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781 results for “earthquakes”
Southern Alps, New Zealand microseismicity earthquake catalog
<p>Earthquake catalog of the microseismicity in the central Alpine Fault, New Zealand (2008 - 2017) in QuakeML format. The information included for each event contains location, phase pick, local magnitude information. For more details refer to the Gcubed publication in the related <a href="http://doi.org/10.1029/2018GC007743">link</a>.</p> <p> </p>
Earthquake catalog in QuakeML format from: "Spatio-Temporal Evolution of Intermediate-Depth Seismicity Beneath the Himalayas: Implications for Metamorphism and Tectonics"
<p>Earthquake catalog of the intermediate-depth seismicity beneath the central Himalayas in QuakeML format. The information included for each event contains location, phase pick, local magnitude information. For more details refer to the Frontiers publication:<a href="https://doi.org/10.3389/feart.2021.742700"> Michailos et al., 2021</a></p>
RSQSim Simulated Earthquake Catalog 5091, New Zealand, NSHM2012 Fault System, 276kyr
<p>Earthquake simulator for New Zealand</p> <p>Simulated earthquake catalog, generated with the Rate-State Earthquake Simulator (RSQSim), described in and used by the following publication:</p> <p>Bruce E. Shaw, Bill Fry, Andrew Nicol, Andrew Howell, and Matthew Gerstenberger, An Earthquake Simulator for New Zealand, <em>submitted</em>, 2021.</p> <p>A github repository with python tools to interact with this catalog, and other similar rsqsim catalogs, is located at:</p> <p><a href="https://github.com/uc-eqgeo/rsqsim-python-tools">https://github.com/uc-eqgeo/rsqsim-python-tools</a></p> <p>This repository is intended to continue to be improved and updated .</p> <p> </p> <p>Additional references discussing the simulator and its uses:</p> <p>Kevin R. Milner, Bruce E. Shaw, Christine A. Goulet, Keith B. Richards‐Dinger, Scott Callaghan, Thomas H. Jordan, James H. Dieterich, Edward H. Field; Toward Physics‐Based Nonergodic PSHA: A Prototype Fully Deterministic Seismic Hazard Model for Southern California. <em><em>Bulletin of the Seismological Society of America</em></em> 2021;; 111 (2): 898–915. doi: <a href="https://doi.org/10.1785/0120200216">https://doi.org/10.1785/0120200216</a></p> <p>Bruce E. Shaw, Kevin R. Milner, Edward H. Field; Keith B. Richards‐Dinger, Jacquelyn J. Gilchrist, James H. Dieterich, and Thomas H. Jordan, 'A physics-based earthquake simulator replicates seismic hazard statistics across California',<em> Science Advances, 4</em>, 2018. <a href="https://www.ldeo.columbia.edu/%7Eshaw/publications/ShawEtal18.pdf">doi:10.1126/sciadv.aau0688</a></p> <p>The catalog is simulated on a fault system for New Zealand built from source in the NSHM2021 national hazard model, following the hybrid loading technique described in Shaw (2019) (<a href="https://doi.org/10.1785/0120180128">https://doi.org/10.1785/0120180128</a>).</p> <p> </p> <p><strong>File Descriptions:</strong></p> <p>The descriptions below are for some of the more relevant files. There are additional files as well. The python tools in the github repository interact with additional files not mentioned here. </p> <p><strong>Catalog CSV File:</strong> <em>catalog.csv</em></p> <p>This is a human-readable summary file listing each event (after<br> skipping the first 50kyrs of model spin-up time).<br> Each line corresponds to an event in the catalog, and contains the<br> following information:</p> <p> * Event ID and occurrence time<br> * Magnitude, Moment, and Area<br> * Participating element information (count, average slip, long-term<br> average slip rate)<br> * Hypocenter and scalar-moment centroid locations<br> * Rupture surface minimum and maximum depths</p> <p><strong>Geometry File (ASCII): </strong><em>zfault_Deepen.in</em></p> <p>ASCII file listing patch (triangular) geometry for the simulated faults<br> in a UTM coordinate system (zone 11S). The primary columns are:</p> <p> * /x1, y1, z1/ - UTM coordinates of the first vertex<br> * /x2, y2, z2/ - UTM coordinates of the second vertex<br> * /x3, y3, z3/ - UTM coordinates of the third vertex<br> * /rake/ - Direction of the motion of the hanging wall relative to the<br> footwall (in degrees, following the convention of Aki & Richards, 2002)<br> * /slip_rate/ - Long-term average slip rate (in m/s)</p> <p>The first line in the file (excluding comment lines that start with '#')<br> is the patch with ID=1, the second ID=2, etc. Additional metadata<br> columns may exist in each line beyond those listed and can be ignored.</p> <p><strong>Catalog List Files (binary):</strong> <em>catalog.eList, catalog.pList,<br> catalog.tList, catalog.dList</em></p> <p>The raw output of RSQSim includes 4 binary "list" files that define the<br> simulated event IDs, times, and total slip in each participating patch.<br> All 4 list files should be processed together, as the /N/-th item in one<br> list file corresponds to the /N/-th item in each other file.</p> <p>For each patch the ruptures during an event, a value is written to each<br> of these files giving 1) the patch number, 2) the event number, 3) the<br> distance slipped during the event, and 4) the time of first rupture for<br> that patch during that event.</p> <p>The format is as follows:</p> <p> * catalog.eList: list of event IDs (1-based), stored as little-endian<br> 4-byte integers<br> * catalog.pList: list of patch IDs (1-based), stored as little-endian<br> 4-byte integers<br> * catalog.tList: list of time of first slip on each patch in each<br> event (in seconds, relative to simulation origin time), stored as<br> little-endian 8-byte double precision floating-point numbers<br> * catalog.dList: list of total slip on each patch in each event (in<br> meters), stored as little-endian 8-byte double precision<br> floating-point numbers</p> <p><strong>RSQSim Input File (ASCII):</strong> <em>multiparam.in</em></p> <p>Key-value pairs of RSQSim model parameters, used to originally run the<br> simulation.</p> <p> </p> <p> </p> <p> </p> <p> </p>
2008 Nura earthquake surface rupture slip vector documentation
<p>This online data holds information related to the surface rupture resulting from the 2008 Nura earthquake in south Kyrgyzstan. The primary dataset is a Google Earth KMZ file with GPS-locations where slip vector measurements were taken along the rupture. A downloadable ZIP file accompanies the KMZ, containing photographs linked to each data point. Both files should be stored in one folder for proper linkage. In addition, a text file is available with all measurements and associated information. Five videos obtained with the drone are available to illustrate the surface rupture zones and geological overview in the Nura settlement surroundings. The entire data was gathered in 2018. </p> <p>Raster-files of high-resolution digital surface models of the surface rupture can be found on opentopography <a href="https://doi.org/10.5069/G9ZW1J4C" target="_blank" rel="noreferrer noopener">https://doi.org/10.5069/G9ZW1J4C</a></p> <p>The data presented in this repository was initially disseminated in a dissertation by Magda Patyniak. This project is part of the CaTeNA-project within the Client II program of and funded by the Federal Ministry of Education and Research (BMBF; Sub-project grant 03G0878E to Manfred Strecker).</p>
X-ray computed microtomographic (XRCT) images of a fault core that slipped during the 1726 San Andreas faultzone earthquake
<p>Uploaded are x-ray computed microtomographic (XRCT) images used to examine solid-fluid interactions within one of the near-surface fault cores that slipped during a circa (ca.) 1726 San Andreas Fault zone earthquake. The study site is 16 km northwest of Bombay Beach, California (33.45873, -115.8560), and our sample, collected at a depth of 1.2 m below sea level, is from a trench that exposes deposits of ancient Lake Cahuilla. The ca. 1726 earthquake occurred during a highstand of ancient Lake Cahuilla; our study site was ~55 m below the lake's surface at the time. Crustal deformation caused by the ca. 1726 earthquake has been documented for at least 85 km along the southernmost San Andreas fault zone, which has been used, alongside other observations, to constrain the earthquake's size to a magnitude 7.2 or larger with offsets on the order of ~3 m. Since the ca. 1726 earthquake, creep and triggered slip have occurred along the section of the fault we study, with estimates of ~3 mm/yr of motion over the last ~160 years.</p> <p>We acquire XRCT images at the Advanced Light Source, Lawrence Berkeley National Lab, on beamline 8.3.2. Imaging uses a 50 mm LuAG scintillator, PCO Edge camera, and 1X Nikon lens. We image with white light x-rays, 13 ms exposure times, and 2625 projections through 180-degree continuous sample rotations. This produces 1280 two-dimensional image slices with voxels' linear dimensions of 3.24 microns. We reconstruct images and perform ring removal, center of rotation optimizations, and outlier removal using TomoPy. We name the sample FT_50_4_ZZZZ, where ZZZZ represents the image slice number; increasing numbers represent increasing distance into the outcrop.</p>
Data from: RockNet: Rockfall and earthquake detection and association via multitask learning and transfer learning
<p>Seismological data can provide timely information for slope failure hazard assessments, among which rockfall waveform identification is challenging for its high waveform variations across different events and stations. A rockfall waveform does not have typical body waves as earthquakes do, so researchers have made enormous efforts to explore characteristic function parameters for automatic rockfall waveform detection. With recent advances in deep learning, algorithms can learn to automatically map the input data to target functions. We develop RockNet via multitask and transfer learning; the network consists of a single-station detection model and an association model. The former discriminates rockfall and earthquake waveforms. The latter determines the local occurrences of rockfall and earthquake events by assembling the single-station detection model representations with multiple station recordings. RockNet achieves macro F1 scores of 0.990 and 0.981 in terms of discriminating earthquakes and rockfalls from other events with the single-station detection and association models, respectively.</p>
Relocated earthquake catalog using DiTing
<p>Relocated earthquake catalog from 2021/08/01 to 2022/09/20 using the DiTingPicker method</p>
Pre-seismic Sentinel-1 PSI surface motion measurements for the area affected by the February 2023 Türkiye–Syria earthquakes
<p>We have processed Copernicus Sentinel-1A data from 01/2019 to 01/2023 (descending track 21) over the broader area (approx. 48400 sq. km) affected by February 6, 2023, M7.8 and M7.5 earthquakes in Türkiye and Syria, utilizing the SNAPPING Persistent Scatterers Interferometry (PSI) medium resolution service of the Geohazards Exploitation Platform (GEP; <a href="https://geohazards-tep.eu">https://geohazards-tep.eu</a>).</p> <p>Measurements contain average Line-of-Sight (LoS) velocities, corresponding uncertainties, and the complete displacement time series. Please note that the original dataset of about 2M point measurements was split into parts, each containing 200k points, to facilitate easier manipulation and visualization.</p> <p>References</p> <p>[1] Foumelis, M.; Delgado Blasco, J.M.; Brito, F.; Pacini, F.; Papageorgiou, E.; Pishehvar, P.; Bally, P. SNAPPING Services on the Geohazards Exploitation Platform for Copernicus Sentinel-1 Surface Motion Mapping. Remote Sens. 2022, 14, 6075. <a href="https://doi.org/10.3390/rs14236075">https://doi.org/10.3390/rs14236075</a></p> <p>[2] SNAPPING – Surface motioN mAPPING Sentinel-1 on-demand processing service, Online tutorial, <a href="https://docs.terradue.com/geohazards-tep/tutorials/Snapping.html">https://docs.terradue.com/geohazards-tep/tutorials/Snapping.html</a>.</p>
Data from "Behavior of reef fishes during a submarine magnitude 5 earthquake"
<p><strong>Behavior of reef fishes during a submarine magnitude 5 earthquake</strong></p> <p>Appendix S1 gathers video excerpts of 2 minutes recorded by 12 remote underwater cameras on the seafloor of N’Gouja reef (Mayotte) before, during and after the magnitude 5.3 earthquake on 10 November 2020 (12:19:39 local time).</p> <p>Table S1 & Tables S2 gathers data of fish behavior collected from the 12 remote underwater videos (rows) during 10 seconds slots before [be.], during [Earthq.] and after [af.] the earthquake (columns). Table S1 contains the proportion of fish individuals seen fleeing. Table S2 contains the feeding activity of <em>Ctenochaetus striatus</em> (number of bites per individual during 10 s).</p>
Earthquake catalogs for: A specific earthquake processing workflow for studying long-lived explosive volcanic eruptions with application to the 2008 Okmok eruption
<p>Repository for the seismic catalogs from Garza-Giron et al. (2023a,b). These include the catalog with absolute locations using NonLinLoc (Lomax et al., 2001; Lomax and Curtis, 2001), and the relocated catalogs using hypoDD (Waldhauser and Ellsworth, 2000) and GrowClust (Trugman and Shearer, 2017).</p> <p>The header of the CSV files is as follows:</p> <p><strong>Date</strong> (year/month/day), <strong>Time</strong> (hr:min:sec:msec), <strong>Latitude</strong> (decimal degrees), <strong>Longitude</strong> (decimal degrees), <strong>Depth</strong> (km), <strong>Magnitude</strong> (Ml calculated for this study), <strong>Event_type</strong> (VT:vulcano-tectonic;LP:long-period), <strong>Number of stations</strong> where the event was detected, <strong>ID</strong></p> <p>References:</p> <div>Garza‐Giron, R., Brodsky, E. E., Spica, Z. J., Haney, M. M., & Webley, P. W. (2023a). A specific earthquake processing workflow for studying long‐lived, explosive volcanic eruptions with application to the 2008 Okmok Volcano, Alaska, eruption. <em>Journal of Geophysical Research: Solid Earth</em>, e2022JB025882.</div> <div> </div> <div> <div>Garza‐Girón, R., Brodsky, E. E., Spica, Z. J., Haney, M. M., & Webley, P. W. (2023b). Earthquakes record cycles of opening and closing in the enhanced seismic catalog of the 2008 Okmok Volcano, Alaska, eruption. <em>Journal of Geophysical Research: Solid Earth</em>, <em>128</em>(7), e2023JB026893.</div> <div> </div> </div> <p>Lomax A, Curtis A (2001) Fast, probabilistic earthquake location in 3-D models using oct-tree importance sampling. Geophys Res Abstracts, 3:955.</p> <p>Lomax, A., Zollo, A., Capuano, P., and Virieux, J. (2001). Precise, absolute earthquake location under Somma‐Vesuvius volcano using a new 3D velocity model.Geophysical Journal International,146, 313–331.</p> <p>Trugman, D. T., and Shearer, P. M. (2017). GrowClust: A hierarchical clustering algorithm for relative earthquake relocation, with application to the Spanish Springs and Sheldon, Nevada, earthquake sequences. Seismological Research Letters, 88(2A), 379-391.</p> <p>Waldhauser, F., and Ellsworth, W. L. (2000). A double-difference earthquake location algorithm: Method and application to the northern Hayward fault, California. Bulletin of the Seismological Society of America, 90(6), 1353-1368.</p>
Optical Image Correlation Data for 2023 Kahramanmaras Earthquakes
<p>Horizontal surface deformation maps generated from pixel tracking of Sentinel-2 optical satellite images using COSI-Corr.</p>
Data for supra-slab earthquakes
<p>Waveform data and hypocenter data of the supra-slab earthquake used in the analysis are included. 'wv.dat' contains vertical, north-south, east-west components and 'tr.dat' contains transverse components. 'hypo_above_wv.dat' contains the source of the earthquake used for waveform analysis and 'hypo_above_03_21.dat' contains the hypocentral data from the catalogue of the Japan Meteorological Agency used for seismic activity analysis.</p> <p> </p> <p>Waveform data was recorded at MeSO-net stations maintained by the National Research Institute for Earth Science and Disaster Prevention (Sakai and Hirata, 2009; Aoi et al., 2021; National Research Institute for Earth Science and Disaster Resilience, 2021).</p>
Sentinel-1 InSAR unwrapped data of the 27 July 2022 Abra earthquake in Luzon, the Philippines
<p>This is a supporting dataset for Tang et al. (2023), "Oblique blind faulting underneath the Luzon volcanic arc during the 2022 M<sub>w</sub> 7.0 Abra earthquake, the Philippines". The original and downsampled line-of-sight displacements for modeling are presented in this repository. The coseismic interferogram using the synthetic aperture radar images from Copernicus Sentinel-1A descending track 32 on 21 July and 2 August, 2022 (6 days before and after the mainshock). The flight direction is ~N190° with a westward look angle ranging from 36° to 45°. Details of processing and downsampling schemes can be found in the paper. The Sentinel-1 images were processed by European Space Agency (ESA) and downloaded from Alaska Satellite Facility (ASF) Data Search Vertex (<a href="https://search.asf.alaska.edu/">https://search.asf.alaska.edu/</a>).</p>
Data for megathrust earthquakes (1)
<p>Waveform data and hypocenter data of the megathrust earthquakes used in the analysis are included. 'wv.dat' contains vertical, north-south, east-west components and 'tr.dat' contains transverse components. 'hypo_thrust_wv.dat' contains the hypocentral data used for waveform analysis from the catalogue of the Japan Meteorological Agency.</p> <p> </p> <p>Waveform data was recorded at MeSO-net stations maintained by the National Research Institute for Earth Science and Disaster Prevention (Sakai and Hirata, 2009; Aoi et al., 2021; National Research Institute for Earth Science and Disaster Resilience, 2021).</p>
A multi-station volcano-tectonic earthquakes monitoring based on Transfer Learning techniques.
<p>A multi-station volcano-tectonic earthquakes monitoring based on Transfer Learning techniques.</p> <p>Manuel Titos (1), Ligdamis Gutiérrez (2,3), Carmen Benítez (1), Pablo Rey Devesa (2,3), Ivan Koulakov (4) and Jesús. M. Ibáñez (2,3)</p> <p><br> <strong>Institutions associated:</strong></p> <p>(1) CITIC, Department of Signal Processing, Telematic and Communications, University of Granada, 18071. Granada. Spain.<br> (2) Department of Theoretical Physics and Cosmos. Science Faculty. Avd. Fuentenueva s/n. University of Granada. 18071. Granada. Spain.<br> (3) Andalusian Institute of Geophysiscs. Campus de Cartuja. University of Granada. C/Profesor Clavera 12. 18071. Granada. Spain.<br> (4) Laboratory for Seismic Forward and Inverse Problems, Institute of Petroleum Geology and Geophysics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia</p> <p><br> <strong>Acknowledgment:</strong></p> <p>This is a short text to acknowledge the contributions of specific colleagues, institutions, or agencies that aided the efforts of the authors.</p> <p>a) This work is part of the research by the Spanish FEMALE project (PID2019-106260GB-I00). <strong>FEMALE </strong>(<em>Forecasting Volcanic Eruptions Using Signal Processing and Machine Learning Techniques on Seismic Signals</em>) https://femalevolcanoes.es/</p> <p><br> b) JMI and LG were partially funded by the Spanish project PROOF-FOREVER (EUR2022.134044).</p> <p><br> <strong>Keywords:</strong></p> <p>Automatic volcanic monitoring, real-time monitoring, Artificial Intelligence, Transfer Learning, Recurrent Neural Networks, Temporal Convolutional Networks.</p> <p> </p> <p><strong>Data availability statement:</strong></p> <p>Seismic data from Bezymianny volcano (2017), Kamchatka, Russia.</p> <p> </p> <p><strong>Contents:</strong></p> <p>Seismic Data from Bezymianny volcano recorded at stations BZ01, BZ02, BZ06 and BZ10.<br> The data represent the vertical component of the seismic signal, associated to the period analyzed in the study:</p>
Spreadsheet containing information on earthquakes that DID / DID NOT rupture the surface
<p>Spreadsheet containing information on earthquakes that DID / DID NOT rupture the surface</p> <p>Data are extracted from the ISC-GEM catalogue. Fields include:</p> <p>N.: identificative number, progressive</p> <p>Event ID: identificative number, from the ISC-GEM catalogue</p> <p>Date: format YYYY-MM-DD, from the ISC-GEM catalogue</p> <p>Lat: latitude of the epicenter, in decimal degrees</p> <p>Lon: longitude of the epicenter, in decimal degrees</p> <p>Depth, Depth unc and Depth quality: information retrieved from the ISC-GEM catalogue</p> <p>Mw, Mw unc and Mw quality: moment magnitude; information retrieved from the ISC-GEM catalogue</p> <p>Str, Dip, Rake: strike, dip and rake for the 2 nodal planes; information retrieved from the ISC-GEM catalogue</p> <p>Fault kin: earthquake mechanism, categorized as reverse, strike-slip, normal, transpressive, transtensive</p> <p>Surface faulting: categorized as YES, NO, no info, debated faulting</p> <p>SRL (surface rupture length in km); MD (max displacement in m); AD (average displacement in m)</p> <p>Reference: literature used to compile the dataset; full list is available in the .pdf file related to this document</p> <p> </p> <p>A poster has been presented at the PATA Days 2023 in France, file available at:</p> <p><a href="https://www.researchgate.net/publication/363739186_LIKELIHOOD_OF_PRIMARY_SURFACE_FAULTING_A_SEQUEL">https://www.researchgate.net/publication/363739186_LIKELIHOOD_OF_PRIMARY_SURFACE_FAULTING_A_SEQUEL</a></p>
Tsunami Initial Profile and Maximum Runup through Earthquake Source Parameters
<p>The fitting database for 7840 earthquake (tsunami) source scenarios and corresponding N-wave parameters.</p>
Cascadia Subduction Zone Fault Heterogeneities from Newly Detected Small Earthquakes - Datasets
<p>Datasets associated with manuscript "Cascadia Subduction Zone Fault Heterogeneities from Newly Detected Small Earthquakes" by Morton et al. (2023), submitted to the <em>Journal of Geophysical Research: Solid Earth</em>. Three datasets are present in this upload:</p> <p><strong>ds01.xlsx</strong>: Catalog of 5,282 detected earthquakes along the Cascadia subduction margin, ordered by time. Events were located using Hypoinverse (Klein, 2002). Columns of the catalog are: Cascadia Initiative deployment year, Origin Time String (YYYYMMDDhhmmss), Origin Time (Year, Month, Day, Hour, Minute, Second), Latitude, Longitude, Event Depth (km), Duration Magnitude (Md), Number of P and S arrival picks with weights > 0.1, Maximum Azimuthal Gap (deg.), Distance to the Nearest Station (km), Travel Time Residual RMS (s), Horizontal Location Error (ERH; km), Vertical Location Error (ERZ; km), Focal Mechanism if applicable (Strike, Dip, Rake; deg.), Plate Designation (Slab, Interface, or Upper Plate), and Previous Existence in Regional Catalogs. Duration magnitudes that could not be constrained are listed as -9. Detected earthquakes that had previously been reported in other catalogs are listed as "Catalog" or "Stone" form the regional or Stone et al. (2018) catalogs, respectively; Those used as template events are marked as "T" or "ST", for those from regional catalogs or the Stone et al. (2018) catalog, respectively, in the last column.</p> <p><strong>ds02.xlsx</strong>: Table of earthquakes chosen as template events for subspace scanning from regional (NEIC, ANF, PNSN, CNDC) and Stone et al. (2018) catalogs. Columns of the template event table are: Catalog Source (T for regional, ST for Stone et al. 2018), Cascadia Initiative (CI) Deployment Year, Template Cluster ID, Date, Time (UTC), Catalog Location (Latitude, Longitude, Depth), Catalog Magnitude, and Whether the Template Event was Detected. Some of the templates were detected but were not included in the final catalog because the travel time residual RMS was greater than 1s and are noted in the table as "poorly located".</p> <p><strong>ds03.xlsx</strong>: Table of seismic stations used in subspace detection scanning, identified by the CI deployment year, Template Cluster ID, Station SEED, and Network Codes. Stations are listed with the corresponding high-pass (HP) or band-pass (BP) filter applied before scanning to maximize the signal-to-noise ratio.</p> <p>References</p> <p>Klein, F. W. (2002). <em>User’s Guide to HYPOINVERSE-2000, a Fortran Program to Solve for Earthquake Locations and Magnitudes</em> (Open File Report 02-171). U.S Geological Survey. https://doi.org/10.3133/ofr02171</p> <p>Stone, I., Vidale, J. E., Han, S., & Roland, E. (2018). Catalog of off-shore seismicity in Cascadia: Insights into the regional distribution of microseismicity and its relation to subduction processes. <em>Journal of Geophysical Research: Solid Earth, 123</em>, 1–12. https://doi.org/10.1002/2017JB014966</p>
Initial Observations for the Destructive Earthquake Doublet of 6 February 2023 in South-Central Türkiye and Northwestern Syria
<p>This dataset is provided as supplementary material to the published paper "The Destructive Earthquake Doublet of 6 February 2023 in South-Central Türkiye and Northwestern Syria : Initial Observations and Analyses" (<em>The Seismic Record</em>, <a href="https://urldefense.com/v3/__https://doi.org/10.1785/0320230007__;!!Nmw4Hv0!3WB4F-6tmOGbOLPRhUkYZ-WFKNU4M33J2_WUvxmcPRrhpgtBblHGGJ3fuNm4hfSUm8zjvwBesiBCkWRMBKGM93LqEmPAUVL8FqE$">https://doi.org/10.1785/0320230007</a>).</p> <p>Included here are: the coordinates of the surface rupture used for modeling, and the preliminary three-dimensional coseismic surface displacements field (east-west, north-south, and vertical) derived via pixel-offset tracking of Sentinel-1 SAR images.</p> <p>The ascii-file “fault_trace_for_modeling.txt” includes longitude and latitude coordinates of the rupture trace.<br> The matlab-file ENU_Turkiye_S1.mat includes<br> enu: the east, north, and vertical displacement components<br> coor: the coordinate information for the enu matrix<br> fault: the coordinate of surface ruptures mapped from the SAR-pixel offset tracking result<br> mask: indicates the area for which the 3D displacements are plausible near the Golbasi basin due to the possible existence of water</p> <p>Original Sentinel-1 SAR images are available via the Copernicus hub at <a href="https://urldefense.com/v3/__https://scihub.copernicus.eu__;!!Nmw4Hv0!3WB4F-6tmOGbOLPRhUkYZ-WFKNU4M33J2_WUvxmcPRrhpgtBblHGGJ3fuNm4hfSUm8zjvwBesiBCkWRMBKGM93LqEmPA9j-Kbj8$">https://scihub.copernicus.eu</a>. The coseismic 3D surface displacements are preliminary results, and further improvements by incorporating ALOS-2 data and inspecting local regions are ongoing. The surface rupture traces used for modeling are mapped based on the SAR-pixel offset tracking result as well as the geomorphology alongside.</p> <p>Date submitted: June 3, 2023</p>
Trinidad Zone 2008-2022 Template-Detected Earthquake Catalog & 2011-2012 Aftershock Array Catalog
<p>This dataset contains two earthquake catalogs for the Trinidad zone in the Raton Basin on the Colorado-New Mexico, USA border. The excel spreadsheet has three tabs and each has a descriptor. The "aftershock_catalog" tab is an earthquake catalog following the 2011 Mw 5.3 mainshock earthquake in the Trinidad zone. It spans from August 2011 to May 2012. The "template" tab contains the earthquakes used as templates for the template-detection earthquake catalog. The "template_detected_catalog" is an earthquake catalog spanning May 30, 2008 to April 1, 2022 built using Transportable Array seismometer T25A.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.