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26 results for “Surface deformation”
Calibrated Earthquake Relocations from the TexNet Catalog (2017–2022) and Vertical Surface Deformation (2016–2022)
<p>This repository contains the relocated earthquake catalog for the Southern Delaware Basin, as presented in the manuscript titled "<em><strong>Insights into Spatiotemporal Evolution of Induced Earthquakes in the Southern Delaware Basin Using Calibrated Relocations from the TexNet Catalog (2017-2022)</strong>".</em></p> <h3>Citations:</h3> <p>Asiye Aziz Zanjani, Heather R. DeShon, Vamshi Karanam, Alexandros Savvaidis; <strong>Insights into Temporal Evolution of Induced Earthquakes in the Southern Delaware Basin Using Calibrated Relocations <em>from the TexNet Catalog (2017-2022</em>) (2025)</strong>. <em>Earth and Space Science, 12 (6), e2024EA004027. <a title="https://doi.org/10.1029/2024EA004027" href="https://doi.org/10.1029/2024EA004027"><strong>https://doi.org/10.1029/2024EA004027</strong></a></em></p> <p>The earthquake relocations were conducted using the Hypocentroidal Decomposition technique with the <strong>open-source MLOC code</strong>, achieving enhanced spatial resolution for over 5,000 events from the TexNet catalog. The relocated catalog includes critical hypocentral parameters—latitude, longitude, depth—as well as origin time, associated uncertainties, and magnitude for each event.</p> <p>This dataset is an essential resource for analyzing the spatiotemporal patterns of induced seismicity associated with anthropogenic activities, such as shallow fluid injection, in the Southern Delaware Basin following the operation of TexNet in 2017. It is suitable for use in seismic hazard assessments, modeling studies, and comparisons with other induced seismicity datasets. Additional data produced during this research includes vertical surface deformation measurements from 2016 through the end of 2022.</p> <p>The repository also contains data referenced in the manuscript’s “Data Availability Statement” and “Open Research” sections. </p> <p>List of files attached to this repository:</p> <ul> <li><strong>catalog.xls</strong>: Primary earthquake relocated catalog developed in this study</li> <li><strong>2016_2022_deformation.csv</strong>: Vertical displacement data (2016–2018) developed in this study</li> <li><strong>2019_2022_deformation.csv</strong>: Vertical displacement data (2016–2022) developed in this study</li> <li><strong>post-2017-injection.xlsx</strong>: Injection data from the Railroad Commission of Texas (<a href="https://www.rrc.texas.gov">source</a>)</li> <li><strong>Hydrofracking-post2017.xlsx</strong>: Hydrofracking well data from FracFocus (<a href="https://fracfocus.org">source</a>)</li> <li><strong>GrowClust-common.xls</strong>: 2-D GrowClust catalog for supplemental information (<a href="https://hirescatalog.texnet.beg.utexas.edu/">source</a>), https://doi.org/10.15781/76hj-ed46</li> <li><strong>TexNet-Catalog</strong>: Initial TexNet catalog's origin and phase data, https://doi.org/10.7914/SN/TX</li> </ul>
Surface deformation of the Mw 6.4 and Mw 7.1 Ridgecrest earthquakes measured from subpixel correlation of Copernicus Sentinel-2 optical images
<p>Surface deformation of the Mw 6.4 and Mw 7.1 Ridgecrest earthquakes measured from subpixel correlation of Copernicus Sentinel-2 optical images </p>
→ Fig. 9. Antiarchan fish Bothriolepis leptocheira jeremejevi (Rohon, 1900), Sosnogorsk locality, Sosnogorsk Formation, lowermost Famennian, anterior median dorsal (A–G) and posterior median dorsal (H–M) plates of the trunk armour. A. IG KSC 155/5 in dorsal (A1) and visceral (A2) views. B. IG KSC 155/108 in dorsal (B1) and visceral (B2) views. C. IG KSC 155/97 in dorsal view. D. IG KSC 155/113 in dorsal (D1) and visceral (D2) views. E. IG KSC 155/140 in dorsal (E1) and visceral (E2) views. F. Impression of the dorsal surface of IG KSC 155/42. G. IG KSC 155/44 in dorsal view. H. Fragment of IG KSC 155/7 in dorsal view. I. IG KSC 155/1 in dorsal (I1) and visceral (I2) views. J. IG KSC 155/71 in dorsal view. K. Slightly deformed IG KSC 155/70 in dorsal (K1) and visceral (K2) views. L. IG KSC 155/158 in dorsal view. M. IG KSC 155/157 in dorsal (M1) and visceral (M2) views. Abbreviations: ADL, anterior dorso-lateral plate; alr, postlevator thickening; AMD, anterior median dorsal plate; cf.ADL, cf.AMD, and cf.MxL, area overlapping ADL, AMD or MxL respectively; cr.tp, posterior transversal internal crest; dlg1 and dlg2, anterior and posterior oblique dorsal sensory line groove; dma, tergal angle; dmr, dorsal median ridge; f.retr, levator fossa; grm, ventral median groove; l, lateral corner; mvr, median ventral ridge; MxL, mixilateral plate; npn, postnuchal notch; oa.ADL, oa.MxL and oa.PMD, area overlapped by ADL, MxL or PMD respectively; pa, posterior corner; pma, posterior marginal area; PMD, posterior median dorsal plate; pr.p, posterior process of AMD; pr.pl, external postlevator process; prv2, posterior ventral process of dorsal wall of trunk armour; pt1 and pt2, anterior and posterior ventral pit; pua, posterior unornamented area of PMD; rf, "round fossula"; sna, supranuchal area; tb, ventral tuberosity. in A new assessment of the Late Devonian antiarchan fish Bothriolepis leptocheira from South Timan (Russia) and the biotic crisis near the Frasnian-Famennian boundary
→ Fig. 9. Antiarchan fish Bothriolepis leptocheira jeremejevi (Rohon, 1900), Sosnogorsk locality, Sosnogorsk Formation, lowermost Famennian, anterior median dorsal (A–G) and posterior median dorsal (H–M) plates of the trunk armour. A. IG KSC 155/5 in dorsal (A1) and visceral (A2) views. B. IG KSC 155/108 in dorsal (B1) and visceral (B2) views. C. IG KSC 155/97 in dorsal view. D. IG KSC 155/113 in dorsal (D1) and visceral (D2) views. E. IG KSC 155/140 in dorsal (E1) and visceral (E2) views. F. Impression of the dorsal surface of IG KSC 155/42. G. IG KSC 155/44 in dorsal view. H. Fragment of IG KSC 155/7 in dorsal view. I. IG KSC 155/1 in dorsal (I1) and visceral (I2) views. J. IG KSC 155/71 in dorsal view. K. Slightly deformed IG KSC 155/70 in dorsal (K1) and visceral (K2) views. L. IG KSC 155/158 in dorsal view. M. IG KSC 155/157 in dorsal (M1) and visceral (M2) views. Abbreviations: ADL, anterior dorso-lateral plate; alr, postlevator thickening; AMD, anterior median dorsal plate; cf.ADL, cf.AMD, and cf.MxL, area overlapping ADL, AMD or MxL respectively; cr.tp, posterior transversal internal crest; dlg1 and dlg2, anterior and posterior oblique dorsal sensory line groove; dma, tergal angle; dmr, dorsal median ridge; f.retr, levator fossa; grm, ventral median groove; l, lateral corner; mvr, median ventral ridge; MxL, mixilateral plate; npn, postnuchal notch; oa.ADL, oa.MxL and oa.PMD, area overlapped by ADL, MxL or PMD respectively; pa, posterior corner; pma, posterior marginal area; PMD, posterior median dorsal plate; pr.p, posterior process of AMD; pr.pl, external postlevator process; prv2, posterior ventral process of dorsal wall of trunk armour; pt1 and pt2, anterior and posterior ventral pit; pua, posterior unornamented area of PMD; rf, "round fossula"; sna, supranuchal area; tb, ventral tuberosity.
The surface deformation induced by thermal expansion of bedrock, based on the the uniform elastic sphere model
<p>The surface deformation induced by thermal expansion of bedrock(TEB), based on the the uniform elastic sphere model in the manuscript submitted to JGR: Solid Earth, including:</p> <p>1. Input data of TEB model:</p> <p><strong>Spherical harmonics coefficients of land surface temperature:</strong> Cosine terms (detrended); Sine terms (detrended) </p> <p>(The coefficients are based on temperature data provided by Physical Sciences Laboratory (PSL) of the National Oceanic and Atmospheric Administration; <u>https://psl.noaa.gov/data/gridded/data.cpc.globaltemp.html</u>)</p> <p>2. Output data of TEB model: </p> <p><strong>The 3-dimensional TEB displacements </strong> <strong>on the 0.5</strong><strong>°×</strong><strong>0.5</strong><strong>°</strong><strong>global grid:</strong> annual variations of East, North, Up components</p>
High resolution deformation data from the surface of a Nickel-based superalloy: Coarse precipitates
<p>High resolution digital image correlation (HRDIC) and electron backscattered diffraction (EBSD) data provided that quantifies the deformation on the surface of Nickel-based superalloy with coarse gamma prime precipitates (250 nm diameter) after 2% strain in tension.</p>
High resolution deformation data from the surface of a Nickel-based superalloy: Fine precipitates
<p>High resolution digital image correlation (HRDIC) and electron backscattered diffraction (EBSD) data provided that quantifies the deformation on the surface of Nickel-based superalloy with fine gamma prime precipitates (70 nm diameter) after 2% strain in tension.</p>
Present-day surface deformation of Sicily: Insights from Sentinel-1 data processed by a PS-InSAR approach
<p>The directory DATASET.zip provides PS-InSAR data used in Henriquet et al., (2022). The data set contains for each Sentinel-1 track (44, 117, 22, 124) the mean PS velocities along the LOS, before (ps_mean_v.xy.v-dos) and after (ps_mean_v-dos_adjusted2GPS.xy) their adjustment to the 3D-GNSS velocity field, as well as the disparities of the PS velocities (ps_mean_disp.xy). The data set also includes the East- and Up-component of the reconstructed mean PS velocity field (East.grd and Up.grd) used in the Figures 7 to 12 in the paper.</p>
Deep, shallow and surface fault-zone deformation during and after the 2021 Mw7.4 Maduo, Qinghai, earthquake illuminates fault structural immaturity
<p>These datasets include the postseismic InSAR time series on ascending and descending tracks and the relocated aftershocks (Wang et al., 2021) of the 2021 Maduo earthquake. The details can be found in our JGR paper.</p> <p>Reference</p> <p>Wang, W., Fang, L., Wu, J., Tu, H., Chen, L., Lai, G., & Zhang, L. (2021). Aftershock sequence relocation of the 2021 Ms7. 4 Maduo earthquake, Qinghai, China. Science China Earth Sciences, 64(8), 1371-1380.</p>
InSAR time-series and FEM Model of the Post-seismic Surface Deformation following the 2013 Baluchistan Earthquake
<p>Subduction zone accretionary prisms are commonly modeled as elastic structures where permanent deformation is accommodated by faulting and folding of otherwise elastic materials, yet accretionary prisms may exhibit other deformation styles over relatively short time scales. In this study, we use 6.5-year (2014-2021) Sentinel-1 InSAR time-series of post-seismic deformation in the Makran accretionary prism of southeast Pakistan to characterize non-linear viscoelastic deformation within an active accretionary prism on short timescales (months to years). We constructed a series of 3-D finite-element models of the Makran subduction zone, including an accretionary prism, and constrained the elastic thickness of the upper wedge and the flow-law parameters (power-law exponent, activation enthalpy, and pre-exponential constant) of the lower wedge through forward model fits to the InSAR time-series. Our results show that the prism is elastically thin (8-12 km) and the non-linear viscoelastic relaxation of the deep portions of the prism alone can sufficiently explain the post-seismic surface deformation. Our best fitting flow-law parameters (<em>n</em> = 3.76±0.39, <em>Q</em> = 82.2±37.73 kJ mol<sup>-1</sup>, and <em>A</em> = 10<sup>-3.36±4.69</sup>) are consistent with triggering of low temperature dislocation creep within fluid-saturated siliciclastic rocks. We believe that the fluids necessary for this weakening originate from sedimentary underplating and/or the presence the hydrocarbons. The presence of power-law rheology within the lower wedge impacts the estimated plate coupling and the stress state in the subduction system, with respect to the conventional elastic wedge model, and hence need to be considered in future earthquake cycle models.</p>
Dynamics of Surface Deformation Induced By Dikes and Cone Sheets in a Cohesive Brittle Coulomb Crust Data
<p>Two files containing raw surface monitoring data from two experimental series and one file containing the analysis of the processed surface monitoring data.<br> <br> </p>
Surface rupture data and InSAR deformation of the March 24, 2021 Mw5.3 Baicheng earthquake, Xinjiang, China
<p>The co-seismic surface rupture data and map, range offset measurements, and the slip model of InSAR used to study the 2021 Baicheng (China) earthquake are included in this repository.</p>
Analytical method for reconstructing the stress on a spherical particle from its surface deformation
<p>Supplemental data for the following manuscript: Lea Johanna Krüger, Michael te Vrugt, Stephan Bröker, Bernhard Wallmeyer, Timo Betz, Raphael Wittkowski, "Analytical method for reconstructing the stress on a spherical particle from its surface deformation".</p><p>Bead1_ExperimentalData.tif and Bead2_ExperimentalData.tif contain the measured bead shapes as TIF files. Bead1_ExperimentalData.txt and Bead2_ExperimentalData.txt contain the measured bead shapes as point clouds. Bead1_SphericalHarmonicsExpansionCoefficients.txt and Bead2_SphericalHarmonicsExpansionCoefficients.txt contain expansions of the bead shapes into spherical harmonics.</p>
Data and code from: Sub-surface deformation of individual fingerprint ridges during tactile interactions
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Data for "Coherence-Guided InSAR Deformation Analysis in the Presence of Ongoing Land Surface Change in the Imperial Valley, California"
<p>Interferometric Synthetic Aperture Radar (InSAR) observations of the surface velocity field in the Imperial Valley, California, over the period of 2015-2019, derived from the European Satellite Agency’s (ESA) Sentinel-1a/b satellite imagery.</p> <p>This dataset includes the following:</p> <p>1. Downsampled results in geographic coordinates (a grid spacing of 2”). The average (secular) velocity (in mm/yr) is estimated along the satellite line-of-sight (LOS) directions from descending (D173) and ascending (A166) tracks over the spatial extent covering the Imperial Valley (S/N/W/E: 32.4/33.6/-116.2/-115). GeoTIFF files contain velocity values or color-coded RGB values using the Matplotlib colormap RdBu_r (ranging from -25 to 25 mm/yr). Masked pixels are assigned with NaN values.</p> <p>2. Original high-resolution results processed in radar coordinates (~28 m in range and ~42 m in azimuth). HDF5 files contain matrices of the same size for the longitude, latitude, LOS secular velocity, and LOS residual displacements at each ground pixel from both tracks. The temporal error of displacement time series at each pixel (in mm) is represented by the root-mean-square residual of data fits to a linear trend. Masked pixels are assigned with NaN values.</p>
Coupled lithospheric deformation in the Qinling Orogen, central China: Insights from seismic reflection and surface-wave tomography
<p><strong>Data of geochronology of intrusive plutons and selected zircon Hf values shown in Figure S1 and the references cited</strong></p>
Three-Dimensional Surface Deformation Field Related to the 2017 North Korea Nuclear Test
<p>Three-dimensional (3D) surface deformation field was retrieved by using the two ALOS PALSAR-2 stripmapinterferometric pairs that acquired from the ascending (20170829_20170912) and descending (20170831_20170928) orbits. For this, the ascending and descending LOS and AT deformations were created from the pairs by the multi-kernel offset tracking method, and then 3D deformation field was retrieved from the ascending and descending LOS and AT deformations. </p> <p>For the 3D deformation field, the unit is centimeter and the coordinate system is geodetic with the WGS84 ellipsoid.</p>
Surface Deformations from Glacial Isostatic Adjustment Models with Laterally Homogeneous, Compressible Earth Structure
<p>The zipped file contains global 1-degree grid files of four different surface deformation parameters:</p> <ul> <li>Horizontal velocity, North component (vnorth), in mm/a</li> <li>Horizontal velocity, East component (veast), in mm/a</li> <li>Vertical velocity (vup), in mm/a</li> <li>Geoid change (dgeoid), in mm/a</li> </ul> <p>calculated from a set of 26 different glacial isostatic adjustment models applying 10 different radially varying (=layered) earth structures and 3 different global ice models.</p> <p>The different earth structures and the available combinations with ice models can be found in the readme.pdf.</p> <p>File naming is simply {ice model}_{earth model}_{parameter}.grd. For example, anu-ice_f72_vup.grd is the global vertical velocity grid file calculated with a GIA model with ANU-ICE ice history and 60 km lithospheric thickness, 4E20 Pa s upper mantle viscosity and 2E21 Pa s lower mantle viscosity. Grid files (NetCDF format) were generated with GMT6 (Wessel et al., 2019), thus can be directly used.</p> <p>Ice thickness histories of ICE-6G_C (Argus et al., 20214; Peltier et al., 2015) and ICE-7G_NA (Roy & Peltier, 2017) were downloaded from W. R. Peltier’s data website at the University of Toronto, Canada: <a href="https://www.atmosp.physics.utoronto.ca/~peltier/data.php">https://www.atmosp.physics.utoronto.ca/~peltier/data.php</a></p> <p>Note that the velocity field of ICE-6G_C(VM5a) can be compared to the one available from W. R. Peltier’s data website. The files provided here are not a substitute for the ones by W. R. Peltier and colleagues! Analyzing the difference between the files from this work and the ones available on the data website can help getting an error estimate from the two GIA model implementations (see further below). The user will find minor differences in the uplift component but larger ones in far field areas of the horizontal components.</p> <p>ICE-7G_NA(VM7) results are added as complement for interested users. However, note that ICE-7G_NA contains ice thickness history modifications in North America only and a fully global re-optimization of the ice thickness is warranted. Hence, excessive use and interpretation of these grid files, especially on global scale, should be avoided.</p> <p>ANU-ICE is a global 1-degree ice thickness model merged from several regional models (Lambeck, 1995; Fleming & Lambeck, 2004; Lambeck et al., 2010; 2014; 2017) kindly provided by Anthony Lambert and Kurt Lambeck, ANU, Canberra, Australia. The regional models contain differing spatial and temporal resolutions that were unified to fit the global 1-degree spatial resolution at mainly common time steps (500–1000 years). The Antarctic Ice Sheet part contains changes in the last time steps, thus some larger changes in the velocities can be found there.</p> <p>The software ICEAGE (Kaufmann, 2004) is used for calculating the grids, which applies the viscoelastic normal-mode method (Peltier, 1974; Wu, 1978). The sea-level equation is solved in a pseudo-spectral approach (Mitrovica et al., 1994; Mitrovica & Milne, 1998) in an iterative procedure in the spectral domain. See further details in Kaufmann and Lambeck (2000; 2002). The spherical harmonic expansion in the spectral domain is truncated at degree 192, which corresponds to ~1° spatial resolution. The models are spherically symmetric (1D), compressible, with Maxwell-viscoelasticity, rotational feedback, and time-dependent coastlines. The Earth’s core is, as assumed to be inviscid, incorporated as lower boundary condition. Rheological parameters such as depth-dependent density, Young’s modulus, etc., are taken from PREM (Preliminary Reference Earth Model; Dziewonski & Anderson, 1981).</p> <p><strong>Acknowledgments</strong></p> <p>HS would like to thank Jeff Freymueller for discussions on model selection.</p> <p><strong>References</strong></p> <p>Argus, D. F., Peltier, W., Drummond, R., Moore, A.W. 2014. The Antarctica component of postglacial rebound model ICE-6G_C (VM5a) based on GPS positioning, exposure age dating of ice thicknesses, and relative sea level histories. Geophysical Journal International 198, 537–563, doi:10.1093/gji/ggu140.</p> <p>Dziewonski, A. M., Anderson, D. L. 1981. Preliminary reference Earth model. Physics of the Earth and Planetary Interiors 25, 297–356, doi:10.1016/0031-9201(81)90046-7.</p> <p>Fleming, K., Lambeck, K. 2004. Constraints on the Greenland ice sheet since the Last Glacial Maximum from sea-level observations and glacial-rebound models. Quaternary Science Reviews 23, 1053–1077, doi:10.1016/j.quascirev.2003.11.001.</p> <p>Kaufmann, G. 2004. Program Package ICEAGE, Version 2004. Manuscript. Institut für Geophysik der Universität Göttingen.</p> <p>Kaufmann, G., Lambeck, K., 2000. Mantle dynamics, postglacial rebound and the radial viscosity profile. Physics of the Earth and Planetary Interiors 121, 301–324, doi:10.1016/S0031-9201(00)00174-6.</p> <p>Kaufmann, G., Lambeck, K., 2002. Glacial isostatic adjustment and the radial viscosity profile from inverse modeling. Journal of Geophysical Research Solid Earth 107, ETG 5-1-ETG 5-15, doi:10.1029/2001JB000941.</p> <p>Lambeck, K. 1995. Late Devensian and Holocene shorelines of the British Isles and North Sea from models of glacio-hydro-isostatic rebound. Journal of the Geological Society London 152, 437–448, doi:10.1144/gsjgs.152.3.0437.</p> <p>Lambeck, K., Purcell, A., Zhao, J., Svensson, N.-O. 2010. The Scandinavian ice sheet: from MIS 4 to the end of the last glacial maximum. Boreas 39 (2), 410–435, doi:10.1111/j.1502-3885.2010.00140.x.</p> <p>Lambeck, K., Rouby, H., Purcell, A., Sun, Y., Sambridge, M. 2014. Sea level and global ice volumes from the Last Glacial Maximum to the Holocene. Proceedings of the National Academy of Sciences of the United States of America 111 (43), 15296–15303, doi:10.1073/pnas.1411762111.</p> <p>Lambeck, K., Purcell, A., Zhao, J. 2017. The North American Late Wisconsin ice sheet and mantle viscosity from glacial rebound analyses. Quaternary Science Reviews 158, 172–210, doi:10.1016/j.quascirev.2016.11.033.</p> <p>Mitrovica, J. X., Davis, J. L., Shapiro, I. I. 1994. A spectral formalism for computing three–dimensional deformations due to surface loads: 1. Theory. Journal of Geophysical Research Solid Earth 99(B4), 7057–7073, doi:10.1029/93JB03128.</p> <p>Mitrovica, J. X., Milne, G. A. 1998. Glaciation-induced perturbations in the Earth’s rotation: a new appraisal. Journal of Geophysical Research Solid Earth 103, 985–1005, doi:10.1029/97JB02121.</p> <p>Peltier, W. R. 1974. The impulse response of a Maxwell Earth. Reviews of Geophysics and Space Physics 12(4), 649–669, doi:10.1029/RG012i004p00649.</p> <p>Peltier, W., Argus, D., Drummond, R. 2015. Space geodesy constrains ice age terminal deglaciation: The global ICE-6G_C (VM5a) model. Journal of Geophysical Research Solid Earth 120, 450–487, doi:10.1002/2014JB011176.</p> <p>Roy, K., Peltier, W. R. 2017. Space-geodetic and water level gauge constraints on continental uplift and tilting over North America: regional convergence of the ICE-6G_C (VM5a/VM6) models. Geophysical Journal International 210(2), 1115-1142, doi:10.1093/gji/ggx156.</p> <p>Wessel, P., Luis, J. F., Uieda, L., Scharroo, R., Wobbe, F., Smith, W. H. F., Tian, D. 2019. The Generic Mapping Tools version 6. Geochemistry, Geophysics, Geosystems 20, 5556–5564, doi:10.1029/2019GC008515.</p> <p>Wu P. 1978. The response of a Maxwell earth to applied surface mass loads: glacial isostatic adjustment. MSc thesis, University of Toronto, Toronto, Ontario, Canada.</p>
A Comprehensive Dataset of Surface Deformation Satellite Maps of The Valley of Toluca, Mexico
<p>A dataset of 1121 ground deformation maps of the Toluca Valley (VT) in Mexico is presented. The given deformation maps cover the VT ground evolution over eight years, from October 2014 to December 2022.</p><p>The VT is located within the State of Mexico between the coordinates of 19°03' to 19°35' north latitude and 99°19' to 99°54' west latitude. The highest altitude point of the VT is the volcano "Nevado de Toluca or Xinantécatl" which is 4,340 meters above sea level. In comparison, the rest of the valley has an average elevation of 2640 meters above sea level. The soil of the VT is mainly composed of Andosols, Feozems, Vertisols, Luvisols, and Cambisols.</p><p>For generating the deformation maps, 240 radar images obtained by the Sentinel 1-A and Sentinel 1-B satellites were used. From these 240 radar images, 2169 pairs of images were formed with a temporal difference of 1, 3, 6, and 12 months. The Differential Interferometric Synthetic Aperture Radar technique was applied to these pairs using SNAP software, resulting in 2169 deformation maps in BEAM-DIMAP format. However, due to limited storage space, only 1121 maps with a coherence greater than 0.299 are presented. Complimentary, a CSV file with the deformation map statistics is also provided.</p>
Surface deformation associated with fractures near the 2019 Ridgecrest earthquake sequence
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High resolution deformation data from the surface of a Nickel-based alloy: Solid solution
<p>High resolution digital image correlation (HRDIC) and electron backscattered diffraction (EBSD) data provided that quantifies the deformation on the surface of a solid solution Nickel-based alloy with no gamma prime precipitates after 2% strain in tension.</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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.