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662 results for “seismicity”
Pre- and co-seismic landslides of the Sept. 5 Luding earthquake
<p>This folder contains the pre- and co-seismic landslides inventories, intensity circle, and seismogenic fault of the Mw 6.6 Luding, China earthquake. The earthquake occurred on 2022-09-05 at 04:52 UTC, the hypocenter was located at 29.61° N, 102.03° E at a depth of 13.0 km. The mapping region encompasses the intensity IX circle of the earthquake.</p>
Original waveform of TanluArray portable seismic network in the Tanlu fault zone and surrounding areas
<p>The waveform in this folder was recorded by the National Institute of Natural Hazards (NINH) (cut by catalog from 2019 and 2021). Waveform data were intercepted from the 10s before and 10s after the theoretical arrival-time of Pn. It is only used for scientific research.</p>
Relocated event catalog for 2014-2023 seismicity at Campi Flegrei
Open the record for dataset details and reuse information.
Country/Territory Seismic Risk Profiles
<p>The GEM Foundation has produced a collection of Country/Territory Seismic Risk Profiles that summarize key metrics of seismic risk, to provide stakeholders in risk management an overview of the risk in a region at-a-glance. Each profile presents the following relavant information:</p> <ul> <li>Social indicators, which provide context to the region in question </li> <li>Risk indicators, detailing an occupancy breakdown of exposed value and losses </li> <li>A list of the major earthquakes that have impacted the region </li> <li>Loss per region, providing a breakdown of average annual losses per Administrative level 1 </li> <li>Building classes, depicting the major construction materials used in the region </li> <li>Loss curves, which provide expected losses per different return periods </li> <li>Maps depicting the geographical distribution of hazard, exposure and losses </li> </ul> <p>The risk results are the results of an event-based risk analysis, where 100,000 years of earthquakes are simulated. Three lines of business are considered: residential, commercial, and industrial. Therefore, value or earthquake losses to other building occupancies (e.g., schools, healthcare) and infrastructure are not included.</p>
Multichannel seismic reflection data used in a geophysical survey at the northern continental margin of the South China Sea
<p>This archive includes the stacked multichannel seismic reflection waveform data. The CDP interval is 12.5 m. This raw data was collected by the Guangzhou Marine Geological Survey (GMGS) between July and September 2020. </p>
Seismic investigation of an Arctic glacier accelerating under climate warming
<p>The data shared here at the one used in the associated paper. They focus on the Arctic glacier Kongsvegen (check location here: https://toposvalbard.npolar.no/), in Svalbard and are linked to the mammamia project (https://www.mn.uio.no/geo/english/research/projects/mammamia/). They are composed of DEM, modelled runoff and seismic measurements. All the processing is detailed in the associated paper. Please cite both the paper and the dataset when using this data. Feel free to reach out if needed.</p><ul><li><i>DEM_dataset_Nanni</i>: glacier surface elevation from 2013 to 2022, glacier bed elevation, dh/dt from 2000 to 2020 (from https://www.theia-land.fr/product/altitude-des-glaciers/). Format: georeferenced .tif.</li><li><i>runoff_1992to2022</i>: runoff at a 3 hour time step at grid point specified by <strong>lat</strong>, <strong>lon</strong> and time specified by <strong>time</strong>. Data is processed following https://doi.org/10.5194/tc-17-2941-2023. Format: .txt tab separated</li><li><i>PSD_NANNI</i>: contains all power spectral density of all seismic stations from 2018 to 2023 for the vertical component. For each year and each station there are 3 files: <strong>frequency</strong> (frequency at which was computed the PSD), <strong>time</strong> (time at which was computed the PSD) and the <strong>PSD</strong> file that contains the PSD value at each (time,frequency) pair. Do not pay attention at the terms corr or resampled in the files names. Note that not all stations have continuous record. KNG stations are for the period 2018-2019, KGS for 2020-2023. Format: .txt tab separated.</li><li><i>PSD_KGS_figure</i>: plotted PSD for each year-station pair for the vertical component.</li><li><i>METADATA_NANNI</i>: contains the stations location and the group to which their belong.</li><li><i>ICEQUAKE_NANNI</i>: contains the time (<strong>time</strong>), amplitude (<strong>mean</strong> and <strong>median</strong>) and rate (<strong>rate </strong>in event per hour) of the icequake detection for each station (<strong>stations</strong>). Format: .txt tab separated. This was computed with STA/LTA, see paper for details.</li></ul><p> </p>
Dataset for the seismically monitored experiments of free-fall granular masses
<p>Datasets related to the paper "Experiments on Landquakes Generated by Free-fall Granular Masses: Implications for Rockfall Impacting Dynamics", submitted to <em>Earth and Space Science</em>.</p> <p>S1_images_the dynamic evolution of the free-fall granular masses tracked by a high-speed camera.</p> <p>S2_data_ data of vertical acceleration signals for all tests recorded by an accelerometer.</p> <p>S3_data_ data of the extracted seismic parameters including maximum seismic amplitude, mean frequency and radiated seismic energy for all tests.</p> <p>S4_data_ data supporting the relationships between intermediate functions associated with the maximum seismic amplitude, mean frequency and seismic energy and number of particles.</p> <p>S5_data_ data supporting the successive velocity profiles and acceleration profiles along the vertical direction of the granular mass.</p> <p>S6_data_ data supporting the relationships between the ratio of components in a granular mass contributing to the maximum seismic amplitude with the number of layers.</p> <p>S7_data_data supporting the relationships between intermediate coefficients associated with the maximum seismic amplitude, mean frequency and seismic energy and the number of layers of granular masses.</p> <p>S8_data_ data of spectrogram of condition D5 computed using Stockwell transform based on the acceleration signals recorded by an accelerometer.</p> <p>S9_data_ data supporting the evolutions of horizontal and vertical motion components of granular masses of tests C1-C5 over time.</p> <p>S10_data_ data supporting the relationships between characteristic frequency and the velocity vector of granular masses of series C, D, E and F.</p>
TDMT solutions from catalog of "A Large Fault Partially Reactivated During Two Contiguous Seismic Sequences in Central Italy: The Role of Geometrical and Frictional Heterogeneities"
<p>Some new TDMT solutions from catalog at the link <a href="https://doi.org/10.5281/zenodo.10801577">https://doi.org/10.5281/zenodo.10801577</a>. The catalog contains events with M > 3.0, that occurred between January 2009 and April 2021, in Campotosto area, Italy. Moment tensor were calculated by applying the Time Domain Moment Tensor technique, originally proposed by Dreger and Helmberger (1993) and Pasyanos et al. (1996) and successively implemented at INGV by Scognamiglio et al. (2009).</p> <p>For every moment tensor the PDF file contains the event location, waveform fits, nodal planes, magnitude, double couple (DC) and compensated linear vector dipole (CLVD) values, variance reduction, six components of moment tensor and station coverage.</p>
To enhance CO2 saturation prediction from seismic data by joint use of attenuation and elastic properties: A machine learning approach
<p>Wang and Zhao submitted for GJI</p>
Data for Seismic Noise and Subsurface Velocity Characterization for a Unique Bedload Monitoring Observatory in a Dryland Ephemeral Channel
<p>Seismic dataset used in submitted manuscript "Seismic Noise and Subsurface Velocity Characterization for a Unique Bedload Monitoring Observatory in a Dryland Ephemeral Channel".</p>
Multivariate Ordinary Least Squares (OLS) regression-based Seismic Hazard Model Data
<p>This dataset includes earthquake parameters, slab geometry, gravity anomalies, and fault proximities used for seismic hazard modeling in the Makran Subduction Zone (MSZ). Supplementary Table S1 contains earthquake data (location, depth, magnitude), slab properties (depth, dip, thickness, strike), and distances to key faults. Supplementary Table S2 provides intraslab seismicity, slab geometry, trench distances, and gravity data. The data are sourced from the USGS Earthquake Catalog, IRIS, Slab-2 model, GMRT, and other geophysical models.</p>
Dataset and machine learning models for seismic response predictions of small-to-medium continuous girder bridges
<p>This upload includes the dataset and machine learning models (based on Matlab platform) for longitudinal seismic response predictions of multi-span highway girder bridges, which have a typical span length of 30 m supported by reinforced concrete (RC) bridge bents and abutments through spherical steel bearings. The input variables (features) are five structural parameters of studied bridges and seven intensity measures of earthquakes. The output variables (labels) are peak column drifts and peak bearing deformations. The dataset is developed by conducting a total number of 720 nonlinear time-history analyses considering the uncertainty of bridges and earthquakes. Machine learning models are developed using two popular machine learning algorithms named artificial neural network (ANN) and support vector regression (SVR).</p>
Seismic refraction, reflection and free-air gravity data of OBS2020-3 in the southwest sub-basin, South China Sea
<p>This dataset (OBS2020-3.Files.zip) contains SEGY files of the OBS2020-3 and the NW section of the MCS2020-3 profiles, as well as the free-air gravity anomaly data along the seismic profiles. The time-axis of the SEGY files for the ocean bottom seismometers are reduced by a reduction velocity of 6.0 km/s. </p>
Investigating the Characteristics of Microseisms using the Australian Seismic Arrays
<p>This repository contains supporting data for reproducing back-projection figures in the manuscript entitled "Investigating the Characteristics of Microseisms using the Australian Seismic Arrays". Please see the readme file in the directory.</p>
GPS data and plotting codes for Remote Sensing paper titled Utilizing Seismic Station Internal GPS for Tracking Surging Glacier Sliding Velocity
<p>Data files (meteorological data, sattelite derived velocity time series, and seismic station GPS data) and plotting codes to reproduce the dataset and plots presented in the paper Gajek et al., Utilizing Seismic Station Internal GPS for Tracking Surging Glacier Sliding Velocity</p>
Dataset of flow rate, water temperature, radon concentration, and seismic waveforms from a hot spring system
<p>Flow rate, water temperature, radon concentration, meteorological data, and seismic waveforms in a hot spring system that used for investigating the groundwater radon changes and hydrological responses induced by large earthquakes. </p>
Rate-and-state friction parameters for "Frictional Characteristics of Oceanic Transform Faults: Progressive Deformation and Alteration Controls Seismic Style"
<p>Rate-and-state friction parameters to accompany "Frictional Characteristics of Oceanic Transform Faults: Progressive Deformation and Alteration Controls Seismic Style"</p>
Implications of sound velocities of natural topaz on the seismic L-discontinuity
<p>This is the data for the paper "Implications of sound velocities of natural topaz on the seismic L-discontinuity".</p>
Physically-Augmented Deep Learning (PADL): Integration of Physical Context for Improved Seismic Event Discrimination
<p>Data for the publication <em>Physically-Augmented Deep Learning (PADL): Integration of Physical Context for Improved Seismic Event Discrimination. </em>Submitted to Geophysical Research Letters<em> </em>(peer review in progress). </p>
Relative traveltimes and amplitude ratios of seismic triplications for the four earthquakes in the southwestern Siberia and resulting best-fit LVL velocity models
<p>For details about the data, please see the published paper titled "A partial molten low-velocity layer atop the mantle transition zone beneath the western Junggar: implication for the formation of subduction-induced sub-slab mantle plume" in the journal G-Cubed.</p>
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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)
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DANDI Archive for NWB datasets
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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.