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Dataset results
17 results for “geodetic data”
New fault slip distribution for the 2010 Mw 7.2 El Mayor Cucapah earthquake based on realistic 3D finite element inversions of coseismic displacements using space geodetic data
<p>The .csv files included in this repository contain the data used in the numerical model as input, while the .txt file is the output (slip on a regular grid of points on the fault planes from the joint inversion of the geodetic datasets.</p>
Geodetic displacement data near North Brawley Geothermal Field, 2009-2019
<p>Supplementary Dataset for Materna, Barbour, Jiang, and Eneva (2022), "Detection of aseismic slip and poroelastic reservoir deformation at the North Brawley Geothermal Field from 2009–2019". The 2009-2019 downsampled and processed displacements for modeling, shown in their Figure 3, are presented in this repository. Processing methods are included in detail in the paper. Also included are the fault geometries used for modeling and the surface rupture trace of the M4.7 normal faulting earthquake in the 2012 Brawley Swarm, traced from a UAVSAR interferogram. </p> <p>TerraSAR-X data were ordered from the German Space Agency (DLR), using funding from grant GEO-10-001 awarded to Imageair Inc. by the California Energy Commission (CEC). InSAR/SqueeSAR processing of these data was done by TRE Altamira in Canada and Italy under CEC grant GEO-16-003 to Imageair Inc. Leveling data were obtained from the Imperial County Department of Public Works (https://publicworks.imperialcounty.org) and processed under the same grant. The Copernicus Sentinel-1 data were processed by the European Space Agency (ESA) and retrieved from the Alaska Satellite Facility (ASF) (https://search.asf.alaska.edu/). Sentinel-1 displacement time series were derived from interferograms processed in Jiang and Lohman (2021) through the support of Southern California Earthquake Center (SCEC) award 20139. SCEC is funded by NSF Cooperative Agreement EAR-1600087 & USGS Cooperative Agreement G17AC00047. UAVSAR data can be downloaded at https://uavsar.jpl.nasa.gov/. Quadtree downsampling was performed with the Kite library (Isken et al., 2017).</p>
Coseismic Surface Ruptures of 20 Strike-Slip Earthquakes Measured from Geodetic Imaging Data
<p>Coseismic surface displacement maps for 20 strike-slip surface rupturing earthquakes measured from radar and optical pixel tracking data. </p> <p>This dataset contains 2D and 3D surface displacement maps, fault traces, total fault-parallel slip measured from the surface displacement maps, a number of strain maps and image IDs used to generate the surface displacement maps </p>
SDUST2023BCO: a global seafloor model determined from multi-layer perceptron neural network using multi-source differential marine geodetic data
<div> <p>SDUST2023BCO.nc is the global marine bathymetric model covering 80°S~80°N and 0°~360°E on 1′×1′ grids. The dataset contains geospatial information (latitude, longitude), SDUST2023BCO bathymetric model and an attachment data.</p> </div>
Operator-Software Impact in Local Tie Networks: Case study at Geodetic Observatory Wettzell (Data set)
<p>The operator-software impact describes the differences between results introduced by different operators using identical software packages but applying different analysis strategies to the same data. This contribution studies the operator-software impact in the framework of local tie determination, and compares two different analysis approaches. Both approaches are used in present local tie determinations and mainly differ in the consideration of the vertical deflection within the network adjustment. However, no comparison study has yet been made so far. Selecting a suitable analysis approach is interpreted as a model selection problem, which is addressed by information criteria within this investigation. A suitable model is indicated by a sufficient goodness of fit and an adequate number of model parameters. Moreover, the stiffness of the networks is evaluated by means of principle component analysis. Based on the date of a measurement campaign performed at the Geodetic Observatory Wettzell in 2021, the impact of the analysis approach on local ties is investigated. For that purpose, an innovated procedure is introduced to obtain reference points of space geodetic techniques defining the local ties. Within the procedure, the reference points are defined independently of the used reference frame, and are based on geometrical conditions. Thus, the results depend only on the estimates of the performed network adjustment and, hence, the applied network analysis approach. The comparison of the horizontal coordinates of the determined reference points shows a high agreement. The differences are less than 0.2 mm. However, the vertical components differ by more than 1 mm, and exceed the coverage of the estimated standard deviations. The main reasons for these large discrepancies are a network tilting and a network bending, which is confirmed by a residual analysis.</p>
Geodetic displacement data from Airborne-LiDAR data and Time Series InSAR: Baton Rouge Case Study.
<p>This repository the results produced by Hurtado-Pulido, Amer, Ebinger, and Holcomb “Variations in subsidence patterns in the Gulf of Mexico passive margin from Airborne-LiDAR data and Time Series InSAR: Baton Rouge Case Study”.</p> <p>This repository presents data sets for figures 4, 5, 6, 7 and 8. Processing methods are described in the paper. The READme file contains details about each file. Please address any questions about this dataset to Hurtado-Pulido.</p> <ul> <li>LiDAR data from 1999 is stored and distributed by the Atlas: The Louisiana Statewide GIS (<a href="https://maps.ga.lsu.edu/lidar2000/">https://maps.ga.lsu.edu/lidar2000/</a>). LiDAR data from 2018 is stored and distributed by the USGS Server through The National Map Download Manager (<a href="https://apps.nationalmap.gov/downloader/">https://apps.nationalmap.gov/downloader/</a>).</li> <li>EnviSAT SAR images were retrieved from the Earth Observation Catalogue (<a href="https://eocat.esa.int/sec/#data-services-area">https://eocat.esa.int/sec/#data-services-area</a>). Sentinel-1 SAR images from the Copernicus Open Access Hub (<a href="https://scihub.copernicus.eu/dhus/#/home">https://scihub.copernicus.eu/dhus/#/home</a>). Both property of the European Space Agency.</li> <li>GNSS information was processed by the Nevada Geodetic Laboratory (Blewitt et al., 2018; <a href="http://geodesy.unr.edu/NGLStationPages/gpsnetmap/GPSNetMap.html">http://geodesy.unr.edu/NGLStationPages/gpsnetmap/GPSNetMap.html</a>).</li> <li>Data from water, injection, and extraction wells is stored in the Strategic Online Natural Resources Information System property of the Louisiana Department of Natural Resources (<a href="http://sonris-www.dnr.state.la.us/gis/agsweb/IE/JSViewer/index.html?TemplateID=181">http://sonris-www.dnr.state.la.us/gis/agsweb/IE/JSViewer/index.html?TemplateID=181</a>).</li> </ul>
Comparative Analysis of Methods to Estimate Geodetic Strain Rates from GNSS Data in Italy
<p>This dataset comprises GNSS velocity field and strain rate maps for Italy.</p> <p><strong>List of Files:</strong></p> <ol> <li> <p><strong>velocity_dataset.dat</strong></p> <ul> <li>GNSS velocity field of stations with time series longer than 4.5 years.</li> <li>Columns: Longitude (degrees), Latitude (degrees), East component of velocity (mm/yr), North component of velocity (mm/yr), Uncertainty on the East component (mm/yr), Uncertainty on the North component (mm/yr), Station Name.</li> </ul> </li> <li> <p><strong>velocity_dataset_filtr.dat</strong></p> <ul> <li>Filtered velocity field.</li> <li>Columns: Longitude (degrees), Latitude (degrees), East component of velocity (mm/yr), North component of velocity (mm/yr), Uncertainty on the East component (mm/yr), Uncertainty on the North component (mm/yr), Station Name.</li> <li>Stations ending with 'GPM' represent velocity values obtained by merging neighboring stations.</li> </ul> </li> <li> <p><strong>strain_rate_nn.dat (strain_rate_visr.dat, strain_rate_wav.dat)</strong></p> <ul> <li>Strain rate computed on cells spaced by 0.025°.</li> <li>Suffixes in the file names: 'nn' refers to the Nearest Neighbor method, 'visr' refers to the VISR method, and 'wav' refers to the Wavelet-based method</li> <li>Columns: Longitude (degrees), Latitude (degrees), exx (east) component of the strain rate tensor (nstr/yr), exy (east, north) component of the strain rate tensor (nstr/yr), eyy (north) component of the strain rate tensor, second invariant of the strain rate (nstr/yr), most extensive eigenvalue (nstr/yr), most compressive eigenvalue (nstr/yr), angle between north and the direction of the eigenvector corresponding to the most compressive eigenvalue (degrees, positive clockwise).</li> </ul> </li> </ol> <p><strong>Reference:</strong></p> <p>For further details, please refer to the article "Comparative Analysis of Methods to Estimate Geodetic Strain Rates from GNSS Data in Italy", published in <em>Annals of Geophysics</em>.</p>
Geodetic height changes at proposed IHRF sites estimated from GRACEGRACE-FO data
<p>This data provide information about geodetic heights change used to obtain all results presented in the article "<span>Yadeta S.M., </span><strong><span>Godah W.</span></strong><span>, Szelachowska M., Fotopoulos G., (2023): </span><span> <em>Assessment of temporal variations of orthometric/normal heights at proposed International Height Reference Frame sites using GRACE/GRACE-FO</em>. Survey Review. </span><span><a href="https://doi.org/10.1080/00396265.2023.2293367"><span>https://doi.org/10.1080/00396265.2023.2293367</span></a></span>" </p>
Supporting Information for "Investigation of Hikurangi subduction zone slow slip events using onshore and onshore geodetic data" PhD thesis
<p>The data sets included here are those inverted using the TDEFNODE (McCaffrey et al., 2009) inversion code in the PhD thesis "Investigation of Hikurangi subduction zone slow slip events using onshore and onshore geodetic data" to obtain geodetic slip models of the 2013-2016 and February-July 2019 periods at the Hikurangi subduction zone.</p> <p> </p> <p><em>The 2013-2016 period captured the 2013 Kāpiti and 2014/2015 Manawatū slow slip events (SSEs), in addition to the 2013 Cook Strait, 2013 Lake Grassmere, and 2014 Eketāhuna earthquakes. The data related to this model are:</em></p> <p><strong>campaign_gps_2013.ts</strong><br> -campaign GPS time series<br> -columns: Year East East_sigma North North_sigma Up Up_sigma<br> -input using TDEFNODE command ts1</p> <p><strong>coseismic_displacements_2013_07_21.ds </strong><br> -coseismic displacements for Cook Strait earthquake (Hamling et al., 2014)<br> -columns: Longitude Latitude Disp_East Disp_North Sigma_East Sigma_North Site Disp_Up Sigma_Up Time1 Time2<br> -input using TDEFNODE command ds2</p> <p><strong>coseismic_displacements_2013_08_16.ds </strong><br> -coseismic displacements for Lake Grassmere earthquake (Hamling et al., 2014)<br> -columns: Longitude Latitude Disp_East Disp_North Sigma_East Sigma_North Site Disp_Up Sigma_Up Time1 Time2<br> -input using TDEFNODE command ds2</p> <p><strong>onshore_gnss_kapiti_manawatu_2013_2016.ts</strong><br> -GNSS time series<br> -columns: Year East East_sigma North North_sigma Up Up_sigma<br> -input using TDEFNODE command ts1</p> <p><strong>LOS_coseismic_2013_08_16.is<br> -</strong>coseismic Line of Sight displacements for Lake Grassmere earthquake (Hamling et al., 2014)<br> -convention: negative displacement equivalent to ground moving towards the satellite<br> -columns: Longitude Latitude LineOfSight_disp sigma Unit_x Unit_y Unit_z<br> -input using TDEFNODE command is1</p> <p> </p> <p><em>Data related to the February-July 2019 SSE model are:</em></p> <p><strong>onshore_gnss_east_coast_sse_2019.ts</strong><br> -GNSS time series<br> -columns: Year East East_sigma North North_sigma Up Up_sigma<br> -input using TDEFNODE command ts4</p> <p><strong>seafloor_displacement_gisborne.ts</strong><br> -seafloor pressure time series<br> -convention: positive change equivalent to seafloor uplift<br> -columns: Year East East_sigma North North_sigma Up Up_sigma<br> -input using TDEFNODE command ts4</p> <p><strong>seafloor_displacement_hawkebay.ts</strong><br> -seafloor pressure time series<br> -convention: positive change equivalent to seafloor uplift<br> -columns: Year East East_sigma North North_sigma Up Up_sigma<br> -input using TDEFNODE command ts4</p> <p><strong>LOS_SSE_2019.is</strong><br> -SSE-related Line of Sight displacement<br> -convention: positive displacement equivalent to ground moving away from satellite<br> -columns: Longitude Latitude LineOfSight_disp sigma Unit_x Unit_y Unit_z<br> -input using TDEFNODE command is1</p> <p> </p> <p>The TDEFNODE manual can be found here:<br> https://robmccaffrey.github.io/TDEFNODE/manual/tdefnode_manual.html</p> <p>The header lines in the time series files (.ts) take the site inter-SSE rates from the model of Wallace et al. (2012).</p> <p> </p> <p><em>References</em></p> <p>Hamling, I. J., D’Anastasio, E., Wallace, L. M., Ellis, S., Motagh, M., Samsonov, S., Palmer, N., and Hreinsdóttir, S. (2014). Crustal deformation and stress transfer during a propagating earthquake sequence: The 2013 Cook Strait sequence, central New Zealand. <em>Journal of Geophysical Research: Solid Earth</em>, <strong>119</strong>(7):6080–6092.</p> <p>McCaffrey, R. (2009). Time-dependent inversion of three-component continuous GPS for steady and transient sources in northern Cascadia. <em>Geophysical Research Letters</em>, <strong>36</strong>(L07304).</p> <p>Wallace, L. M., Barnes, P., Beavan, J., Van Dissen, R., Litchfield, N., Mountjoy, J., Langridge, R., Lamarche, G., and Pondard, N. (2012). The kinematics of a transition from subduction to strike-slip: An example from the central New Zealand plate boundary. <em>Journal of Geophysical Research: Solid Earth</em>, <strong>117</strong>(B2).</p>
Published and new Geochronology, Thermochronology, Geodetic, and Earthquake Data from the Fairweather Transform Region
<p>Published and new Geochronology, Thermochronology, Geodetic, and Earthquake Data from the Fairweather Transform Region used in <strong>Benowitz, J., </strong>Lease, R., Hauessler, P., Pavlis, P., Mann, M., Fairweather Transform Orogenesis: 25 million years of Crustal-block vertical extrusion and double indenter tectonics since ca. 3 Ma., for <i>Tectonophysics</i>.</p>
Geodetic model of the March 2021 Thessaly seismic sequence inferred from seismological and InSAR data
<p>A selection of Sentinel-1 (S1) wrapped and unwrapped measurements used in this study (from "a" to "u" files in tiff format as indicated in the word file attached). S1 data were processed by using our own internally developed InSAR processing chain.<br> <br> Earthquakes data locations.</p> <p><br> </p> <p> </p>
Nankai Trough FakeQuakes geodetic and waveform data
<p>Supplementary data for the master thesis "A Study on Tsunami Damage Prediction Based on Pre-computed Scenarios<strong>" </strong>by Louise A. Hirao-Vermare, master's student at Tohoku University.<br> "nagahama_geodetic_data.tar.gz" gathers synthetic geodetic data, i.e., ground displacements, at several inland stations. "nagahama_wave_data.tar.gz" gathers synthetic wave elevations at several offshore gauges. <br> Not all data are used in the master thesis. <br> File formats are explained in READ_ME.txt. The location of the observation stations are provided in the .klm files.</p>
Data files for 'Tan et al., (2023). Structural heterogeneity-controlled rupture process of the 2021 Mw 7.1 Fukushima, Japan earthquake revealed by joint inversion of seismic and geodetic data'
<p>slip model.dat: rupture model of the 2021 Mw 7.1 Fukushima earthquake</p> <p>In 'slip model.dat', each row contains the moment rate function of each sub-fault. The numbers of the sub-faults are given in the first two columns.</p>
Supporting data for "Geodetic monitoring of elastic and inelastic deformation in compacting reservoirs due to subsurface operations"
<p>Supporting data for "Geodetic monitoring of elastic and inelastic deformation in compacting reservoirs due to subsurface operations" </p> <p>Yuexin Li1*, Mateo Acosta1, Krittanon Sirorattanakul1, Stephen Bourne2, and Jean-Philippe Avouac1</p> <p>1 Division of Geological and Planetary Sciences, California Institute of Technology, USA<br>2 Shell Global Solutions International, Amsterdam, The Netherlands</p> <p>Nov 2024<br>Contact: Yuexin Li (yuexinli@berkeley.edu, yuexinli.sar@gmail.com)</p> <p> </p> <p>This study was supported by the NSF/Industry-University Collaborative Research Center 'Geomechanics and Mitigation of Geohazards' (National Science Foundation award # 1822214), and the Enhancement Project GMG-3 funded by Nederlandse Aardolie Maatschappij (NAM). M.A acknowledges funding from the Swiss National Science Foundation through grant P2ELP2195127 and from Caltech’s Resnick sustainability institute. We would like to acknowledge NAM for granting the access and permitting to present the InSAR and GNSS data.</p>
Data for "Constraints on absolute chamber volume from geodetic measurements: Trapdoor faulting in the Galapagos"
<p>SNdif.mat: InSAR data covering the April 2005 trapdoor faulting event.</p> <p>SN_GPS.mat: GPS data of the April 2005 trapdoor faulting event.</p> <p>Both datasets were prepared and provided by Jonsson [2009]</p>
Cascading rupture process of the 2021 Maduo, China earthquake revealed by the joint inversion of seismic and geodetic data
<p>The coseismic Sentinel-1 line-of-sight (LOS) displacements, strong-motion and teleseismic waveforms used in the joint inversion of the source rupture process for the 2021 Maduo, China earthquake are included in this repository.</p>
Very Long Baseline Interferometry (VLBI) National Geodetic Survey (NGS) card data from NASA CDDIS
Very Long Baseline Interferometry (VLBI) ASCII files in the NGS card format. Very Long Baseline Interferometry (VLBI) auxiliary ASCII files provided by the International VLBI Service for Geodesy and Astrometry (IVS) include schedules, notes, and session log files.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.