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662 results for “seismicity”
Density maps of seismic localization with a low phase coherence at 13 Hz on Argentière glacier
<p>This dataset is associated with the paper:</p> <p>----------</p> <p><strong>Dynamic imaging of glacier structures at high-resolution using source localization: a dense seismic array experiment.</strong></p> <p> </p> <p><em>Ugo Nanni<sup>1,*</sup>, Philippe Roux<sup>2</sup>, Florent Gimbert<sup>1</sup> and Albanne Lecointre<sup>2</sup></em></p> <p> </p> <p><em><sup>1</sup> IGE, Univ. Grenoble Alpes, CNRS, IRD, Grenoble, France</em></p> <p><em><sup>2</sup> ISTerre, Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, IRD, IFSTTAR, Grenoble, France</em></p> <p><em>---------</em></p> <p>It contains 32 maps of seismic localization associated with low phase coherence and frequency of 13 Hz, and represents the events originating from transverse crevasses (see details in the paper).</p> <p>An image of the glacier is also provided to compare the localization to the glacier structure.</p> <p>Dataset is in .mat format</p> <p> </p>
Seismic Network and Motifs Vrancea
<p>A seismic network for earthquakes with magnitude larger than 4 in Vrancea, Romania seismic region. Here are also presented the network's 3 nodes motifs (triangles)</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>
Additional dataset concerning "Observations of mantle seismic anisotropy using array techniques: shear-wave splitting of beamformed SmKS phases"
<p>SplitRacer input and output for beams and single-station splitting measurements for event 201007290731. This dataset was used in "Observations of mantle seismic anisotropy using array techniques: shear-wave splitting of beamformed SmKS phases" by Jonathan Wolf, Daniel A. Frost, Maureen D. Long, Ed Garnero, Adeolu O. Aderoju, Neala Creasy and Ebru Bozdag. The manuscript is available at <a href="https://doi.org/10.1029/2022JB025556">https://doi.org/10.1029/2022JB025556</a>.</p>
Toward understanding tectonic and geometric control on the Lenglongling fault from inter- and co-seismic InSAR observations
<p>The datasets include the interseismic (2014-2021) and coseismic InSAR observations to characterize the interseismic slip-rate along the Qilian-Haiyuan fault, the fault geometry and coseismic slip distribution for the 2022 Menyuan earthquake.</p>
Inventories of landslides triggered by the 2019 Cotabato - Davao del Sur (Philippines) seismic sequence
<p>These files are related to the paper “Environmental effects following a seismic sequence: the 2019 Cotabato - Davao del Sur (Philippines) earthquakes” by Ferrario M. F., Perez J., Livio F., Rimando J., Michetti A. M., currently under review.</p> <p>Files include a multi-temporal inventory of landslides triggered during a seismic sequence. In October – December 2019, the Cotabato and Davao del Sur Provinces (Philippine) were hit by four Mw > 6.0 earthquakes. The sequence started with a Mw 6.4 on 16 October (EQ1), then three earthquakes with Mw of 6.6, 6.5 and 6.8 occurred on 29 October (EQ2), 31 October (EQ3) and 15 December 2019 (EQ4).</p> <p>Landslides were manually mapped on 3-m resolution PlanetScope images. Shapefiles are in WGS84 UTM Zone 51n and include:</p> <ul> <li>Area study: shapefile of the study area (inventories 2 and 3)</li> <li>Area study_October 2019: shapefile of the study area for inventory 1</li> <li>Landslides_ott2019: polygonal inventory of landslides mapped on images acquired on 24 and 28/10/2019, that is after EQ1</li> <li>Landslides_nov2019: polygonal inventory of landslides mapped on images acquired on 15 and 16/11/2019, that is after EQ3</li> <li>Landslides_dic2019: polygonal inventory of landslides mapped on images acquired on 05/02/2020, that is after EQ4</li> </ul>
Postdiction Competition - Sera.ta - Seismic Response of Masonry Cross Vaults: Shaking table tests and numerical validations
<p>Once the blind prediction has been completed (DOI 10.5281/zenodo.7624666), new data are given to the research groups to perform the post diction simulations. The main objectives are:</p> <ul> <li>to calibrate the numerical model based on the dynamic properties;</li> <li>to emprove the capability of different modelling/analysis approaches and better justify the numerical assumptions.</li> </ul> <p>Below you can find the data set for the post diction analysis namely:</p> <ul> <li>Unstrengthened specimen results: </li> <li>Strengthened specimen results: </li> <li>Results of mix mortars used for the TRM technique:</li> </ul> <p> </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>
Moment tensors of 2017 seismic swarm in Reykjanes Peninsula, Iceland
<p>Data for the paper: Pavla Hrubcová and Václav Vavryčuk, 2023. Tectonic stress changes related to plate spreading prior to the 2021 Fagradalsfjall eruption in SW Iceland. Tectonophysics, https://doi.org/10.1016/j.tecto.2023.229761</p>
The HELPOS Fault Database: a new contribution to seismic hazard assessment in Greece
<p>In seismically-active regions such as Greece, the mapping of active faults is a key step to assess seismic hazards and evaluate deterministic ground motion scenarios for infrastructure works, pipeline designs and other constructions of critical importance. Here, we present a comprehensive database of active onshore and offshore faults in Greece based on existing studies and GIS geospatial mapping using geological, geophysical, seismological and geomorphological criteria. The design and population of the database follows the NOAFaults concept <a href="http://doi.org/10.5281/zenodo.3483136">http://doi.org/10.5281/zenodo.3483136</a> and development in ARCGIS environment. The HELPOS database includes over 550 faults with simplified (linear) traces and lengths between 8 – 108 km (onshore part) together with their corresponding 2D rupture planes. Additional information includes parametric data such as maximum expected magnitude, slip rate, length, width, strike, dip angle, last seismic event, rupture depth (to top-fault) and fault kinematics. A particular aim of the HELPOS Fault database has been an update of the seismic sources model for the seismic hazard assessment of Greece considering shallow earthquakes, which involves modeling surface fault traces in terms of seismic sources at depth. The fault database is a major contribution to HELPOS with applications among others in volcano-tectonic settings, urban planning, paleoseismology, landscape processes, and in the study of active tectonics, deformation and interactions between overriding plate (Aegean) faults and the Hellenic subduction.</p> <p><strong>In this version of the database (v1.8) we include the onshore fault traces and rupture planes and the offshore fault traces</strong>.</p> <p>We acknowledge funding by project "HELPOS - Hellenic Plate Observing System” (MIS 5002697) which was funded by the Operational Programme “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014-2020) and co-financed by Greece and the European Union (European Regional Development Fund).</p>
Seafloor and volcanic seismic horizons from NZ3D
<p>This file (horizons.csv) contains picked seismic horizons for the seafloor and top of volcanic basement in the NZ3D volume within 15 km of the deformation front. The columns are formatted as crossline, inline, seafloor depth (m), top of volcanic basement (m).</p> <p>Raw and processed NZ3D seismic data can be downloaded here: https://www.marine-geo.org/tools/entry/MGL1801.</p>
InSight's seismic and meteorological data related to the Martian convective vortices
<p><strong>Overview:</strong></p> <p>This repository includes the catalog related to Martian convective vortices observed by NASA's InSight mission. The detailed description is made in the JGR Planet paper entitled "Systematic catalog of Martian convective vortices observed by InSight" by Onodera et al. When you use the information in the catalog, please refer to the following citation.</p> <ul> <li>Onodera, K. et al. (2023), InSight's seismic and meteorological data related to the Martian convective vortices, Zenodo,<em><strong> </strong></em>doi:10.5281/zenodo.7801343<em><strong>.</strong></em></li> </ul> <p><strong>Files:</strong></p> <p>The first numbers in each file name correspond to the ID number included in the catalog file (InSight_CV_Catalog.pickle). All files are in csv format including time in Local Mean True Time in sol, respective observation records. If a number is missing, that means the corresponding data were not available on that sol (at least with the sampling rate we focused on in our paper).</p> <ul> <li><strong>InSight_CV_Catalog.pickle</strong>: It includes all estimated parameters presented by Onodera et al. (2023).</li> <li> <p><strong>PS.zip</strong>: 20 min long pressure data centered at the maximum pressure drop time (LMST, Pressure).</p> </li> <li> <p><strong>VBB_ACC.zip</strong>: 20 min long acceleration data centered at the maximum pressure drop time (LMST, Z comp., N comp., E comp.).</p> </li> <li> <p><strong>WSpeed_WDir_ATemp_calib.zip</strong>: 20 min long calibrated wind & air temperature data centered at the maximum pressure drop time (LMST, Wind speed, Wind direction, Air temperature).</p> </li> </ul>
Seismic dataset for Ruapehu and Whakaari volcanoes in New Zealand
<p>RSAM, MF, HF and DSAR time series for Ruapehu stations FWVZ over the 14 years explored, and for Whakaari stations WIZ over 9 years.</p> <p>Computing datastreams: we harnessed seismic data from a vertical component station for each individual volcano. We applied data processing techniques that resulted in the generation of four distinct time series, with a sampling interval of 10 minutes. Various measures were employed to capture different aspects of the seismic signal. The first measure, known as the Real-time Seismic Amplitude Measurement (RSAM), was obtained by calculating the 10-minute moving average of the velocity recorded by the vertical station This signal was then subjected to bandpass filtering within the frequency range of 2 to 5 Hz, which focuses on tremor signal of frequent volcanic origin while excluding ocean noise at lower frequencies. Similarly, the Median Frequency (MF) and High Frequency (HF) measures were derived using a comparable approach to RSAM, but with specific bandpass filtering applied. MF was obtained by filtering the signal within the frequency range of 4.5 to 8 Hz, while HF was obtained by filtering within the frequency range of 8 to 16 Hz. The 4.5 Hz threshold between RSAM and MF reflects an assumption that tremor mostly radiates energy below 4.5 Hz. To exclude this effect and explore attenuation related to permeability change (such as sealing), this frequency value is used as a threshold. Lastly, the Displacement Seismic Amplitude Ratio (DSAR) was calculated as the ratio of the integrals of the MF and HF signals. High values of DSAR have been inferred to correlate with high gas levels in the edifice, suggesting either reduced fluid motion and/or trapping that has led to a gas-accumulation.</p>
Slip deficit rate realizations for 2023 New Zealand National Seismic Hazard Model geodetic inversions
<p>This data set contains inversion results presented in Johnson et al. (2023) and also Johnson et al. (2022). All calculations involving slip deficit rates in those papers were conducted using the results in the files provided in this data set. </p>
Seismic records of the April 12, 2014 Solomon Islands (Mw = 7.6) earthquake (Sadeghi-Bagherabadi et al. 2023)
<p>Seismic records of the April 12, 2014 Solomon Islands (Mw = 7.6) earthquake (Sadeghi-Bagherabadi et al. 2023), recorded by the CIGSIP temporarry network in the western Arabia-Eurasia collision zone.</p> <p>Contact:<br> Amir Sadeghi-Bagherabadi (amir.sadeghi@hotmail.com)</p> <p>It is a supplement to:</p> <p><strong>Sadeghi-Bagherabadi, A., Margheriti, L., Aoudia, A., Baccheschi, P., Lucente, F. P., Sobouti, F., (2023). Anisotropic Gradients in Iran: Quasi-Love Waves Illuminate the Deep Structure and Deformation Style of the Zagros, Alborz and Kopet Dagh. Journal of Geodynamics, <a href="https://doi.org/10.1016/j.jog.2023.101989">https://doi.org/10.1016/j.jog.2023.101989</a></strong></p> <p>If you use this dataset, please cite the following paper:</p> <p><strong>Sadeghi-Bagherabadi, A., Margheriti, L., Aoudia, A., Baccheschi, P., Lucente, F. P., Sobouti, F., (2023). Anisotropic Gradients in Iran: Quasi-Love Waves Illuminate the Deep Structure and Deformation Style of the Zagros, Alborz and Kopet Dagh. Journal of Geodynamics, <a href="https://doi.org/10.1016/j.jog.2023.101989">https://doi.org/10.1016/j.jog.2023.101989</a></strong></p> <p>_________________________________________________________________</p> <p><br> Table of contents: </p> <p>SAC_files.tar.gz : includes seismic records of the April 12, 2014 Solomon Islands (Mw = 7.6) earthquake. The SAC file names are formatted as: YYYY.MM.DD-hh.mm.ss._SSSc.sac. For example '2014.04.12-20.14.39._E01e.sac' is the E-W component of station E01</p> <p>Resp_files.tar.gz : includes the station response files. The response file names are formatted as:MSSS-resp.txt. For example 'ME01-resp.txt' is the response file for station E01.</p> <p>_________________________________________________________________</p> <p>The CIGSIP project was a trilateral undertaking by the Institute for Advanced Studies in Basic Sciences (IASBS), Geological Survey of Iran, and Chinese Academy of Sciences. CIGSIP was funded and supported by the Strategic Priority Research Program (B) (Grant number XDB03010802) and the International Partnership Program (GJHZ1776) of the Chinese Academy of Sciences.</p>
Codes and catalogs for: Parametric testing of EQTransformer's performance against a high-quality, manually-picked catalog for reliable and accurate seismic phase picking
<p><strong>Codes and Catalogs for:</strong> "Parametric Testing of EQTransformer's Performance Against a High-Quality, Manually-Picked Catalog for Reliable and Accurate Seismic Phase Picking."</p> <p><strong>Codes:</strong></p> <ol> <li><strong>overlap_check.py:</strong> This script tests the overlap parameter of EQTransformer to help minimize detection inconsistencies.</li> <li><strong>picks_comparison_other_networks.py:</strong> This code evaluates the probability threshold of EQTransformer by obtaining the time differences between picks from a catalog and EQTransformer.</li> <li><strong>test_seisbench_eq_eqt.py:</strong> A comparative analysis between the native EQTransformer and its implementation in SeisBench.</li> </ol> <p><strong>Catalogs:</strong></p> <ol> <li><strong>picks_differences_all_years_0.01_mag_cat.csv:</strong> This catalog presents pick differences for the central Alpine Fault using the SAMBA network and manual picks from Michailos et al. (2019).</li> <li><strong>sed_picks.csv:</strong> A catalog that showcases pick differences derived from data obtained from the Swiss Seismological Service (SED).</li> </ol> <p><strong>Note:</strong> Versions <1.0 represent pre-acceptence files and should not be used.</p>
Legacy seismic data for large repeating earthquakes in Mexico
<p>In this dataset we include, in two different compressed files:1) a set of images of scanned Galitzin legacy seismograms recorded at the De Bilt Seismological Station, The Netherlands, corresponding to different large Mexican earthquakes (M>7.0) occurred between 1928 and 1978, and 2) the corresponding vectorized and corrected data.</p> <p><br> Description of compressed files:</p> <p>1. DBN-Vectorized-Seismograms.zip , that contains the vectorized data.</p> <p>2. DBN-Scanned-Galitzin-Seismograms.zip , that contains the scanned images of seismograms.</p> <p> </p> <p>Description of the files:</p> <p>1. Naming of Data Files.<br> Data are archived in XY ASCII files. The files are named as: STN_yyyy_mm_dd_C_p?.txt. Here:</p> <p>STN refers to the Station identification code<br> yyyy stands for the four-digit year<br> mm designates the two-digit month<br> dd signifies the two-digit day<br> C indicates the Component (either Z, NS, or EW)<br> p? represents the segment (0, 1, or 2) when applicable. Seismograms are sometimes divided in more than one segment (up to 3). The first segment is labeled P0. Subsequent segments are named P1 and P2. </p> <p> </p> <p>2. Naming of Scanned images.<br> Data are archived in JPG images. The files are named as: STN_yyyy_mm_dd_C.jpg. Here:</p> <p>STN refers to the Station identification code<br> yyyy stands for the four-digit year<br> mm designates the two-digit month<br> dd signifies the two-digit day<br> C indicates the Component (either Z, NS, or EW)<br> </p>
Catalog of seismicity for the Kerguelen Islands (1999-2020)
<p>This catalog of the seismicity of the Kerguelen Islands is related to the article: 'Recent seismicity on the Kerguelen Islands' by O. Lengliné, J. Rimpôt, A. Maggi and D. Zigone, Seismica, 2023.<br> </p>
Knowledge-Graphs-for-Seismic-Data-and-Metadata: Data
<p><strong>Abstract</strong></p> <p>The increasing scale and diversity of seismic data, and the growing role of big data in seismology, has raised interest in methods to make data exploration more accessible. This paper presents the use of knowledge graphs (KGs) for representing seismic data and metadata to improve data exploration and analysis, focusing on usability, flexibility, and extensibility. Using constraints derived from domain knowledge in seismology, we define semantic models of seismic station and event information used to construct the KGs. Our approach utilizes the capability of KGs to integrate data across many sources and diverse schema formats. We use schema-diverse, real-world seismic data to construct KGs with millions of nodes, and illustrate potential applications with three big-data examples. Our findings demonstrate the potential of KGs to enhance the efficiency and efficacy of seismological workflows in research and beyond, indicating a promising interdisciplinary future for this technology.</p> <p><strong>Methods</strong></p> <p>The data here consists of, and was collected from:</p> <ul> <li>Station metadata, in StationXML format, acquired from IRIS DMC using the fdsnws-station webservice (https://service.iris.edu/fdsnws/station/1/).</li> <li>Earthquake event data, in NDK format, acquired from the Global Centroid-Moment Tensor (GCMT) catalog webservice (https://www.globalcmt.org) [1,2]. </li> <li>Earthquake event data, in CSV format, acquired from the Northern California Seismic Network (NCSN) catalog using the NCEDC's Northern California Earthquake Catalog Search webservice (doi.org/10.7932/NCEDC) [3].</li> <li>Earthquake event data, in CSV format, acquired from the USGS earthquake catalog webservice (doi.org/10.5066/F7MS3QZH) [4].</li> </ul> <p>A complete description of the StationXML file format can be found at https://www.fdsn.org/xml/station/.</p> <p>A complete description of the NDK file format can be found at https://www.ldeo.columbia.edu/~gcmt/projects/CMT/catalog/allorder.ndk_explained. </p> <p>A complete description of the NCEDC file format can be found at https://ncedc.org/pub/doc/cat1/catlist.txt.</p> <p>A complete description of the USGS file format can be found at https://earthquake.usgs.gov/data/comcat/#event-terms.</p> <p>Also provided are conversions from NDK and StationXML file formats into JSON format. </p> <p><strong>Usage Notes</strong></p> <p>No special programs or software is reqired to open the data files included here.</p> <p><strong>References</strong></p> <p>[1] Dziewonski, A. M., Chou, T. A., & Woodhouse, J. H. (1981). Determination of earthquake source parameters from waveform data for studies of global and regional seismicity. <em>Journal of Geophysical Research: Solid Earth</em>, <em>86</em>(B4), 2825-2852.</p> <p>[2] Ekström, G., Nettles, M., & Dziewoński, A. M. (2012). The global CMT project 2004–2010: Centroid-moment tensors for 13,017 earthquakes. <em>Physics of the Earth and Planetary Interiors</em>, <em>200</em>, 1-9.</p> <p>[3] NCEDC (2014), Northern California Earthquake Data Center. UC Berkeley Seismological Laboratory. Dataset. doi:10.7932/NCEDC.</p> <p>[4] U.S. Geological Survey, Earthquake Hazards Program, 2017, Advanced National Seismic System (ANSS) Comprehensive Catalog of Earthquake Events and Products: Various, https://doi.org/10.5066/F7MS3QZH.</p> <p> </p>
Dataset for "Seismic signatures of partial steam saturation in fractured geothermal reservoirs: Insights from poroelasticity"
<p>Dataset for "Seismic signatures of partial steam saturation in fractured geothermal reservoirs: Insights from poroelasticity". This dataset allows to reproduce the figures of the manuscript. Cite: Quiroga, G. E., Rubino, J. G., Solazzi, S. G., Barbosa, N. D., Favino, M., & Holliger, K. (2023). Seismic signatures of partial steam saturation in fractured geothermal reservoirs: Insights from poroelasticity. <em>Geophysics</em>, <em>88</em>(5), WB89-WB104.</p> <p> </p>
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