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662 results for “seismicity”
Seismic and meteorological records from Trakarding-Trambau Glacier system, Nepal Himalaya (October 21 - November 9, 2017)
<p>The following geophysical field data (collected between October 21 and November 9, 2017) at Trakarding-Trambau Glacier system in Nepal Himalaya is provided in this dataset: </p> <p> </p> <p>(1) Hourly air-temperature measured at four sites (AWS, T1, T2 and T3). Units are degrees Celcius. Local time.</p> <p>[file name] Hourly_Air_temperature_AWS_T1_T2_T3_degC.csv</p> <p> </p> <p>(2) Hourly wind speed measured at the AWS site. Units are meters per second. Local time.</p> <p>[file name] Hourly_Wind_speed_AWS_MperS.csv</p> <p> </p> <p>The aforementioned stations had the following dGPS-derived coordinates:</p> <p>{Station, lat [deg], lon [deg], elevation [m] }</p> <p>AWS, 27.84356265, 86.4867231, 4805.582206</p> <p>T1, 27.84575824, 86.49189978, 4591.4429</p> <p>T2, 27.82976456, 86.51989785, 4768.8465</p> <p>T3, 27.855872, 86.531197, 5390.48</p> <p> </p> <p>(3) Raw seismic data (vertical component) recorded at five locations (DAM, C1, C2, C3, and C4) by four data-loggers (AKX, AKS, AKT, AKU) with a sampling frequency of 400 Hz. The file format (*.pri0) corresponds to a standard [.mseed]-format. Units are counts representing velocity. UTC time.</p> <p> </p> <p>The aforementioned stations had the following dGPS-derived coordinates:</p> <p>{StationName-Logger, lat [deg], lon [deg], elevation [m] }</p> <p> </p> <p>DAM-AKX, 27.870954, 86.463243, 4375.030762</p> <p>C1-AKS, 27.84546885, 86.49247316, 4594.0462</p> <p>C2-AKT, 27.82939476, 86.52001441, 4777.5211</p> <p>C3-AKU, 27.83593425, 86.53248327, 5288.3311</p> <p>C4-AKX, 27.87962877, 86.542076, 5555.2085</p>
Data from: Numerical Simulation of the Atmospheric Signature of Artificial and Natural Seismic Events
<p>This data is related to the seismic hammer experiment discussed in "Numerical Simulation of the Atmospheric Signature of Artificial and Natural Seismic Events" by Martire et al. (2018, DOI will be added upon acceptance of the manuscript).</p> <p>The .zip file contains 3 .mseed files, and 1 .txt file. The .mseed are the raw seismometer signals. The .txt details the position of the sensor.</p> <p>Remaining data used in our paper can be found in the repository related to "Detection of Artificially Generated Seismic Signals using Balloon-borne Infrasound Sensor" by Krishnamoorthy et al. (2018, DOI 10.1002/2018GL077481). That repository has DOI 10.6084/m9.figshare.6137507.</p>
Estimations of Sensor Misorientation for Broadband Seismic Stations in and around Africa
<p>To ensure the accuracy of future rotation-based seismological studies using data recorded by broadband seismic stations in Africa and environs, we investigate the sensor orientation of 1075 stations belonging to 41 seismic networks deployed in and around the African continent in the past three decades. We applied three independent waveform-based orientation estimation methods that involve the measurement of P-wave particle motion based on the principal component analysis, minimizing the P-wave energy on the transverse component of motion, and measuring intermediate-period Rayleigh-wave arrival angles from teleseismic earthquakes. This dataset is the compilation of the entire result of this study.</p>
Seismic data (ASCII)
<p>Each file corresponds to a single day of data.</p> <p>Signal amplitude (0± 2048) of the 6 sensors (on each line) at a sampling rate of 250 Hz.</p> <p> </p>
Subpixel optical correlation co-seismic offsets for the Mw 6.4 and Mw 7.1 Ridgecrest, California earthquakes, from Copernicus Sentinel 2 data
<p>Two strong earthquakes (Mw 6.4 and Mw 7.1) took place near Ridgecrest, California, on July 4 2019 and July 6, respectively.</p> <p><a href="https://earthquake.usgs.gov/earthquakes/eventpage/ci38443183/executive">https://earthquake.usgs.gov/earthquakes/eventpage/ci38443183/executive</a></p> <p><a href="https://earthquake.usgs.gov/earthquakes/eventpage/ci38457511/executive">https://earthquake.usgs.gov/earthquakes/eventpage/ci38457511/executive</a></p> <p>In order to assess surface ruptures and the displacement field from the earthquakes, we used subpixel image correlation with Copernicus Sentinel-2 optical imagery (Band 4). MicMac and CosiCorr software was used to to extract the 2D (East-West and North-South) horizontal co-seismic displacement field.</p> <p>Four high-resolution figures are given per method and component (EW and NS). Road network (white lines - from OpenStreetMap) and Quaternary Faults (black polylines) from USGS (<a href="https://earthquake.usgs.gov/hazards/qfaults/">https://earthquake.usgs.gov/hazards/qfaults/</a>) are used for overlay.</p> <p>Rasters are given per software used (MICMAC_ for MicMac and COSI for CosiCorr), with a pixel resolution of 20m. Final product is corrected with detrending (to remove mostly registration errors) and filtered to remove noise. Stripes resulting from pushbroom scanner and orbit errors were not removed at this product (visible as WNW-ESE and NNE-SSW linear parallel stripes).</p> <p>-North-South displacement: positive values to the North.</p> <p>- East-West displacement: positive values to the East.</p> <p>Raster files are projected in UTM Zone 11North WGS84 ( EPSG:32611)</p> <p> </p> <p>A contribution to <strong>CEOS Working Group Disasters:</strong> Seismic Demonstrator</p> <p><strong>Copyright:</strong> Contains modified Copernicus Sentinel data (2019), OpenStreetMap data (2019), Quaternary Fault and Fold Database of the United States - USGS (2019)</p>
Seismic anisotropy dataset from Illsley-Kemp et al., G3, 2019 (10.1029/2019GC008529)
<p>The datasets provided here are the seismic anisotropy results for the four seperate regions of New Zealand, reported and discussed in Illsley-Kemp et al., <em>Geochemistry, Geophysics, Geosystems, </em>2019 (10.1029/2019GC008529). </p> <p>If you use this date, please cite the following paper:</p> <p>Illsley-Kemp, F., Savage, M. K., Wilson, C. J. N., & Bannister, S., 2019, 10.1029/2019GC008529. Mapping Stress and Structure from Subducting Slab to Magmatic Rift: Crustal Seismic Anisotropy of the North Island, New Zealand. <em>Geochemistry, Geophysics, Geosystems.</em></p> <p>The data are csv files in the same format as MFAST output (http://mfast-package.geo.vuw.ac.nz), with each column corresponding to the following:</p> <p>1: Result ID</p> <p>2: Station code</p> <p>3: Station latitude</p> <p>4: Station longitude</p> <p>5: Earthquake ID (after GeoNet)</p> <p>6: Year</p> <p>7: Julian day on which the event occurred, with decimal digits giving the fraction of the day</p> <p>8: Earthquake latitude</p> <p>9: Earthquake longitude</p> <p>10: Earthquake-station distance (km)</p> <p>11: Earthquake depth (km)</p> <p>12: Earthquake magnitude</p> <p>13: Back azimuthal angle</p> <p>14: Initial polarisation of the shear wave in degrees</p> <p>15: Error of Spol in degrees, one standard deviation</p> <p>16: Start time of the selected measurement window in seconds, relative to the start of the seismogram at t = 0</p> <p>17: End time of the selected measurement window in seconds, relative to the start of the seismogram at t = 0</p> <p>18: Not used</p> <p>19: Not used</p> <p>20: Signal to noise ratio</p> <p>21: Delay time (δt) between fast and slow shear wave in seconds</p> <p>22: Error of δt in degrees, one standard deviation</p> <p>23: Angle of the orientation of the fast shear wave (φ), in degrees from North</p> <p>24: Error of φ in degrees, one standard deviation</p> <p>25: Angle of incidence at the station, measured against a horizontal plane in degrees, where 0 means vertical incidence</p> <p>26: Not used</p> <p>27: Type of measurement. This field contains the measurement code that is used, the number of measurement window start times and the number of window end times</p> <p>28: Not used</p> <p>29: Not used</p> <p>30: Nyquist frequency of the event in Hz</p> <p>31: Evaluation of the measurement quality</p> <p>32: Lower corner frequency of the bandpass filter in Hz</p> <p>33: Higher corner frequency of the bandpass filter in Hz</p> <p>34: Angle between the initial polarisation and the fast orientation in degrees</p> <p>35: Not used</p> <p>36: Not used</p> <p>37: The maximum value of the eigenvalue of the corrected covariance matrix</p> <p>38: The number of degrees of freedom in the measurement</p> <p>39: The minimum value of the eigenvalue of the covariance matrix before it was scaled to have the 95% confidence level set to 1</p> <p>40: The S-wave travel time between the earthquake and the station</p> <p>41: The dominant frequency in the S wave, determined from the frequency at the maximum spectral amplitude</p>
Compilation of Moon internal structure models and seismic event locations presented in Garcia et al., Space Science Review, 2019 study
<p>Compilation of of previously published internal structure model of the Moon in "named discontinuities" seismological format + 3 new models associated to the above mentioned study + previously published Moon quake location estimates by various authors.</p> <p>The study, the internal structure models and quake locations compilation were performed by the ISSI international research team on Moon Seismology and internal structure described here: http://www.issibern.ch/teams/internstructmoon/</p>
Semi-Supervised Pre-trained Foundation Model for 3D Structural Feature Analysis of Seismic Images
<p>Codes, trained model, and datasets for the paper "Semi-Supervised Pre-trained Foundation Model for 3D Structural Feature Analysis of Seismic Images".</p>
Kinematic and Paleoseismic Investigation of an Upper-Plate Fault on Chirikof Island: A Potential Tsunami-Seismic Hazard Source within the Alaska Subduction Zone
Open the record for dataset details and reuse information.
Seismic modeling of bedload transport in a gravel-bed alluvial channel
<p>This repository publishes data for 4 flow events at the Arroyo de Los Pinos on the paper "Seismic modeling of bedload transport in a sandy gravel-bed alluvial channel".</p>
Earthquake Catalogs of the LArge-n Seismic Survey in Oklahoma dataset
<p>This dataset release contains earthquake catalogs created using different association methods for the LArge-n Seismic Survey in Oklahoma dataset. These datasets can be used by researchers to further analyze the earthquakes in the array to better understand their behavior. The association methods applied here are as follows the Guassian Mixture Model Association (GaMMA) (Zhu et al., 2022), PhaseLink (Ross et al., 2019), the Graph Earthquake Neural Interpretation Engine (GENIE) (McBrearty and Beroza, 2023) and Rapid Earthquake Association and Location (REAL) code (Zhang et al., 2019). For detailed information please see the paper that accompanies this dataset (Pennington et al. 2024). Important notes though, the GaMMA dataset has a large number of false events so it should be used with caution. The PhaseLink dataset does not associate S-phase arrivals so the catalog will only include P-wave arrivals. We also include in this dataset the original detected phase arrivals that each of these catalogs were created from to allow any user to test and apply new methods to and later compare to our results.</p>
On the emergence of fault afterslip during laboratory seismic cycles
<div>This is the ReadMe file corresponding to the dataset of the study entitled:</div> <div>"On the emergence of fault afterslip during laboratory seismic cycles"</div> <div>By Noël C., Twardzik C., Dublanchet P., and Passelègue F.</div> <div> </div> <div>This Read-Me file has been last edited in October 2024</div> <div> </div> <div>This readme file describes the data repository and supplementary files accompanying the above publication. </div> <div>For any further queries please contact corentin.noel@geoazur.unice.fr</div> <div> </div> <div> </div> <div> </div> <div>Each experiment has a .txt file. The nam of the file is composed of first the sample configuration, then the confining pressure. If "down" is following, it stands for the confining pressure downphase at the end of the experiment (see method section of the manuscript). For Granite_Marble experiments, "bis" at the end of the name stands for the duplicated experiment. </div> <div> </div> <div>The data are tab separate file, each column is a variable as follow:</div> <div>Column 1: Time(s)</div> <div>Column 2: Axial average displacement (mm)</div> <div>Column 3: Axial stress (MPa)</div> <div>Column 4: Confining pressure (MPa)</div> <div>Column 5: Strain gage 1 (µstrain)</div> <div>Column 6: Strain gage 2 (µstrain)</div> <div>Column 7: Strain gage 3 (µstrain)</div> <div>Column 8: Strain gage 4 (µstrain)</div> <div>Column 9: Strain gage 5 (µstrain)</div> <div>Column 10: Strain gage 6 (µstrain)</div> <div>Column 11: Strain gage 7 (µstrain)</div> <div>Column 12: Strain gage 8 (µstrain)</div>
Seismic Model of the Seafloor Sediment and Shallow Oceanic Crust of the Alaska-Aleutian Subduction Zone at the Alaska Peninsula
<p>This dataset is supplementary to</p> <blockquote> <p>Zheng, Mengjie, Sheehan, Anne, Liu, Chuanming, Wu, Mengyu, & Ritzwoller, Michael. (2024). Characterizing Sub-Seafloor Seismic Structure of the Alaska Peninsula Along the Alaska-Aleutian Subduction Zone. <em>Journal of Geophysical Research: Solid Earth</em>, <em>129</em>(11), e2024JB029862. <a href="https://doi.org/10.1029/2024JB029862">https://doi.org/10.1029/2024JB029862</a></p> </blockquote> <p>This dataset contains files of sub-seafloor S-wave velocities and sediment properties.</p>
Parihaka Annotated Seismic Dataset - Slices from Cube (inlines and crosslines)
<p><strong>Parihaka Seismic Dataset</strong></p> <p> </p> <p><strong>Description - Images</strong></p> <p><strong>crosslines:</strong> TIFF image data, little-endian, direntries=10, height=1006, bps=134, compression=none, PhotometricIntepretation=RGB, width=590</p> <p><strong>inlines:</strong> TIFF image data, little-endian, direntries=10, height=1006, bps=134, compression=none, PhotometricIntepretation=RGB, width=781</p> <p> </p> <p><strong>Description - Labels (Annotations)</strong></p> <p><strong>crosslines:</strong> PNG image data, 590 x 1006, 8-bit grayscale, non-interlaced</p> <p><strong>inlines:</strong> PNG image data, 781 x 1006, 8-bit grayscale, non-interlaced</p> <p> </p> <p> </p> <p>Acknowledgements:<br><br>New Zealand Petroleum and Minerals (NZPM) for providing data<br>https://www.nzpam.govt.nz/</p> <p>https://geodata.nzpam.govt.nz/</p> <p> </p> <p>The training labels for this volume have been provided by Chevron U.S.A. Inc</p> <p> </p> <p>The original data is from: 2020 SEG Annual Meeting Machine Learning Interpretation Workshop by Susan Stamm (Sep 3, 2020). Available at: https://public.3.basecamp.com/p/JyT276MM7krjYrMoLqLQ6xST</p>
Supplemental datafiles for the manuscript "On the origin of seismic anisotropy in the shallow crust of the Northern Volcanic Zone, Iceland"
<p>Files to accompany the submission of the manuscript <strong>"On the origin of seismic anisotropy in the shallow crust of the Northern Volcanic Zone, Iceland" </strong>to the Journal of Geophysical Research: Solid Earth.<br> <br> <strong>File 1: </strong>conorbacon_ds01.inp - Input file for Coulomb</p> <p><strong>File 2: </strong>conorbacon_ds02.txt - Shear-wave splitting results file</p> <p> </p>
Data products for "3D modeling of long-term slow slip events along the flat-slab segment in the Guerrero Seismic Gap, Mexico"
<p>Data products for '3D modeling of long-term slow slip events along the flat-slab segment in the Guerrero Seismic Gap, Mexico' by A. Perez-Silva, D. Li, A.-A. Gabriel and Y. Kaneko</p>
Seismic noise recorded at Solfatara Volcano in April 2007
<p>Seismic noise recorded during a seismic survey carried out at Solfatara Volcano in the period 2-6 April 2007. Five circular seismic arrays were deployed inside the crater; an other seismic station was installed on the eastern rim for a hardrock reference. Details on the experiment, as well as data description and station coordinates are reported in: Petrosino, S., Damiano, N., Cusano, P., Veneruso, M., Zaccarelli, L., Torello, V., & Del Pezzo, E. (2008). Seismic noise at Solfatara Volcano (Campi Flegrei, Italy): acquisition techniques and first results. <em>Quaderni di Geofisica</em>.</p> <p>Shallow crustal structure of Solfatara volcano, inferred from dataset analysis has been published in: Petrosino, S., Damiano, N., Cusano, P., Di Vito, M. A., de Vita, S., & Del Pezzo, E. (2012). Subsurface structure of the Solfatara volcano (Campi Flegrei caldera, Italy) as deduced from joint seismic‐noise array, volcanological and morphostructural analysis. <em>Geochemistry, Geophysics, Geosystems</em>, <em>13</em>(7).</p>
Seismic noise recorded at Bagnolifutura area (Campi Flegrei) in 2012
<p>In 2012 two seismic surveys were carried out in the area of Bagnolifutura (Campi Flegrei, Naples), with the aim of characterizing the properties of the seismic noise. During the first survey, which was conducted from 2 to 4 April, seven broadband three-component seismometers were installed in two different array configurations. The second survey started on November 26 and ended on December 5. During this period, seismic noie was recorded by seven broadband and one short-period three-component sensors.</p>
Controls on post-seismic landslide behaviour in brittle rocks - Datasets
<p>Datasets summarising:</p> <p>1. DynBPS direct shear data;</p> <p>2. physical properties of the Tubul Sandstone analysed; and</p> <p>3. post-shear height profiles along samples, derived from Structure-from-Motion photogrammetry.</p>
Data for "The interplay between seismic and aseismic slip along the Chaman fault illuminated by InSAR" submitted to JGR: Solid Earth
<p>This compressed folder contains data presented in Figures of the following paper : <strong>"The interplay between seismic and aseismic slip along the Chaman fault illuminated by InSAR" </strong>by<em> </em>M. Dalaison, R. Jolivet, E. M. van Rijsingen and S. Michel, submitted to <em>JGR: Solid Earth </em>in August 2021.</p> <p>Data are in their final processed version. Raw data used in this study are freely available online ( scihub.copernicus.eu, earthdata.nasa.gov, www.ecmwf.int, pubs.usgs.gov/of/2007/1103 )</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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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.