artu Ellmann ◽  
Romet Köök
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Road Construction ◽  
Point Clouds ◽  
Satellite System ◽  
Ground Control Points ◽  
Surface Models ◽  
Aerial Vehicle ◽  
Global Navigation Satellite ◽  
Sand And Gravel ◽  
The Impact

Unmanned aerial vehicle photogrammetry is a surveying technique that enables generating point clouds, 3D surface models and orthophoto mosaics. These are based on photos captured with a camera placed on an unmanned aerial vehicle. Within the framework of this research, unmanned aerial vehicle photogrammetry surveys were carried out over a sand and gravel embankment with the aim of assessing the vertical accuracy of the derived surface models. Flight altitudes, ground control points and cameras were varied, and the impact of various factors on the results was monitored. In addition, the traditional real-time-kinematic Global Navigation Satellite System surveys were conducted for verifications. Surface models acquired by different methods were used to calculate volumes and compare the results with requirements set by Estonian Road Administration. It was found that with proper measuring techniques an accuracy of 5.7 cm for the heights were achieved.

scholarly journals Macrozonation of Seismic Transient Ground Displacement and Permanent Ground Deformation of Iran

2020 ◽  
Author(s):  
Saeideh Farahani ◽  
Behrouz Behnam ◽  
Ahmad Tahershamsi
Keyword(s):  
Risk Assessment ◽  
Ground Deformation ◽  
Seismic Hazards ◽  
Specific Region ◽  
Fault Rupture ◽  
Ground Displacement ◽  
Ground Deformations ◽  
Collision Zone ◽  
Macro Scale ◽  
Permanent Ground Deformation

Abstract. Iran is located on the Alpide earthquake belt, in the active collision zone between the Eurasian and Arabian plates. This issue makes Iran a country that suffers from geotechnical seismic hazards associated with frequent destructive earthquakes. Also, according to the rapid growth of population and demands for construction lifelines, the risk assessment studies which should be carried out in order to reduce the probable damages is necessary. The most important destructive effects of earthquakes on lifelines are transient ground displacements and permanent ground deformations. The availability of the map of the displacements caused by liquefaction, landslide, and surface fault rupture can be a useful reference for researchers and engineers who want to carry out a risk assessment project for each specific region of the country. In this study, the mentioned precise maps by using a considerable number of GIS-based analyses and by employing HAZUS methodology, are produced and presented. It is important to note that a required accuracy for risk assessment is approximately around the macro scale. So, in order to produce a suitable map for risk assessment goals, in terms of accuracy, the GIS-based analyses are employed to mapping all spread of Iran.

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 Robust autonomous flight in cluttered environment using a depth sensor

2020 ◽  
Vol 12 ◽  
pp. 175682932092452
Author(s):  
Liang Lu ◽  
Alexander Yunda ◽  
Adrian Carrio ◽  
Pascual Campoy
Keyword(s):  
High Speed ◽  
Point Clouds ◽  
Depth Sensor ◽  
Cluttered Environments ◽  
Industrial Plants ◽  
Cluttered Environment ◽  
Navigation Strategy ◽  
Physical Sensors ◽  
Aerial Vehicle ◽  
Planning Objective

This paper presents a novel collision-free navigation system for the unmanned aerial vehicle based on point clouds that outperform compared to baseline methods, enabling high-speed flights in cluttered environments, such as forests or many indoor industrial plants. The algorithm takes the point cloud information from physical sensors (e.g. lidar, depth camera) and then converts it to an occupied map using Voxblox, which is then used by a rapid-exploring random tree to generate finite path candidates. A modified Covariant Hamiltonian Optimization for Motion Planning objective function is used to select the best candidate and update it. Finally, the best candidate trajectory is generated and sent to a Model Predictive Control controller. The proposed navigation strategy is evaluated in four different simulation environments; the results show that the proposed method has a better success rate and a shorter goal-reaching distance than the baseline method.

scholarly journals Comparing High Accuracy t-LiDAR and UAV-SfM Derived Point Clouds for Geomorphological Change Detection

2021 ◽  
Vol 10 (6) ◽  
pp. 367
Author(s):  
Simoni Alexiou ◽  
Georgios Deligiannakis ◽  
Aggelos Pallikarakis ◽  
Ioannis Papanikolaou ◽  
Emmanouil Psomiadis ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Change Detection ◽  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Mean Value ◽  
Detection Methods ◽  
Mountainous Catchments ◽  
Aerial Vehicle ◽  
Soil Erosion Assessment

Analysis of two small semi-mountainous catchments in central Evia island, Greece, highlights the advantages of Unmanned Aerial Vehicle (UAV) and Terrestrial Laser Scanning (TLS) based change detection methods. We use point clouds derived by both methods in two sites (S1 & S2), to analyse the effects of a recent wildfire on soil erosion. Results indicate that topsoil’s movements in the order of a few centimetres, occurring within a few months, can be estimated. Erosion at S2 is precisely delineated by both methods, yielding a mean value of 1.5 cm within four months. At S1, UAV-derived point clouds’ comparison quantifies annual soil erosion more accurately, showing a maximum annual erosion rate of 48 cm. UAV-derived point clouds appear to be more accurate for channel erosion display and measurement, while the slope wash is more precisely estimated using TLS. Analysis of Point Cloud time series is a reliable and fast process for soil erosion assessment, especially in rapidly changing environments with difficult access for direct measurement methods. This study will contribute to proper georesource management by defining the best-suited methodology for soil erosion assessment after a wildfire in Mediterranean environments.

scholarly journals Application of UAV-SfM photogrammetry and aerial lidar to a disastrous flood: repeated topographic measurement of a newly formed crevasse splay of the Kinu River, central Japan

2017 ◽  
Vol 17 (9) ◽  
pp. 1505-1519 ◽  
Author(s):  
Atsuto Izumida ◽  
Shoichiro Uchiyama ◽  
Toshihiko Sugai
Keyword(s):  
Lidar Data ◽  
High Definition ◽  
Central Japan ◽  
Aerial Photos ◽  
Data Resolution ◽  
Disastrous Flood ◽  
Surface Models ◽  
Elevation Changes ◽  
Aerial Vehicle ◽  
Crevasse Splay

Abstract. Geomorphic impacts of a disastrous crevasse splay that formed in September 2015 and its post-formation modifications were quantitatively documented by using repeated, high-definition digital surface models (DSMs) of an inhabited and cultivated floodplain of the Kinu River, central Japan. The DSMs were based on pre-flood (resolution: 2 m) and post-flood (resolution: 1 m) aerial light detection and ranging (lidar) data from January 2007 and September 2015, respectively, and on structure-from-motion (SfM) photogrammetry data (resolution: 3.84 cm) derived from aerial photos taken by an unmanned aerial vehicle (UAV) in December 2015. After elimination of systematic errors among the DSMs and down-sampling of the SfM-derived DSM, elevation changes on the order of 10−1 m – including not only topography but also growth of vegetation, vanishing of flood waters, and restoration and repair works – were detected. Comparison of the DSMs showed that the volume eroded by the flood was more than twice the deposited volume in the area within 300–500 m of the breached artificial levee, where the topography was significantly affected. The results suggest that DSMs based on a combination of UAV-SfM and lidar data can be used to quantify, rapidly and in rich detail, topographic changes on floodplains caused by floods.

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