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27 results for “glacier velocity”
Data supporting 'Empirical correction of systematic orthorectification error in Sentinel-2 velocity fields for Greenlandic outlet glaciers'
<p><strong>Note: An updated dataset covering the majority of Greenland's marine-terminating glaciers is available as part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) project through the National Snow and Ice Data Center (NSIDC) at <a href="https://doi.org/10.5067/B28FM2QVVYWY">https://doi.org/10.5067/B28FM2QVVYWY</a>. </strong></p> <p>Data supporting the paper:</p> <blockquote> <p>Chudley, T. R., Howat, I. M., Yadav, B. N., & Noh, M. J. (2022). Empirical correction of systematic orthorectification error in Sentinel-2 velocity fields for Greenlandic outlet glaciers. <em>The Cryosphere. </em>16, 2629–2642, https://doi.org/10.5194/tc-16-2629-2022</p> </blockquote> <p>Dataset consists of four netCDF files containing stacked Sentinel-2 velocity data of four Greenlandic outlet glaciers (Helheim Glacier, Jakobshavn Isbræ, Store Glacier, and Kangerlussuaq) between 2017 and 2021. Velocity data are derived and corrected following the methods outlined in Chudley <em>et al.</em> (2022). </p> <p>NetCDF files are created by, and tested to be readable by, Python's xarray package.</p> <p>The dimensions of the netCDF file are as follows:</p> <ul> <li><strong>X</strong> - <em>x </em>coordinates in NSDIC Sea Ice Polar Stereographic North (EPSG:3413).</li> <li><strong>Y</strong> - <em>y</em> coordinates in NSDIC Sea Ice Polar Stereographic North (EPSG:3413).</li> <li><strong>time</strong> - temporal midpoint of velocity field.</li> </ul> <p>The variables of the netCDF file are as follows:</p> <ul> <li><strong>dmag</strong> - the absolute magnitude of the velocity, in metres per day.</li> <li><strong>dx</strong> - the velocity in the <em>x</em> direction, in metres per day.</li> <li><strong>dy</strong> - the velocity in the <em>y</em> direction, in metres per day.</li> <li><strong>date1</strong> - the date and time of the first scene acquisition.</li> <li><strong>date2</strong> - the date and time of the second scene acquisition.</li> <li><strong>baseline</strong> - the temporal baseline, in days, between scene acquisitions.</li> <li><strong>orbit_pair</strong> - the combination of orbital pathways in the string format 'RXXX_RYYY', where XXX is relative orbit number of the first scene and YYY the relative orbit number of the second scene.</li> <li><strong>mag_rmse</strong> - the root mean square error of the absolute velocity of the off-ice area. </li> <li><strong>dx_mean</strong> - the mean velocity of the off-ice area in the <em>x</em> direction.</li> <li><strong>dx_sd</strong> - the standard deviation of the velocity of the off-ice area in the <em>x</em> direction.</li> <li><strong>dy_mean</strong> - the mean velocity of the off-ice area in the <em>x</em> direction.</li> <li><strong>dy_sd</strong> - the standard deviation of the velocity of the off-ice area in the <em>y</em> direction.</li> </ul>
Dataset and codes for 'Climatic control on seasonal variations of glacier surface velocity'
<p><strong>This repository contains the codes and processed data used to retrieve 10-day changes in glacier surface velocity over the Western Pamir.</strong></p> <p>The supp_CODES.zip contains all details and codes to use COSI-CORR (<a href="http://www.tectonics.caltech.edu/slip_history/spot_coseis/">http://www.tectonics.caltech.edu/slip_history/spot_coseis/</a>) to process a large batch of satellite images. The images can be downloaded directly via <a href="https://earthexplorer.usgs.gov/">https://earthexplorer.usgs.gov/</a> or <a href="https://scihub.copernicus.eu/">https://scihub.copernicus.eu</a>. Please read the Methods and Data section of the associated manuscript for details.</p> <p> </p> <p>The Matrix_velocities.zip contains, for each of the 48 investigated glaciers, the DEM, X, Y (NANNI_2022_supp_glacier_centreline_DEM_XY_1px_30m_1.txt) as well as a matrix of n*m with m the distance along flow and n the number of time step over which the velocity is calculated (NANNI_2022_supp_glacier_centreline_vel_matrix_1px_30m_1.txt), ans the associated figure that show the multi year velocity changes together with the one year average and the along centreline profiles. An example is shown in the two figures for glacier 48 in the main repository.</p> <p> </p> <p>The NANNI_2022_supp_glacier_characteristics file contains the glacier characteristics (48*8), as shown in the associated figures.</p> <p> </p> <p>The NANNI_2022_supp_pickedpoints_migration_AUTUMN/SPRING contains the automatically picked points for the onset of the acceleration in Spring and Autmun for each glacier. The headers contains the information, and the files contains is shown in the associated figure.</p> <p>the temperature profiles used to calculate the Iso 0C are in NANNI_2022_supp_temp_perday_fedchenko_2400m</p> <p>The position of each 48 glacier is shown in the associated figure.</p> <p> </p> <p>You can also find the processed velocity fields (velocity magnitude) under the different path an row: p151r33.zip and p152r33.zip for Landsat8, T42SYJ.zip and T43SBD.zip for Sentinel 2. In these folder you will a find a .tif file names similar to:</p> <p><em>Working_cosicorr_windows_FCorr_16days_p152r33_159_175_AB_1101110_Filtered_correlations_p152r33_filtered_abs.tif</em></p> <p>The name of the files gives information about the time span used (16days), the path and raw (p152r33), the data of the slave in DOY from 2013 (159) and of the master (175).</p> <p>The Statistics.zip file contains for each path and row the associated DEM, glacier mask (RGI), median magnitude (ABS), median NS displacement (NS), median EW displacemnt (EW), with the associated median absolute deviation (MAD). The files containing 'bflt' corresponds to the values computed before the filtering procedure, and the one without, after the filtering procedure. </p> <p>The .tif files are not georeferenced, but are all projected on the same grid with a 30m square pixel size on a UTM 33 42N projection.</p> <p> </p> <p> </p> <p>Please contact me for any question.</p> <p> </p> <div class="notranslate"> </div>
MEaSUREs ITS_LIVE Sentinel-1 Image-Pair Glacier and Ice Sheet Surface Velocities: Version 2 (Greenland Sample Products)
<p>We provide 21 sample products of MEaSUREs ITS_LIVE Sentinel-1 Image-Pair Glacier and Ice Sheet Surface Velocities: Version 2 in three test regions of Greenland Ice Sheet. The full archive of version 2 ITS_LIVE products (including image pair maps, data cubes and mosaics) from Sentinel-1 as well as other optical sensors (Landsat-4/5/6/7/8 and Sentinel-2) can be found at the ITS_LIVE project website: <a href="https://its-live.jpl.nasa.gov/">https://its-live.jpl.nasa.gov</a>.</p> <p><strong>Sensor</strong>: Sentinel-1A/B</p> <p><strong>Processor</strong>: <a href="https://github.com/isce-framework/isce2">ISCE</a>v2.4.1 (topsApp -> <a href="https://github.com/leiyangleon/Geogrid">Geogrid</a>v1.4.0 -> <a href="https://github.com/nasa-jpl/autoRIFT">autoRIFT</a>v1.4.0)</p> <p><strong>Project</strong>: NASA MEaSUREs project <a href="https://its-live.jpl.nasa.gov">ITS_LIVE</a></p> <p><strong>Region 1</strong> (69.13N, 50.88W; Jakobshavn Isbræ Glacier): 7 ascending image pairs</p> <p><strong>Region 2</strong> (77.61N, 42.79W; central north of interior Greenland): 3 ascending image pairs</p> <p><strong>Region 3</strong> (72.48N, 35.87W; central south of interior Greenland): 10 descending image pairs and 1 ascending image pair</p> <p>This serves as a supplementary dataset for the companion journal article submitted to Earth System Science Data (to appear).</p> <p> </p> <p><strong>Acknowledgement</strong>: This effort was funded by the NASA MEaSUREs program in contribution to the Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) project (<a href="https://its-live.jpl.nasa.gov/">https://its-live.jpl.nasa.gov/</a>) and through Alex Gardner’s participation in the NASA NISAR Science Team.</p>
Model output from Inverting ice surface elevation and velocity for bed topography and slipperiness beneath Thwaites Glacier
<p>This model output dataset accompanies the draft paper 'Inverting ice surface elevation and velocity for bed topography and slipperiness beneath Thwaites Glacier'.</p>
Central and Eastern Himalaya glacier velocities 2017-2019 (Sentinel 2)
<p> </p> <p>This dataset contains the median glacier surface velocity for the Central and Eastern Himalaya glacier velocities 2017-2019 (Sentinel 2). The velocities have been obtained by feature-tracking of November Sentinel 2 images spaced 1 year apart.</p> <p>The folder contains the following fields at 80 m resolution in GeoTiff format:</p> <ul> <li>the velocity magnitude 'vel' (meters per year)</li> <li>the x/y velocity components x_vel/y_vel (meters per year)</li> <li>the associated errors err, x_err, y_err (meters per year)</li> <li>the median absolute deviation of all the merged velocities 'MAD' (meters per year)</li> <li>the number of image pairs that have been merged in the median</li> </ul> <p>I recommend filtering data with error larger than 5 m/yr.</p> <p> </p> <table> <caption>Metadata Properties</caption> <tbody> <tr> <td>CRS</td> <td>EPSG:32645 - WGS 84 / UTM zone 45N - Projected</td> </tr> <tr> <td>Extent</td> <td>9425.6070999999992637,3045085.1858000000938773 : 883803.9936000000452623,3368628.0986000001430511</td> </tr> <tr> <td>Unit</td> <td>meters</td> </tr> <tr> <td>Width</td> <td>11192</td> </tr> <tr> <td>Height</td> <td>3981</td> </tr> <tr> <td>Data type</td> <td>Float32 - Thirty two bit floating point</td> </tr> </tbody> </table> <p> </p>
"Monthly velocity and seasonal variations of the Mont Blanc glaciers derived from Sentinel-2 between 2016-2024" - supplementary materials
<p>The repository contains the supplementary materials to be downloaded relative to the research article:</p> <p>“Monthly velocity and seasonal variations of the Mont Blanc glaciers derived from Sentinel-2 between 2016-2024” </p> <p>https://doi.org/10.5194/egusphere-2023-2771</p> <p>The available files are:</p> <p>-92 raster maps of monthly velocity of the study area.</p> <p>-Shapefiles whith the glacier outlines of the 30 studied glaciers.</p> <p>-Shapefiles of the velocity time series extraction areas.</p> <p>-Velocity time series 2016-2024 of the 30 glaciers from the study. </p>
High Mountain Asia glacier velocities 2013-2015 (Landsat 8)
<p>This dataset contains the median glacier surface velocity for the Pamir-Karakoram-Himalaya for the years 2013-2015 (Landsat 8 only). The velocities has been obtained by feature-tracking of Landsat images spaced 1 year apart.</p> <p>The folder contains the following fields at 120 m resolution in GeoTiff format:</p> <p>- the velocity magnitude 'vel' (meters per year)</p> <p>- the x/y velocity components x_vel/y_vel (meters per year)</p> <p>- the associated errors err, x_err, y_err (meters per year)</p> <p>- the standard deviation of all the merged velocities 'std' (meters per year)</p> <p>- the number of image pairs that have been merged in the median</p> <p> </p> <p>I recommend filtering data with error larger than 10 m/yr.</p> <p>For more information and any use of the data, please refer to Dehecq, A., Gourmelen, N., Trouve, E., 2015. Deriving large-scale glacier velocities from a complete satellite archive: Application to the Pamir–Karakoram–Himalaya. Remote Sensing of Environment 162, 55–66. <a href="https://doi.org/10.1016/j.rse.2015.01.031">https://doi.org/10.1016/j.rse.2015.01.031 </a></p>
High Mountain Asia glacier velocities 1999-2003 (Landsat 7)
<p>This dataset contains the median glacier surface velocity for the Pamir-Karakoram-Himalaya for the years 1999-2003 (Landsat 7 SLC-ON only). The velocities has been obtained by feature-tracking of Landsat images spaced 1 year apart.</p> <p>The folder contains the following fields at 120 m resolution in GeoTiff format:</p> <p>- the velocity magnitude 'vel' (meters per year)</p> <p>- the x/y velocity components x_vel/y_vel (meters per year)</p> <p>- the associated errors err, x_err, y_err (meters per year)</p> <p>- the standard deviation of all the merged velocities 'std' (meters per year)</p> <p>- the number of image pairs that have been merged in the median</p> <p> </p> <p>I recommend filtering data with error larger than 10 m/yr.</p> <p>For more information and any use of the data, please refer to Dehecq, A., Gourmelen, N., Trouve, E., 2015. Deriving large-scale glacier velocities from a complete satellite archive: Application to the Pamir–Karakoram–Himalaya. Remote Sensing of Environment 162, 55–66. <a href="https://doi.org/10.1016/j.rse.2015.01.031">https://doi.org/10.1016/j.rse.2015.01.031 </a></p>
Sliding velocity, water discharge and basal shear stress time series at Argentière Glacier
<p>The data set contains all data presented in:</p> <p>Gimbert, F., Gilbert, A., Gagliardini, O., Vincent, C., & Moreau, L. (2021). Do Existing Theories Explain Seasonal to Multi-Decadal Changes in Glacier Basal Sliding Speed? <em>Geophysical Research Letters</em>, <em>48</em>(15), e2021GL092858. <a href="https://doi.org/10.1029/2021GL092858">https://doi.org/10.1029/2021GL092858</a></p> <p>and also in:</p> <p>Gilbert, A., Gimbert, F., Thøgersen, K., Schuler, T. V., & Kääb, A. (2022). A Consistent Framework for Coupling Basal Friction with Subglacial Hydrology on Hard-bedded Glaciers. <em>Geophysical Research Letters</em>, <em>49</em>, e2021GL097507. <a href="https://doi.org/10.1029/2021GL097507">https://doi.org/10.1029/2021GL097507</a></p> <p>Files Description:</p> <p>==================================<br> SlidingVelocities1989_2019.csv :<br> ==================================</p> <p>Contains daily values of recorded sliding velocities at the wheel.</p> <p>Column 1 = Date<br> Column 2 = Daily Values (cm/day)</p> <p>================================<br> BasalShearStress1980_2019.csv :<br> ================================</p> <p>Contains daily values of inferred basal shear stress at the wheel.</p> <p>Column 1 = Date<br> Column 2 = Daily Values (MPa)</p> <p>================================<br> WaterDischarge1985_2019.csv :<br> ================================</p> <p>Contains daily values of recorded water discharge at the glacier outlet</p> <p>Column 1 = Date<br> Column 2 = Daily Values (m3/s)</p>
Recherchebreen delta formation and glacier flow velocity data
<p>Data supporting our study on the rapid delta formation connected to glacier surge. The dataset contains positions of delta shoreline and centreline length (2020-2022) together with glacier flow velocity derived from Sentinel-1. Delta-related data produced by Jan Kavan, glacier velocity data by Adrian Luckman.</p> <p> </p> <p>This study is a contribution to the National Science Centre project ‘GLAVE’ (Award No. UMO-2020/38/E/ST10/00042).</p>
Velocity of Greenland's Helheim Glacier controlled both by terminus effects and subglacial hydrology with distinct realms of influence
<p>Description of files contained in this archive:</p> <p><strong> </strong></p> <p>SHAKTI-ISSM model output</p> <p>Winter spin-up</p> <p>Helheim_SHAKTI_N_2_1yr_H10.mat</p> <ul> <li> <p>Winter base state spin-up simulation, final state serves as initial conditions for seasonal simulations</p> </li> </ul> <p><strong> </strong></p> <p>Seasonal hydrology-forced simulations</p> <p>Helheim_big_seasonal_low.mat</p> <ul> <li> <p>Seasonal simulation</p> </li> </ul> <p>Helheim_big_seasonal_firn.mat</p> <ul> <li> <p>Seasonal + firn aquifer simulation</p> </li> </ul> <p>Helheim_big_seasonal_bigmelt.mat</p> <ul> <li> <p>Enhanced melt simulation</p> </li> </ul> <p><strong> </strong></p> <p>Seasonal terminus-forced simulations</p> <p>Helheim_termforce_year2_v3.mat</p> <ul> <li> <p>Termforce simulation</p> </li> </ul> <p>Helheim_termforce_seasonal_v3.mat</p> <ul> <li> <p>Seasonal + termforce simulation</p> </li> </ul> <p>Helheim_termforce_seasonal_firn_v3.mat</p> <ul> <li> <p>Seasonal + firn aquifer + termforce simulation</p> </li> </ul> <p>Helheim_termforce_seasonal_bigmelt2_v3.mat</p> <ul> <li> <p>Enhanced melt + termforce simulation</p> </li> </ul> <p><strong> </strong></p> <p>Sensitivity simulations</p> <p>MOLHO_365d.mat</p> <ul> <li> <p>Winter base state spin-up simulation using MOLHO instead of SSA</p> </li> </ul> <p>A15_365d.mat</p> <ul> <li> <p>Winter base state spin-up simulation with flow law parameter for -15 deg C instead of -10 deg C</p> </li> </ul> <p>Helheim_br1_lr100_1yr.mat</p> <ul> <li> <p>Winter base state spin-up simulation including opening by sliding, final state serves as initial conditions for seasonal simulations</p> </li> </ul> <p>Helheim_br1_lr100_bigmelt.mat</p> <ul> <li> <p>Enhanced melt simulation including opening by sliding</p> </li> </ul> <p><strong><br><br></strong></p> <p>Model setup scripts (to be used with ISSM in MATLAB)</p> <p>runme_Helheim_inversion.m</p> <ul> <li> <p>Script to perform stress balance inversion</p> </li> </ul> <p>Helheim_CG.exp</p> <ul> <li> <p>Model domain coordinates</p> </li> </ul> <p>Greenland_clean.par</p> <ul> <li> <p>Parameter file</p> </li> </ul> <p>merra2_runoff.mat</p> <ul> <li> <p>14-day smoothed meltwater input</p> </li> </ul> <p>runme_Helheim_shaktiissm_startfrominversion_clean.m</p> <ul> <li> <p>Script to perform coupled SHAKTI-ISSM simulation, beginning from a model set up in the inversion script</p> </li> </ul> <p>runme_Helheim_continue_shaktiissm_clean.m</p> <ul> <li> <p>Script to continue a coupled SHAKTI-ISSM simulation, beginning from the end state of a previous SHAKTI-ISSM simulation</p> </li> </ul> <p>runme_Helheim_continue_seasonal_clean.m</p> <ul> <li> <p>Script to run a transient seasonal coupled SHAKTI-ISSM simulation, beginning from the end state of a winter SHAKTI-ISSM spin-up simulation</p> </li> </ul> <p><strong> </strong></p> <p>Plotting scripts</p> <p>load_models_Helheim_termforce.m</p> <ul> <li> <p>Load model output</p> </li> </ul> <p>plot_timeseries_coupled_point_paper_clean.m</p> <ul> <li> <p>Plot time series of effective pressure, velocity, and meltwater input. Also plots scatter plot of velocity vs. effective pressure</p> </li> </ul> <p>plot_pm_logscale.m</p> <ul> <li> <p>Plot difference in velocity compared to winter state with +/- log10 color scale</p> </li> </ul> <p>plot_pm_logscale_N.m</p> <ul> <li> <p>Plot difference in effective pressure compared to winter state with +/- log10 color scale</p> </li> </ul>
Ice Velocity of Icelandic Glaciers
<p>Ice velocity map of Icelandic glaciers derived from Sentinel-1 SAR data acquired from 2014-10-01 to 2020-12-31. The surface velocity is derived applying feature tracking techniques. The ice velocity map is provided at 100m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity is provided in true meters per day, towards EASTING(vx) and NORTHING(vy) direction of the grid, and the vertical displacement (vz), is derived from a digital elevation model. Provided is a NetCDF file with the velocity components: vx, vy, vz and vv (magnitude of the horizontal components), along with maps of valid pixel count and uncertainty (stdx, stdy). The product was generated by ENVEO.<br> </p>
Cone Glacier velocity and climate data from November 2017 to January 2022
<p>Glacier velocity (m/yr) data obtained using Sentinel-2 near-infrared band 8 satellite images and the Glacier Image Velocimetry (GIV) open-source toolkit (Van Wyk de Vries & Wickert, 2021; https://doi.org/10.5194/tc-15-2115-2021). Precipitation (mm) and temperature (degrees centigrade) data obtained from gridded ERA5 reanalysis data (Hersbach et al., 2020; https://doi.org/10.1002/qj.3803) for the 0.25° x 0.25° grid square within which Cone Glacier sits. (2023-05-09)</p>
Data of "Inferring the Basal Friction Law from long term observations of Glacier Length, Thickness and Velocity changes on an Alpine Glacier"
<p>This dataset contains the surface velocity and elevation of Argentière Glacier in 2003 and 2018 used in:</p> <p>Gilbert, A., Gimbert, F., Gagliardini, O., & Vincent, C. (2023). Inferring the Basal Friction Law From Long Term Changes of Glacier Length, Thickness and Velocity on an Alpine Glacier. <em>Geophysical Research Letters</em>, <em>50</em>(16), e2023GL104503. <a href="https://doi.org/10.1029/2023GL104503">https://doi.org/10.1029/2023GL104503</a></p> <p>Surface DEM files contain elevation Z on a 20X20 meter grid (geotif files, coordinnate are in Lambert 2E ( EPSG:27572 ) )</p> <p>Horizontal Velocity files contain measured horizontal velocities Vh in m/yr on a 20X20 meter grid (geotif files, coordinnate are in Lambert 2E ( EPSG:27572 ) )</p>
Subglacial Drainage Evolution Modulates Seasonal Ice Flow Variability of Three Tidewater Glaciers in Southwest Greenland - velocity and plume data
<p>This file contains four datasets:</p> <p>- ice velocity estimates of the area surrounding and including Kangiata Nunata Sermia, southwest Greenland, derived from Landsat imagery and from Sentinel 1 imagery</p> <p>- plume observations in this area</p> <p>- subglacial discharge at the terminus</p> <p>- glacier terminus positions</p> <p>A more complete description of these datasets will be provided in the publication with the same name (currently in review). The methods used to measure glacier terminus positions are described in https://doi.org/10.5194/esurf-6-551-2018 </p>
Sliding velocity, water discharge, water pressure, and rainfall time series at Argentière Glacier between 2019 and 2021
<p>Files Description:</p> <p>==================================<br>cavitometer_2019-2021.dat:<br>==================================</p> <p>Contains 30-min sampled values of recorded sliding velocities at the cavitometer.</p> <p>Column 1 = Date<br>Column 2 = Velocity (mm/hour)</p> <p>================================<br>water_discharge_2019-2021.dat:<br>================================</p> <p>Contains 15-min sampled values of recorded water discharge at the glacier outlet.</p> <p>Column 1 = Date<br>Column 2 = Water discharge (m3/s)</p> <p>================================<br>water_pressure_2019-2021.dat:<br>================================</p> <p>Contains 30-min sampled values of recorded water pressure at the borehole BH2.</p> <p>Column 1 = Date<br>Column 2 = Water pressure (bar)</p> <p>================================<br>rainfall_2019-2021.dat:<br>================================</p> <p>Contains 30-min sampled values of recorded rainfall at the meteo station.</p> <p>Column 1 = Date<br>Column 2 = Rainfall (mm w.eq./hour)</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>
Ground Freezing Index (GFI) and the relative change of the minimum seasonal velocity compared to the mean velocity between 2005 and 2017 at Becs-de-Bosson rock glacier in the Swiss Alps
<p>This dataset contains the Ground Freezing Index (GFI) and the relative change of the minimum seasonal velocity compared to the mean velocity between 2005 and 2017 at Becs-de-Bosson rock glacier in the Swiss Alps. Velocity data is measured by GNSS surveys. GFI is the sum of the daily negative GSTs during the entire freezing season, indicating the coldness of the winter temperature.</p>
Line of Sight (LOS) velocity obtained from terrestrial radar interferometer at Helheim Glacier
<p>1h-interval LOS ice flow speed processed using TRI dataset collected at Helheim Glacier in August, 2016.</p> <p> </p>
Rock glacier velocities, Selwyn Mountains, Yukon and NWT, Canada, Version 1
An average of 6 markers were surveyed on each of 15 rock glaciers, once each in 1983 and 1995 using a level (1983) and a theodolite (1995). Measurement error was on the order of 3 percent, however, the greatest variability in observed velocities is explained by the varying locations of the markers on the rock glaciers. Lichen ages were determined by Dyke (1990a), and rock glacier lengths were obtained from 1:50,000 surficial geology maps used to compile the maps in Dyke (1990c-f). Please see the data documentation for further information.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.