scholarly journals Short communication: A semi-automated method for rapid fault slip analysis from topographic scarp profiles

2019 ◽  
Author(s):  
Franklin D. Wolfe ◽  
Timothy A. Stahl ◽  
Pilar Villamor ◽  
Biljana Lukovic
Keyword(s):  
Monte Carlo ◽  
High Resolution ◽  
Open Source ◽  
Hanging Wall ◽  
Temporal Analysis ◽  
Fault Scarp ◽  
Fault Slip ◽  
Source Characterization ◽  
Automated Method ◽  
Wide Range

Abstract. Here, we introduce an open source, semi-automated, Python-based graphical user interface (GUI) called the Monte Carlo Slip Statistics Toolkit (MCSST) for estimating dip slip on individual or bulk fault datasets. Using this toolkit, profiles are defined across fault scarps in high-resolution digital elevation models (DEMs) and then relevant fault scarp components are interactively identified (e.g., footwall, hanging wall, and scarp). Displacement statistics are calculated automatically using Monte Carlo simulation and can be conveniently visualized in Geographic Information Systems (GIS) for spatial analysis. Fault slip rates can also be calculated when ages of footwall and hanging wall surfaces are known, allowing for temporal analysis. This method allows for rapid analysis of tens to hundreds of faults in rapid succession within GIS and a Python coding environment. Application of this method may contribute to a wide range of regional and local earthquake geology studies with adequate high-resolution DEM coverage, both regional fault source characterization for seismic hazard and/or estimating geologic slip and strain rates, including creating long-term deformation maps. ArcGIS versions of these functions are available, as well ones that utilize free, open source Quantum GIS (QGIS) and Jupyter Notebook Python software.

scholarly journals Short communication: A semiautomated method for bulk fault slip analysis from topographic scarp profiles

2020 ◽  
Vol 8 (1) ◽  
pp. 211-219
Author(s):  
Franklin D. Wolfe ◽  
Timothy A. Stahl ◽  
Pilar Villamor ◽  
Biljana Lukovic
Keyword(s):  
Monte Carlo ◽  
High Resolution ◽  
Open Source ◽  
Hanging Wall ◽  
Temporal Analysis ◽  
Fault Scarp ◽  
Fault Slip ◽  
Source Characterization ◽  
Wide Range ◽  
Fault Scarps

Abstract. Manual approaches for analyzing fault scarps in the field or with existing software can be tedious and time-consuming. Here, we introduce an open-source, semiautomated, Python-based graphical user interface (GUI) called the Monte Carlo Slip Statistics Toolkit (MCSST) for estimating dip slip on individual or bulk fault datasets that (1) makes the analysis of a large number of profiles much faster, (2) allows users with little or no coding skills to implement the necessary statistical techniques, (3) and provides geologists with a platform to incorporate their observations or expertise into the process. Using this toolkit, profiles are defined across fault scarps in high-resolution digital elevation models (DEMs), and then relevant fault scarp components are interactively identified (e.g., footwall, hanging wall, and scarp). Displacement statistics are calculated automatically using Monte Carlo simulation and can be conveniently visualized in geographic information systems (GISs) for spatial analysis. Fault slip rates can also be calculated when ages of footwall and hanging wall surfaces are known, allowing for temporal analysis. This method allows for the analysis of tens to hundreds of faults in rapid succession within GIS and a Python coding environment. Application of this method may contribute to a wide range of regional and local earthquake geology studies with adequate high-resolution DEM coverage, enabling both regional fault source characterization for seismic hazard and/or estimating geologic slip and strain rates, including creating long-term deformation maps. ArcGIS versions of these functions are available, as well as ones that utilize free, open-source Quantum GIS (QGIS) and Jupyter Notebook Python software.

scholarly journals Localized extension in megathrust hanging wall following great earthquakes in western Nepal

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Magali Riesner ◽  
Laurent Bollinger ◽  
Judith Hubbard ◽  
Cyrielle Guérin ◽  
Marthe Lefèvre ◽  
...  
Keyword(s):  
High Resolution ◽  
Hanging Wall ◽  
Ground Surface ◽  
Normal Fault ◽  
Fault Scarp ◽  
Fault System ◽  
Digital Elevation ◽  
Thrust Zone ◽  
Elevation Model ◽  
Short Time

AbstractThe largest (M8+) known earthquakes in the Himalaya have ruptured the upper locked section of the Main Himalayan Thrust zone, offsetting the ground surface along the Main Frontal Thrust at the range front. However, out-of-sequence active structures have received less attention. One of the most impressive examples of such faults is the active fault that generally follows the surface trace of the Main Boundary Thrust (MBT). This fault has generated a clear geomorphological signature of recent deformation in eastern and western Nepal, as well as further west in India. We focus on western Nepal, between the municipalities of Surkhet and Gorahi where this fault is well expressed. Although the fault system as a whole is accommodating contraction, across most of its length, this particular fault appears geomorphologically as a normal fault, indicating crustal extension in the hanging wall of the MHT. We focus this study on the reactivation of the MBT along the Surkhet-Gorahi segment of the surface trace of the newly named Reactivated Boundary Fault, which is ~ 120 km long. We first generate a high-resolution Digital Elevation Model from triplets of high-resolution Pleiades images and use this to map the fault scarp and its geomorphological lateral variation. For most of its length, normal motion slip is observed with a dip varying between 20° and 60° and a maximum cumulative vertical offset of 27 m. We then present evidence for recent normal faulting in a trench located in the village of Sukhetal. Radiocarbon dating of detrital charcoals sampled in the hanging wall of the fault, including the main colluvial wedge and overlying sedimentary layers, suggest that the last event occurred in the early sixteenth century. This period saw the devastating 1505 earthquake, which produced ~ 23 m of slip on the Main Frontal Thrust. Linked or not, the ruptures on the MFT and MBT happened within a short time period compared to the centuries of quiescence of the faults that followed. We suggest that episodic normal-sense activity of the MBT could be related to large earthquakes rupturing the MFT, given its proximity, the sense of motion, and the large distance that separates the MBT from the downdip end of the locked fault zone of the MHT fault system. We discuss these results and their implications for the frontal Himalayan thrust system.

scholarly journals RADAR-Base: Open Source Mobile Health Platform for Collecting, Monitoring, and Analyzing Data Using Sensors, Wearables, and Mobile Devices

10.2196/11734 ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. e11734 ◽  
Author(s):  
Yatharth Ranjan ◽  
Zulqarnain Rashid ◽  
Callum Stewart ◽  
Pauline Conde ◽  
Mark Begale ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Collection ◽  
Open Source ◽  
Mobile Health ◽  
Large Scale ◽  
Streaming Data ◽  
Security And Privacy ◽  
The European Union ◽  
Wide Range ◽  
Remote Assessment

Background With a wide range of use cases in both research and clinical domains, collecting continuous mobile health (mHealth) streaming data from multiple sources in a secure, highly scalable, and extensible platform is of high interest to the open source mHealth community. The European Union Innovative Medicines Initiative Remote Assessment of Disease and Relapse-Central Nervous System (RADAR-CNS) program is an exemplary project with the requirements to support the collection of high-resolution data at scale; as such, the Remote Assessment of Disease and Relapse (RADAR)-base platform is designed to meet these needs and additionally facilitate a new generation of mHealth projects in this nascent field. Objective Wide-bandwidth networks, smartphone penetrance, and wearable sensors offer new possibilities for collecting near-real-time high-resolution datasets from large numbers of participants. The aim of this study was to build a platform that would cater for large-scale data collection for remote monitoring initiatives. Key criteria are around scalability, extensibility, security, and privacy. Methods RADAR-base is developed as a modular application; the backend is built on a backbone of the highly successful Confluent/Apache Kafka framework for streaming data. To facilitate scaling and ease of deployment, we use Docker containers to package the components of the platform. RADAR-base provides 2 main mobile apps for data collection, a Passive App and an Active App. Other third-Party Apps and sensors are easily integrated into the platform. Management user interfaces to support data collection and enrolment are also provided. Results General principles of the platform components and design of RADAR-base are presented here, with examples of the types of data currently being collected from devices used in RADAR-CNS projects: Multiple Sclerosis, Epilepsy, and Depression cohorts. Conclusions RADAR-base is a fully functional, remote data collection platform built around Confluent/Apache Kafka and provides off-the-shelf components for projects interested in collecting mHealth datasets at scale.

Unlocking modern nation-scale LiDAR datasets with FOSS – the Laserchicken framework

2020 ◽  
Author(s):  
Meiert W. Grootes ◽  
Christiaan Meijer ◽  
Zsofia Koma ◽  
Bouwe Andela ◽  
Elena Ranguelova ◽  
...  
Keyword(s):  
High Resolution ◽  
Open Source ◽  
Point Cloud ◽  
Laser Scanning ◽  
Vegetation Type ◽  
Ecosystem Structure ◽  
Point Cloud Data ◽  
Ecosystem Research ◽  
Cloud Data ◽  
Wide Range

<p>LiDAR as a remote sensing technology, enabling the rapid 3D characterization of an area from an air- or spaceborne platform, has become a mainstream tool in the (bio)geosciences and related disciplines. For instance, LiDAR-derived metrics are used for characterizing vegetation type, structure, and prevalence and are widely employed across ecosystem research, forestry, and ecology/biology. Furthermore, these types of metrics are key candidates in the quest for Essential Biodiversity Variables (EBVs) suited to quantifying habitat structure, reflecting the importance of this property in assessing and monitoring the biodiversity of flora and fauna, and consequently in informing policy to safeguard it in the light of climate change an human impact.</p><p>In all these use cases, the power of LiDAR point cloud datasets resides in the information encoded within the spatial distribution of LiDAR returns, which can be extracted by calculating domain-specific statistical/ensemble properties of well-defined subsets of points.  </p><p>Facilitated by technological advances, the volume of point cloud data sets provided by LiDAR has steadily increased, with modern airborne laser scanning surveys now providing high-resolution, (super-)national scale datasets, tens to hundreds of terabytes in size and encompassing hundreds of billions of individual points, many of which are available as open data.</p><p>Representing a trove of data and, for the first time, enabling the study of ecosystem structure at meter resolution over the extent of tens to hundreds of kilometers, these datasets represent highly valuable new resources. However, their scientific exploitation is hindered by the scarcity of Free Open Source Software (FOSS) tools capable of handling the challenges of accessing, processing, and extracting meaningful information from massive multi-terabyte datasets, as well as by the domain-specificity of any existing tools.</p><p>Here we present Laserchicken a FOSS, user-extendable, cross-platform Python tool for extracting user-defined statistical properties of flexibly defined subsets of point cloud data, aimed at enabling efficient, scalable, and distributed processing of multi-terabyte datasets. Laserchicken can be seamlessly employed on computing architectures ranging from desktop systems to distributed clusters, and supports standard point cloud and geo-data formats (LAS/LAZ, PLY, GeoTIFF, etc.) making it compatible with a wide range of (FOSS) tools for geoscience.</p><p>The Laserchicken feature extraction tool is complemented by a FOSS Python processing pipeline tailored to the scientific exploitation of massive nation-scale point cloud datasets, together forming the Laserchicken framework.</p><p>The ability of the Laserchicken framework to unlock nation-scale LiDAR point cloud datasets is demonstrated on the basis of its use in the eEcoLiDAR project, a collaborative project between the University of Amsterdam and the Netherlands eScience Center. Within the eEcoLiDAR project, Laserchicken has been instrumental in defining classification methods for wetland habitats, as well as in facilitating the use of high-resolution vegetation structure metrics in modelling species distributions at national scales, with preliminary results highlighting the importance of including this information.</p><p>The Laserchicken Framework rests on FOSS, including the GDAL and PDAL libraries as well as numerous packages hosted on the open source Python Package Index (PyPI), and is itself also available as FOSS (https://pypi.org/project/laserchicken/ and https://github.com/eEcoLiDAR/ ).</p>

A new Method for Fault-Scarp Detection Using Linear Discriminant Analysis (LDA) in High-Resolution Bathymetry Data From the Alarcón Rise and Pescadero Basin, Gulf of California.

2021 ◽  
Author(s):  
Luis Angel Vega Ramirez ◽  
Ronald Michael Splez Madero ◽  
Juan Contreras Perez ◽  
David Caress ◽  
David A. Clague ◽  
...  
Keyword(s):  
High Resolution ◽  
Gulf Of California ◽  
Autonomous Underwater Vehicle ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Fault Scarp ◽  
Fault Line ◽  
Cross Sectional ◽  
Linear Discriminant ◽  
Automated Method

<p>The mapping of faults and fractures is a problem of high relevance in Earth Sciences. However, their identification in digital elevation models is a time-consuming task given the resulting networks' fractal nature. The effort is especially challenging in submarine environments, given their inaccessibility and difficulty in collecting direct observations. Here, we propose a semi-automated method for detecting faults in high-resolution gridded bathymetry data (~1 m horizontal and ~0.2 m vertical) of the Pescadero Basin in the southern Gulf of California, which were collected by MBARI's D. Allan B autonomous underwater vehicle. This problem is well suited to be explored by machine learning and deep-learning methods. The method learns from a model trained to recognize fault-line scarps based on key morphological attributes in the neighboring Alarcón Rise. We use the product of the mass diffusion coefficient with time, scarp height, and root-mean-square error as training attributes. The method consists of projecting the attributes from a three-dimensional space to a one-dimensional space in which normal probability density functions are generated to classify faults. The LDA implementation results in various cross-sectional profiles along the Pescadero Basin show that the proposed method can detect fault-line scarps of different sizes and degradation stages. Moreover, the method is robust to moderate amounts of noise (i.e., random topography and data collection artifacts) and correctly handles different fault dip angles. Experiments show that both isolated and linkage fault configurations are detected and tracked reliably.</p>

scholarly journals RADAR-base: An Open Source mHealth Platform for Collecting, Monitoring and Analyzing Data Using Sensors, Wearables, and Mobile Devices (Preprint)

2018 ◽  
Author(s):  
Yatharth Ranjan ◽  
Zulqarnain Rashid ◽  
Callum Stewart ◽  
Maximilian Kerz ◽  
Mark Begale ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Collection ◽  
Open Source ◽  
User Interfaces ◽  
Large Scale ◽  
Streaming Data ◽  
Security And Privacy ◽  
Multiple Sources ◽  
High Resolution Data ◽  
Wide Range

BACKGROUND With a wide range of use cases in both research and clinical domains, collecting continuous mobile health (mHealth) streaming data from multiple sources in a secure, highly scalable and extensible platform is of high interest to the open source mHealth community. The EU IMI RADAR-CNS program is an exemplar project with the requirements to support collection of high resolution data at scale; as such, the RADAR-base platform is designed to meet these needs and additionally facilitate a new generation of mHealth projects in this nascent field. OBJECTIVE Wide-bandwidth networks, smartphone penetrance and wearable sensors offer new possibilities for collecting (near) real-time high resolution datasets from large numbers of participants. We aimed to build a platform that would cater for large scale data collection for remote monitoring initiatives. Key criteria are around scalability, extensibility, security and privacy. METHODS RADAR-base is developed as a modular application, the backend is built on a backbone of the highly successful Confluent/Apache Kafka framework for streaming data. To facilitate scaling and ease of deployment, we use Docker containers to package the components of the platform. RADAR-base provides two main mobile apps for data collection, a Passive App and an Active App. Other 3rd Party Apps and sensors are easily integrated into the platform. Management user interfaces to support data collection and enrolment are also provided. RESULTS General principles of the platform components and design of RADAR-base are presented here, with examples of the types of data currently being collected from devices used in RADAR-CNS projects: Multiple Sclerosis, Epilepsy and Depression cohorts. CONCLUSIONS RADAR-base is a fully functional, remote data collection platform built around Confluent/Apache Kafka and provides off-the-shelf components for projects interested in collecting mHealth datasets at scale.

Ultrasound speckle tracking to detect vascular distensibility changes from angioplasty and branch ligation in a radio-cephalic fistula: Use of novel open source software

2020 ◽  
pp. 112972982095991
Author(s):  
William F Weitzel ◽  
Nirmala Rajaram ◽  
Yihao Zheng ◽  
Brian J Thelen ◽  
Venkataramu N Krishnamurthy ◽  
...  
Keyword(s):  
High Resolution ◽  
Open Source ◽  
Open Source Software ◽  
Vessel Wall ◽  
Speckle Tracking ◽  
Wall Motion ◽  
Wide Range ◽  
Before And After ◽  
Conventional Ultrasound ◽  
Duplex Doppler

We used novel open source software, based on an ultrasound speckle tracking algorithm, to examine the distensibility of the vessel wall of the inflow artery, anastomosis, and outflow vein before and after two procedures. An 83-year-old white man with a poorly maturing radio-cephalic fistula received an angioplasty at the anastomosis followed by branch ligation 28 days later. Duplex Doppler measurements corroborated the blood flow related changes anticipated from the interventions. The experimental distensibility results showed that it is technically feasible to measure subtle vessel wall motion changes with high resolution (sub-millimeter) using standard Digital Imaging and Communications in Medicine (DICOM) ultrasound data, which are readily available on conventional ultrasound scanners. While this methodology was originally developed using high resolution radiofrequency from ultrasound data, the goal of this study was to use DICOM data, which makes this technology accessible to a wide range of users.

scholarly journals Development of surface ruptures by hanging-wall extension over a thrust ramp along the Ragged Mountain fault, Katalla, Alaska, USA: Applications of high-resolution three-dimensional terrain models

Geosphere ◽  
2021 ◽  
Author(s):  
Sarah N. Heinlein ◽  
Terry L. Pavlis ◽  
Ronald L. Bruhn
Keyword(s):  
High Resolution ◽  
Hanging Wall ◽  
Three Dimensional ◽  
Active Tectonics ◽  
Normal Fault ◽  
Fault Slip ◽  
The South ◽  
The North ◽  
Terrain Models ◽  
Surface Ruptures

High-resolution three-dimensional terrain models are used to evaluate the Ragged Mountain fault kinematics (Katalla, Alaska, USA). Previous studies have produced contradictory interpretations of the fault’s kinematics because surface ruptures along the fault are primarily steeply dipping, uphill-facing normal fault scarps. In this paper, we evaluate the hypothesis that these uphill-facing scarps represent extension above a buried thrust ramp. Detailed geomorphic mapping along the fault, using 20-cm-resolution aerial imagery draped onto a 1-m-resolution lidar (light detection and ranging) elevation model, was used to produce multiple topographic profiles. These profiles illustrate scarp geometries and prominent convex-upward topographic surfaces, indicating significant disturbance by active tectonics. A theoretical model is developed for fault-parallel flow over a thrust ramp that shows the geometric relationships between thrust displacement, upper-plate extension, and ramp dip. An important prediction of the model for this study is that the magnitude of upper-plate extension is comparable to, or greater than, the thrust displacement for ramps with dips greater than ~45°. This model is used to analyze profile shapes and surface displacements in Move software (Midland Valley Ltd.). Analyses of scarp heights allow estimates of hanging-wall extension, which we then use to estimate slip on the underlying thrust via the model. Assuming a low-angle (30°) uniformly dipping thrust and simple longitudinal extension via normal faulting, variations in extension along the fault would require a slip gradient from ~8 m in the north to ~22 m in the south. However, the same north-south variation in extension with a constant slip of 8–10 m may infer an increase in fault dip from ~30° in the north to ~60° in the south. This model prediction has broader implications for active-fault studies. Because the model quantifies relationships between hanging-wall extension, fault slip, and fault dip, it is possible to invert for fault slip in blind thrust ramps where hanging-wall extension is the primary surface manifestation. This study, together with results from the St. Elias Erosion and Tectonics Project (STEEP), clarifies the role of the Ragged Mountain fault as a contractional structure within a broadly sinistral shear system in the western syntaxis of the St. Elias orogeny.

Development of a conical anode Fe-gun for low voltage SEM

1988 ◽  
Vol 46 ◽  
pp. 978-979
Author(s):  
T. Miyokawa ◽  
S. Norioka ◽  
S. Goto
Keyword(s):  
High Resolution ◽  
Field Emission ◽  
Low Voltage ◽  
Irradiation Damage ◽  
Cold Cathode ◽  
Virtual Source ◽  
Source Position ◽  
Electrostatic Lens ◽  
Electrostatic Lenses ◽  
Wide Range

Field emission SEMs (FE-SEMs) are becoming popular due to their high resolution needs. In the field of semiconductor product, it is demanded to use the low accelerating voltage FE-SEM to avoid the electron irradiation damage and the electron charging up on samples. However the accelerating voltage of usual SEM with FE-gun is limited until 1 kV, which is not enough small for the present demands, because the virtual source goes far from the tip in lower accelerating voltages. This virtual source position depends on the shape of the electrostatic lens. So, we investigated several types of electrostatic lenses to be applicable to the lower accelerating voltage. In the result, it is found a field emission gun with a conical anode is effectively applied for a wide range of low accelerating voltages.A field emission gun usually consists of a field emission tip (cold cathode) and the Butler type electrostatic lens.

Three-fold astigmatism: An important TEM aberration

1993 ◽  
Vol 51 ◽  
pp. 972-973 ◽  
Author(s):  
O.L. Krivanek ◽  
M.L. Leber
Keyword(s):  
High Resolution ◽  
Spatial Frequency ◽  
Field Emission ◽  
Azimuthal Angle ◽  
Hollow Cone ◽  
Small Probe ◽  
Wide Range ◽  
High Resolution Images ◽  
Image Position

Three-fold astigmatism resembles regular astigmatism, but it has 3-fold rather than 2-fold symmetry. Its contribution to the aberration function χ(q) can be written as:where A3 is the coefficient of 3-fold astigmatism, λ is the electron wavelength, q is the spatial frequency, ϕ the azimuthal angle (ϕ = tan-1 (qy/qx)), and ϕ3 the direction of the astigmatism.Three-fold astigmatism is responsible for the “star of Mercedes” aberration figure that one obtains from intermediate lenses once their two-fold astigmatism has been corrected. Its effects have been observed when the beam is tilted in a hollow cone over a wide range of angles, and there is evidence for it in high resolution images of a small probe obtained in a field emission gun TEM/STEM instrument. It was also expected to be a major aberration in sextupole-based Cs correctors, and ways were being developed for dealing with it on Cs-corrected STEMs.

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