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81 results for “altimetry”
Sentinel-3A and Sentinel-3B radar altimetry water surface elevation in the Zambezi catchment
<p>This dataset contains the data presented in Kittel et al. (2020): Sentinel-3 radar altimetry for river monitoring – a catchment-scale evaluation of satellite water surface elevation from Sentinel-3A and Sentinel-3B, https://doi.org/10.5194/hess-2020-165</p> <p>The dataset is the full Sentinel-3A and 3B radar altimetry records for water surface elevation in the Zambezi catchment for all virtual stations containing at least 80% of the expected observations and predominantly single-peak waveforms. Not all VS have been manually checked or validated.</p> <p>Additionally the repository contains a shapefile with all Sentinel-3 virtual stations in the Zambezi.</p>
An Improved Method Based on Deep Learning for Refined Bathymetry from Satellite Altimetry: Reducing the Errors Effectively
<p><strong>The source dataset and code for this research.</strong></p>
Absolute sea level changes along the coast of China from tide gauges, GNSS and satellite altimetry
<p>The datasets are used for the study of absolute sea level changes along the coast of China from tide gauges, GNSS and satellite altimetry. There are five folders containing the data of GNSS, tide gauge, land freshwater runoff and the results extraction from AVISO grid products. A data description is included in the datasets.</p>
ICESat, ERS1, ERS2, Envisat Laser and Radar Altimetry Datasets for the Cryosphere model Comparison Tool (CmCt) Input for Greenland and Antarctica
<div> <p>These datasets contain the ICESat, ERS1, ERS2, Envisat Laser and Radar Altimetry Datasets for CmCt Input data for Greenland and Antarctica. These reference observational datasets are used in the CmCt to compare ice sheet models with.</p> <p>The <strong>ICESat/GLAS</strong> instrument was a lidar altimeter and the primary instrument on the NASA ICESat mission. It took point elevation measurements approximately every 170 meters along its track, and each shot had a footprint of approximately 70 meters in diameter.</p> <p>The GLAS instrument contained 3 lasers, but due to some instrumentation issues, it was decided to turn the lasers on and off during predetermined time periods. For more detailed information about GLAS and the ICESat mission, visit the <a href="http://icesat.gsfc.nasa.gov/icesat/" target="_blank" rel="nofollow noopener noreferrer noopener noreferrer noopener noreferrer">ICESat website</a>.</p> <p>For use with the CmCt project, the Greenland elevation data from ICESat/GLAS (Zwally et al, 2002) were preprocessed. The data were cleaned and limited to the ice sheets. At the time of creation the 634 release of the <a href="https://nsidc.org/data/GLA12/versions/34" target="_blank" rel="nofollow noopener noreferrer noopener noreferrer noopener noreferrer">GLAS12</a> product was used (<em>Zwally et al, 2014</em>). </p> <p>The processing was accomplished by:</p> <ol> <li>restricting the data to GLAS data points only on the ice surface</li> <li>applying two data quality filters we required the GLAS surface reflectivity to be > 0.0375 and we required the uncertainty associated with the GLAS fitting procedure to be < 0.0375 (the numerical coincidence is in fact a coincidence). These are the same quality criteria that were used for <a href="http://imbie.org/" target="_blank" rel="nofollow noopener noreferrer noopener noreferrer noopener noreferrer">IMBIE2</a> and thus are being implemented for the CmCt.</li> <li>checking the data against the reerence DEM (GIMP 90-m DEM for Greenland or Bamber 1-km DEM for Antarctica), requiring the elevation difference to be < 200m.</li> </ol> <p>Please find more details on the data preprocessing in the Supporting Docs tab.</p> <p>The<a href="https://www.esa.int/Applications/Observing_the_Earth/Envisat" target="_blank" rel="nofollow noopener noreferrer noopener noreferrer noopener noreferrer"> <strong>Envisat</strong></a> (Environmental Satellite), <strong><a href="https://eoportal.org/web/eoportal/satellite-missions/e/ers-1" target="_blank" rel="nofollow noopener noreferrer noopener noreferrer noopener noreferrer">ERS1</a></strong>, <strong><a href="https://eoportal.org/web/eoportal/satellite-missions/e/ers-2" target="_blank" rel="nofollow noopener noreferrer noopener noreferrer noopener noreferrer">ERS2</a></strong> (European Remote Sensing Satellites 1 and 2) radar altimeter datasets were also preprocessed to prepare the data to generate a comparison data set for the CmCt. Several filters were used to remove data that are not on the ice sheet or have questionable elevations. Please see the detailed processing descriptions in the Supporting Docs.</p> <p>Radar and laser altimeters measure similar parameters. They measure the time of flight of photons from the spacecraft to the reflection point and back to the spacecraft. The time of flight is then used to calculate an elevation. Accurate elevations require precise knowledge of the spacecraft orbit, corrections for atmospheric scattering, and other factors.</p> <p>There are several differences between the radar and laser altimetry data available here that should be noted:</p> <ul> <li>The accuracy of the elevations calculated from the radar data is generally lower than the accuracy of elevations based on laser data, primarily because <ul> <li>the radar beam is much broader (several km by the time it reaches the ground vs < 100 m for the laser beam).</li> <li>the radar photons penetrate snow and ice a significant amount (cm to m), whereas the laser photons from ICESat penetrate minimally if at all.</li> </ul> </li> <li>ERS and Envisat worked at a lower pulse rate than ICESat, and had a shorter repeat period, so the data are sparser on the ground (but repeat approximately monthly). On the other hand, the radar satellites worked continuously, whereas ICESat only operated for 2-3 months per year. </li> <li>The radar data collectively cover a longer period of time, starting more than a decade earlier and extending past the end of the ICESat data.</li> <li>ERS and Envisat were in orbits that left larger holes at the poles than ICESat (8.5 degrees for the radar satellites vs 4 degrees for ICESat).</li> <li>Radar beams penetrate clouds, whereas the ICESat laser beam was scattered by clouds, with returns becoming unusable if the optical depth was much greater than 1.</li> </ul> <h4> </h4> <h4>Laser and Radar Altimetry Available Data Time Range:</h4> <h4> </h4> <table> <tbody> <tr> <td>ERS1:</td> <td>1991-1995</td> </tr> <tr> <td>ERS2:</td> <td>1996-2002</td> </tr> <tr> <td>Envisat:</td> <td>2003-2012</td> </tr> <tr> <td>ICESat/GLAS:</td> <td>2003-2009</td> </tr> </tbody> </table> <h4> </h4> <h4>Downloading Data</h4> <p><a href="https://theghub.org/resources?id=4737"><strong>The data can be downloaded from the Globus GHub-CmCt endpoint. Please log in and click on the Download tab to receive the Download instructions.</strong></a></p> </div> <h4>References</h4> <div> <p>Howat, I. M., A. Negrete, and B. E. Smith, The Greenland Ice Mapping Project (GIMP) land classification and surface elevation data sets, The Cryosphere 8.4 (2014): 1509-1518.</p> <p> </p> <p>Howat, I. M., A. Negrete, and B. E. Smith. MEaSUREs Greenland Ice Sheet Mapping Project (GIMP) Digital Elevation Model, Boulder, Colorado USA: NASA National Snow and Ice Data Center Distributed Active Archive Center (2015).</p> <p> </p> <p>Zwally, H. J., et al. ICESat's laser measurements of polar ice, atmosphere, ocean, and land, Journal of Geodynamics 34.3 (2002):405-445.</p> <p> </p> <p>Zwally, H. J., et al. GLAS/ICESat L2 Antarctic and Greenland ice sheet altimetry data V034, National Snow and Ice Data Center, Boulder, Colorado (2014).</p> </div>
Figure 1 in Validation of Wind Speed Calculated on Satellite Altimetry Data by Measurements on Weather Stations Located Along the White Sea Coast
Figure 1. Maps of the White Sea. Dashed lines show boundaries of the sea and their internal parts (Lebedev et al., 2011).
Figure 2 in Interannual Variability of Water Exchange Anomalies Between the Northern, Middle and Southern Caspian Based on Satellite Altimetry Data
Figure 2. Position of the 133 and 209 tracks of the TOPEX/Poseidon and Jason-1/2/3 satellites on water area of the Caspian Sea and coordinate axes for calculation water exchange across these tracks. Dashed lines show geographic division of the Caspian Sea on three parts.
Dataset used in "Unmanned Aerial System (UAS) observations of water surface elevation in a small stream: comparison of radar altimetry, LIDAR and photogrammetry techniques"
<p>Dataset for research paper "Unmanned Aerial System (UAS) observations of water surface elevation in a small stream: comparison of radar altimetry, LIDAR and photogrammetry techniques", published in Remote Sensing of Environment 2019, Elsevier Journal.</p> <p>Dataset includes:</p> <p>-MATLAB_codes.rar: zip file that contains MATLAB codes. MAIN.m is the main code, it refers to external functions that are included in the zip file. MAIN.m plots the figures of the paper in which we compare radar, LIDAR and photogrammetry and computes statistics of table 3 (table of the paper)</p> <p>-zip file WL_observations_Aomose.zip contains LIDAR, radar, and photogrammetry observations to be loaded by MATLAB code MAIN.m</p> <p>-the LIDAR Digital Surface Model (DSM_final.tif) retrieved in the stream Amose Å</p> <p>-the photogrammetry Digital Elevation Model (DEM_nov.tif) and orthomosaic (orthomosaic_nov.tif) </p> <p> </p>
Monthly glacier mass changes from CryoSat-2 radar altimetry
<p>We generate a record of ice loss across glaciers globally for the first time from CryoSat-2 swath interferometric radar altimetry. CryoSat-2’s orbital sub-cycle of 30 days allows us to resolve changes at high temporal resolution for Alaska, Arctic Canada North and South, Greenland periphery glaciers, Iceland, Svalbard, Franz Josef Land, Novaya Zemlya, Severnaya Zemlya, High Mountain Asia, Southern Andes and Antarctic periphery glaciers between 2010 and 2020.</p>
GLAS/ICESat 1 km Laser Altimetry Digital Elevation Model of Greenland, Version 1
The Geoscience Laser Altimeter System (GLAS) instrument on the Ice, Cloud, and land Elevation Satellite (ICESat) provides global measurements of elevation, and repeats measurements along nearly-identical tracks; its primary mission is to measure changes in ice volume (mass balance) over time. This digital elevation model (DEM) of Greenland is derived from GLAS/ICESat laser altimetry profile data and provides new surface elevation grids of the ice sheets and coastal areas, with greater latitudinal extent and fewer slope-related effects than radar altimetry.This DEM is generated from the first seven operational periods (from February 2003 through June 2005) of the GLAS instrument. It is provided on polar stereographic grids at 1 km grid spacing. The grid covers all of Greenland south of 83° N. Elevations are reported as centimeters above the datums, relative to both the WGS 84 ellipsoid and the EGM96 geoid, in two separate elevation data files. A data quality map of the interpolation distance is distributed in addition to the elevation data. ENVI header files are also provided.The data are in 4-byte (long) signed integer binary files (big endian byte order) and are available via FTP.
Antarctic 1 km Digital Elevation Model (DEM) from Combined ERS-1 Radar and ICESat Laser Satellite Altimetry, Version 1
This data set provides a 1 km resolution Digital Elevation Model (DEM) of Antarctica. The DEM combines measurements from the European Remote Sensing Satellite-1 (ERS-1) Satellite Radar Altimeter (SRA) and the Ice, Cloud, and land Elevation Satellite (ICESat) Geosciences Laser Altimeter System (GLAS). The ERS-1 data are from two long repeat cycles of 168 days initiated in March 1994, and the GLAS data are from 20 February 2003 through 21 March 2008. The data set is approximately 240 MB comprised of two gridded binary files and two Environment for Visualizing Images (ENVI) header files viewable using ENVI or other similar software packages. The data are available via FTP.
Antarctic 5-km Digital Elevation Model from ERS-1 Altimetry, Version 1
This data set provides a Digital Elevation Model (DEM) for Antarctica to 81.5 degrees south latitude, at a resolution of 5 km. Approximately twenty million data points were used to generate this data set. Data points were derived from ERS-1 radar altimetry during the geodetic phase from March 1994 to May 1995.
Seasat and GEOSAT Altimetry for the Antarctic and Greenland Ice Sheets, Version 1
<p><font color="#FF0000">Note: This data set is now on HTTPS so references to CD-ROM are historic and no longer applicable.</font></p>The Ice Altimetry System (IAS) data seet contains surface elevations of the Antarctic and Greenland ice sheets derived from Seasat and GEOSAT radar altimetry data. The Seasat data were collected for a continuous 90 days in 1978, at latitudes between 72 degrees South and 72 degrees North. GEOSAT was launched in 1985 and placed in a nearly identical orbit to Seasat, also at latitudes of between 72 degrees South and 72 degrees North. The orbit was designed to provide high-density measurements over the Earth's surface, at a maximum grid spacing of 2.7 kilometers at the equator and much denser spacing over polar ice sheets. Data were acquired between April 1985 and September 1986.Initially acquired by the Johns Hopkins APL (Applied Physics Lab) satellite tracking facility, the raw altimetry satellite data from Seasat and GEOSAT were passed on to NASA, via the US Navy. NASA developed slope correction routines for the higher slopes over the ice sheets, relative to ocean surfaces. The data are height profile Level 3 data and gridded height Level 4 data provided by the Oceans and Ice branch of the Laboratory for Hydrospheric Physics of Goddard Space Flight Center. Elevations from the full data rate (i.e., one measurement every 662.5 m) are provided in georeferenced databases. These elevations are relative to the WGS-84 ellipsoid. Gridded elevations at 10-kilometer and 20-kilometer spacing are provided in the gridded data sets created from the GEOSAT and Seasat data, respectively. Software to extract and browse subsets of these data is included. The IAS software also allows the user to view contours created from the gridded data and groundtracks of the full-rate data.
GLAS/ICESat 500 m Laser Altimetry Digital Elevation Model of Antarctica, Version 1
The Geoscience Laser Altimeter System (GLAS) instrument on the Ice, Cloud, and land Elevation Satellite (ICESat) provides global measurements of elevation, and repeats measurements along nearly-identical tracks; its primary mission is to measure changes in ice volume (mass balance) over time. This digital elevation model (DEM) of Antarctica is derived from GLAS/ICESat laser altimetry profile data and provides new surface elevation grids of the ice sheets and coastal areas, with greater latitudinal extent and fewer slope-related effects than radar altimetry.This DEM is generated from the first seven operational periods (from February 2003 through June 2005) of the GLAS instrument. It is provided on polar stereographic grids at 500 m grid spacing. The grid covers all of Antarctica north of 86° S. Elevations are reported as centimeters above the datums, relative to both the WGS 84 ellipsoid and the EGM96 geoid, in two separate elevation data files. A data quality map of the interpolation distance is distributed in addition to the elevation data. ENVI header files are also provided.The data are in 4-byte (long) signed integer binary files (big endian byte order) and are available via FTP.
Input data for manuscript "An open-source low-cost sensor for SNR-based GNSS reflectometry: Design and long-term validation towards sea level altimetry"
<p>Input data for Fagundes et al. (2021), "An open-source low-cost sensor for SNR-based GNSS reflectometry: Design and long-term validation towards sea level altimetry", GPS Solutions (in press). <a href="https://www.researchgate.net/publication/341946011">preprint</a></p>
3D-LAKES: A Three-Dimensional Global Lake and Reservoir Bathymetry Utilizing ICESat-2 Altimetry and Landsat Imagery
<p>This study introduces the 3D-Global Lakes (3D-LAKES) dataset, which includes the area-elevation (A-E) relationship and three-dimensional bathymetry for 510,530 global lakes and reservoirs, representing 98.9% of global surface water storage capacity. In this Zenodo, Level 1 (L1) and Level 2 (L2) A-E relationships are provided. L1 products were created using ICESat-2 and Landsat satellites, while L2 products, apply interpolation and extrapolation to L1 products, may contain errors. For detailed structure and format information, please read the "README" file included in the repository.</p> <p>Furthermore,</p> <p>You can view the A–E relationships and 3D bathymetry maps interactively through the Google Earth Engine (GEE) application. Please visit <a href="https://planet-test-projectchi.projects.earthengine.app/view/d-lakes" target="_new" rel="noreferrer">this link</a>.</p> <p>For downloading the 3D Bathymetry maps, please visit either the <strong><a href="https://code.earthengine.google.com/071edead921f56ae44f67888528f854c" target="_blank" rel="noopener">Google Earth Engine (GEE) code</a></strong> or the <strong><a href="https://colab.research.google.com/drive/15yRD3E06zmsm4tAF-mBz-DhHvIKNq1Lh?usp=drive_link" target="_blank" rel="noopener">Python version</a></strong> of the code.</p> <p>For detailed methodology and validation, see Huang (2025)*.</p> <p>Huang, C.H., Zhang, S., Shah, D. <em>et al.</em> 3D-LAKES: Three-Dimensional Global Lake and Reservoir Bathymetry from ICESat-2 Altimetry and Landsat Imagery. <em>Sci Data</em> <strong>12</strong>, 1625 (2025). https://doi.org/10.1038/s41597-025-05911-y</p> <p> </p>
Altimetry-derived Gravity Gradients using Spectral Method and Their Performance in Bathymetry Inversion using Back-Propagation Neural Network
<p>Data and accompanying MATLAB scripts for the machine learning section of the paper <em> Altimetry-derived Gravity Gradients using Spectral Method and Their Performance in Bathymetry Inversion using Back-Propagation Neural Network</em>. </p>
UVS Occultation Altimetry Code and Synthetic Data
Open the record for dataset details and reuse information.
GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034
GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product. Each data granule has an associated browse product.
GLAS/ICESat L1A Global Altimetry Data (HDF5) V033
Level-1A altimetry data (GLAH01) include the transmitted and received waveform from the altimeter. Each data granule has an associated browse product.
GOLDSTONE MOON DSS14/DSS13/DSS15/DSS25 5 ALTIMETRY V1.0
This archive contains digital elevation models (DEMs) of the lunar south pole. Elevation data at 200 pixels per degree of latitude (~150 m spatial resolution) were obtained with radar interferometry from the Goldstone Solar System Radar and calibrated with Lunar Reconnaissance Orbiter laser altimetry data. Elevations are given in meters with respect to a 1737.4 km sphere.
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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
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