Find research datasets worth reusing

Fiber-optic seismic sensing of vadose zone soil moisture dynamics data sets

CC_daily.h5: Daily cross-correlation functions for common-offset DAS channels. RCC_dv_v_full.csv: Summary of all the measured dv/v from the ballistic surface waves in daily cross-correlation functions.

Trained Random Forest Model for PNW Seismic Event Classification Trained on 150s waveforms (P-50, P+100), 50 Hz, and 1-10 Hz BP Filtered

This dataset contains three trained  random forest models named as following -  <ul> <li>P_10_100_F_1_10_50.joblib - This is a model trained on 110s long waveforms (origin time - 10, origin time +100) in case of earthquakes and explosions and (first arrival pick -10, first arrival pick + 100) in case of surface events, the waveforms are tapered using 10% cosine taper, bandpass filtered between 1-10 Hz using Butterworth four corner filter, normalized and resampled to 50 Hz. </li> <li>P_50_100_F_1_10_50.joblib </li> <li>P_10_30_F_1_15_50.joblib. </li> </ul> And also the standard scaler parameters for each features that will be used to normalize them.

opencc-by-4.0Jun 2024View details →

Microseismic catalogue from seismicity on the Jericho Fault (Dead Sea) [Dataset]

This is a database of results linked to the associated manuscript (Klinger et al., 2024) which has been submitted to Geophysical Journal International and is currently in review.   We report locations, magnitudes,  timing and location errors for microseismic events linked to seismic acitivity on the Jericho Fault. Prior to publication please cite this database using the following two references: Klinger, A.G., Kurzon, I., Sagy, A.  (2024). Microseismic and damage-zone characteristics of a fully locked fault segment on the Dead Sea Transform. Manuscript submitted to Geophysical Journal International .  Klinger, A.G., Werner, M.J.  (2021). Microseismic catalogue from seismicity on the Jericho Fault (Dead Sea) [Data set]. Zenodo. https://zenodo.org/uploads/11653666.

Codes, Catalogues and Data for "Deep Learning Phase Pickers: How Well Can Existing Models Detect Hydraulic-Fracturing Induced Seismicity from a Downhole Array"

Codes, Catalogues and Data available for:  "Deep Learning Phase Pickers: How Well Can Existing Models Detect Hydraulic-Fracturing Induced Seismicity from a Downhole Array" Catalog folder: Contains the CMM (beam-forming based) event catalogue as well as event and station information for the PNR-1z site. Classification Test folder: Jupyter notebooks that run the classification tests and mseed input data of isolated phases (P, S, Noise). DL_model_catalogues folder: Contains full catalogues for each DL phase picker (GPD, U-GPD, EQT and PhaseNet) and the LinMEF-filtered catalogues. Model_run_docs folder: Util/core files for PhaseNet and EQTransformer to read data with different sampling frequencies (i.e., not 100 Hz) Data folder: Contains one hour of continuous downhole data (11th December 2018, 9am-10am) from the PNR-1z dataset.

opencc-by-4.0Jul 2018View details →

Imaging subsurface structure of an urban area based on Diffuse-Field Theory concept using seismic ambient noise

Ambient noise data for a small urban area of NER India. The data set constitute all the raw files that were used for figures in the paper by Bora et al.

opencc-by-4.0Apr 2019View details →

Seismic interpretation of key stratigraphic and structural surfaces, and crustal faults within the Galicia 3-D reflection survey

This repository contains all the seismic interpretations utilized for the analysis in the article "Origin of serpentinization patterns beneath the S-reflector detachment fault in the Galicia margin, offshore Spain".  The "Surfaces" file contains the CPS-3 shape files of the major stratigraphic and structural surfaces (seafloor, base of post-rift sedimentary strata, base of pre/syn-rift sedimentary strata, base of crystalline basement, S-reflector detachment fault, Moho). The "Faults" file contains the interpretations of the major crustal faults overlying the S-reflector detachment. The "Data" file contains the spatial boundary of where the S-reflector is the crust-mantle boundary, the P-wave velocities of Schuba et al. (2019) and calculated degree of serpentinization (Schuba et al., submitted) based on Christensen's (2004) 200 MPa/200oC serpentinite compilation study.  All seismic interpretations were carried out on PetrelTM versions 2015 and 2017. The seismic reflection volume that was interpreted can be found at https://doi.org/10.1594/IEDA/500151.   References:  <ul> <li>Christensen, N.I. (2004). Serpentinites, Peridotites, and Seismology. International Geology Review, 46(9), 795-816. https://doi.org/10.2747/0020-6814.46.9.795</li> <li>Schuba, C.N., Schuba, J.P. Gray, G.G., and Davy, R.G., (2019). Interface targeted velocity estimation using machine learning. Geophysical Journal International, 218(1), 45-56. https://doi.org/10.1093/gji/ggz142</li> <li>Schuba, C.N., Gray, G.G., Morgan, J.K., Schuba, J.P., and Sawyer, D.S., (submitted). Interface targeted velocity estimation using machine learning. Geochemistry, Geophysics, Geosystems.</li> </ul>

opencc-by-4.0Aug 2019View details →

Changes in Permeability Caused by Two Consecutive Earthquakes – Insights from the Responses of a Well-Aquifer System to Seismic Waves

All data used in paper "Changes in Permeability Caused by Two Consecutive Earthquakes – Insights from the Responses of a Well-Aquifer System to Seismic Waves".

opencc-by-4.0Oct 2019View details →

GPS, InSAR, and seismic waveform data for study of 2014 South Napa, California, earthquake

GPS_Brocher_et_al2015.txt : Observed static offsets at CGPS and SGPS sites, respectively, presented by Brocher et al. (2015) determined using GPS time series up to several days after the event napa_CSK_20140619_20140903_asc.grd : Observed unwrapped COSMO-SkyMed ascending interferogram spanning June 19 - September 3, 2014 napa_CSK_20140726_20140827_desc.grd : Observed unwrapped COSMO-SkyMed descending interferogram spanning July 26 - August 27, 2014 napa_sentinel_20140807_20140831_desc.grd : Observed unwrapped Sentinel descending interferogram spanning August 7 - August 31, 2014 seismic_waveforms.tar.gz : Three-component seismic waveforms in (time (s after origin time), velocity (m/s)) format for 16 stations bandpass filtered between 0.067 and 1.5 Hz.  Filenames indicate which velocity component (East, North, or Up=Z) and station name. Study: "Coseismic slip and early after slip of the M6.0 August 24, 2014 South Napa, California, earthquake" by Fred F. Pollitz, Jessica R. Murray, Sarah E. Minson, Charles W. Wicks, and Jerry L. Svarc. Journal of Geophysical Research, in press

Dataset and Code Accompanying "Challenges and Learning from Exploring Deep Metric Learning for Identifying Seismic Stratigraphy"

Dataset and code related to the work outlined in "Challenges and Learning from Exploring Deep Metric Learning for Identifying Seismic Stratigraphy". File Description: <ul> <li>seis_seg.h5 - trained model weights.</li> <li>topseis_temp.npy - seismic survey.</li> <li>train_demo.ipynb - training demo including synthetic modelling pipeline.</li> <li>inference_and_plot - inference and reproducing main results.</li> </ul> Pre-calculated phase volume and encoded features for reproducing figures: <ul> <li>unwrapped_phase_volume_full.npy.</li> <li>features_full_ds222_ps32_s222.npy.</li> <li>indices_full_ds222_ps32_s222.npy.</li> </ul>

Lithospheric structure and strength variations in Antarctica from joint modeling of elevation, geoid and seismic data

These models include Moho depth, LAB depth and integrated lithospheric strength based on a 1D approach involving thermal analysis under local isostasy and a rheological method.

Kawah Ijen volcano seismic data 2012

Seismic data (vertical channel) from Kawah Ijen volcano at station IJEN. Information regarding the station location and sensor can be found in <a href="https://doi.org/10.1002/2014JB011590">https://doi.org/10.1002/2014JB011590</a>. Data were collected and archived thanks to Devy Syahbana, Suparjan and Bambang Heri Purwanto from CVGHM (Center for Volcanology and Geological Hazard Mitigation).

Supporting material for "Benford's law as debris flow detector in seismic signals"

Supporting material list, 0, Source code for Random_Forest_model; 1, Random_Forest_model.pkl, trained machine learning model; 2, FiguresSI.zip, 58 debris flow events with Benford's law features, and Exp. fitting curve; 3, Table2DebrisFlowEventDetails.xlsx, details of 58 debris flow events and expentional fitting parameters. Note, you can check our GitHub repository https://github.com/Nedasd/Benfords_law_as_mass_movements_detector.git

Scanned Seismograms for September 1973 - Santiago, Chile seismic station

Seismograms recorded by the SANTIAGO seismic station in September 1973. The sensor was a Teledyne Geotech S13 and the recorder a Geotech Helicorder RV01B. The scan was made thanks to the collaboration of the Servicio de Información y Bibliotecas (SISIB) of the Universidad de Chile.

Displacement time series from Foamquake and Gelquake in single- and double asperity configurations: Supplementary material to "Scaled seismotectonic models of megathrust seismic cycles through the lens of dynamical system theory"

This dataset includes displacement data from 4 experiments performed with Foamquake and Gelquake (Mastella et al. 2022, Corbi et al., 2013), two scaled seismotectonic models reproducing the megathrust seismic cycle running at the Laboratory of Experimental Tectonics LET (Univ. Roma Tre). These models enable the generation of hundreds of quasi-periodic cycles of stress accumulation and sudden release through the spontaneous nucleation of frictional instabilities within one or many analog seismic asperities. Models are monitored by the means of a high-resolution top-view monitoring camera acquiring images at 7.5 and 50 frames per second for Gelquake and Foamquake, respectively. This dataset has been created with particle image velocimetry (PIV, using MatPIV (Sveen 2004)) through the cross-correlation between consecutive images. The PIV provides us with velocity field time series. These are integrated to obtain displacement time series. From the whole model surface, in each experiment we selected data from a cross-section striking parallel to the trench and located at the downdip center of the asperities. Cross sections are discretized in 28 and 29 target points in Gelquake and Foamquake, respectively.  Displacement time series have been normalized to zero mean and unit variance to ensure the same level of magnitude for comparison between different experiments. Linear and second order polynomial trends have been removed to make the stick-slip confined in a given range and avoid non-stationary behavior. Time series data are not passed through filters (e.g., smoothing or moving average). Filename informs about the nature of the analog upper plate (i.e., foam and gel) and geometrical configuration of asperities (i.e., mono and twin). Together with individual files for each experiment, this dataset includes a Matlab script (i.e., all_timeseries.m) that allows visualization of displacement time series from individual target points.  This dataset is supplementary to the paper in SEISMICA "Scaled seismotectonic models of megathrust seismic cycles through the lens of dynamical system theory” by Corbi et al. (2024), where detailed descriptions of models and experimental results can be found.

Postseismic Deformation Due to the 2021 MW 7.4 Maduo (China) Earthquake and Implications for Regional Rheology and Seismic Hazards around the Bayan Har block

input.sh:  Model input file in RELAX to simulate the coupled afterslip and viscoelastic contributions in the study of Tian et al. (2024), EPSL ****.txt: Observed postseismic time series following the 2021 MW 7.4 Maduo (China) Earthquake   Title: Postseismic Deformation Due to the 2021 MW 7.4 Maduo (China) Earthquake and Implications for Regional Rheology and Seismic Hazards around the Bayan Har block

Data for Urban Seismic Source Mapping

In this study, we explore the innovative use of existing and ubiquitous urban infrastructure--telecommunication optical fibers--to map urban seismic sources. We integrate seismic interferometry and beamforming algorithms to overcome the proximity limitations of previous urban seismology approaches.  Our method models the propagation of seismic surface waves to estimate the spatio-temporal distribution of seismic source power (SSP; average seismic energy per unit of time), enabling the detection and localization of urban seismic sources occurring remotely from optical fibers. <code>Put these pickle files into '/urban_das/data/das_data/' and run the scripts at https://github.com/jingxiaoliu/urban_das</code> If you use this implementation, please cite our papers: <blockquote> [1] Liu, J., Li, H., Noh, H. Y., Santi, P., Biondi, B., & Ratti, C. (2025). Urban sensing using existing fiber-optic networks. Nature Communications, 16(1), 3091. [2] Yuan, S., Liu, J., Noh, H. Y., Clapp, R., & Biondi, B. (2024). Using vehicle‐induced DAS signals for near‐surface characterization with high spatiotemporal resolution. Journal of Geophysical Research: Solid Earth, 129(4), e2023JB028033. [3] Liu, J., Yuan, S., Dong, Y., Biondi, B., & Noh, H. Y. (2023). TelecomTM: A fine-grained and ubiquitous traffic monitoring system using pre-existing telecommunication fiber-optic cables as sensors. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 7(2), 1-24. </blockquote>

japan-seismic-waveform-synthetics

Open the record for dataset details and reuse information.

Vs30 and f0 values from the Project: Study of Historical Seismicity in Azuay and Seismic Microzonation of the Soils in Cuenca, Ecuador

This study presents 100 Vs30 values and 530 f0 values derived from the project: Study of Historical Seismicity in Azuay and Seismic Microzonation of the Soils in Cuenca, Ecuador. The article, titled 'Seismic Microzonation of Cuenca: Soil Classification Based on Fundamental Frequency and Shear Wave Velocity,' explores the implications of these measurements for understanding local soil behavior under seismic conditions.

opencc-by-4.0Oct 2024View details →

Crustal structure of northwestern Iran based on regional seismic tomography

The tomography model presented in the paper "Crustal structure of northwestern Iran based on regional seismic tomography" are obtained using the LOTOS code by Koulakov (2009). Here, we present the full version of the code with initial data and parameters used for calculating P and S velocity models beneath the northwestern Iran. This version of the code is adopted for the Windows OS and contains the entire program listing and the full project structure for Microsoft Visual Studio 2010 and Intel Visual Fortran. Detailed description of the code can be found at <a href="http://www.ivan-art.com/science/LOTOS">www.ivan-art.com/science/LOTOS</a> This file includes: 1. The full folder with the LOTOS code for the passive-source seismic tomography (Koulakov, 2009, BSSA).  2. Folder with the dataset including arrival times of the P and S waves from local seismicity in the area of NW Iran. 3. README_NW_IRAN.PDF file with the description of the workflow on how to reproduce the tomography models based on experimental and synthetic data presented in the article.  4. Folder SRF_FIGS with figures from the paper created in Surfer-13 that can be used as templates to visualize the results.  Koulakov, I., 2009, LOTOS code for local earthquake tomographic inversion: Benchmarks for testing tomographic algorithms: Bulletin of the Seismological Society of America, v. 99, p. 194–214, https://doi.org/10.1785/0120080013.