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21 results for “Glacier mapping”
High-mountain Asia glacier elevation change trend (dh/dt) map for the period spanning 2000 to 2018
<p>See manuscript for methodology and dataset description:</p> <p>Shean DE, Bhushan S, Montesano P, Rounce DR, Arendt A and Osmanoglu B (2020) A Systematic, Regional Assessment of High-Mountain Asia Glacier Mass Balance. Front. Earth Sci. 7:363. DOI: 10.3389/feart.2019.00363</p> <p>https://www.frontiersin.org/articles/10.3389/feart.2019.00363/full</p> <p>GeoTiff header contains relevant metadata and georeferencing information (30 m pixel size, Albers Equal Area projection). Proj string is '+proj=aea +lat_1=25 +lat_2=47 +lat_0=36 +lon_0=85 +x_0=0 +y_0=0 +ellps=WGS84 +datum=WGS84 +units=m +no_defs'</p> <p>External overview file (.ovr) contains pyramidal overviews for improved visualization performance at different zoom levels.</p>
Indicative distribution map for Ecosystem Functional Group T6.1 Ice sheets, glaciers and perennial snowfields
<p>This archive contains indicative distribution maps and profiles for <strong>T6.1 Ice sheets, glaciers and perennial snowfields</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
New glacier thickness and bed topography maps for Svalbard - Dataset
<p>The dataset includes three Geotiff files that include:</p> <p>1) A bed topography map of Svalbard (heights in m a.s.l.) [Bed_map.tiff]</p> <p>2) An ice thickness map of Svalbard (in m) [Thickness_map.tiff]</p> <p>3) A mask file that with values from 0-3 indicating non-glacier areas (0), glaciers modelled with the Parallel Ice Sheet model (1), glaciers modelled with the Instructed Glacier Model (2), and surging glaciers (3). </p> <p>For a description of the methods used to generate the datasets, we refer to the manuscript "A new glacier thickness and bed map for Svalbard", to be submitted to The Cryosphere Discussions.</p>
Data for 'Mapping and characterization of avalanches on mountain glaciers with Sentinel-1 satellite imagery'
<div>This dataset contains avalanche deposit outlines (as shapefiles) derived for the study 'Mapping and characterization of avalanches on mountain glaciers with Sentinel-1 satellite imagery'</div> <div> </div> <div>They were outlined at three different sites (Mt Blanc, Everest and Hispar regions) for the periods 11/2016-10/2021 (Mt Blanc) and 11/2017-10/2022 (Everest and Hispar). The time period is indicated in the file name.</div> <div> </div> <div>For each dataset we give the raw outlines (Automated_outlines_dates), the manually updated (Automated_outlines_dates_ManualUpd) and the manually updated after accounting for surface elevation change (Automated_outlines_dates_ManualUpd_shifted). </div> <div> </div> <div>In order to know which scenes were used for the mapping (if no avalanche was detected, we did not provide a shapefile, but this doesn't been that there is a gap in the Sentinel-1 time series), we provide a Sentinel1_date file that shows all the Sentinel-1 RGB pairs that we used to detect the avalanches.</div> <div> </div> <div>We also provide as geotiffs the temporally aggregated outlines (Automated_outlines_dates_ManualUpd_shifted_aggregated; over one specific year yn - from 01/11/yn-1 to 01/11/yn - or the full study period):</div> <div>- as heatmaps (where the value of each pixel corresponds to the number of avalanches that occured) </div> <div>- as binary maps of deposits (where 1 is when an avalanche occured over the time period and 0 is where none were detected).</div> <div> </div> <div> </div> <div>Finally we provide a csv file for each region with metrics per glacier:</div> <div> </div> <div>RGI ID</div> <div>Glacier size (in m^2)</div> <div>Catchment size (in m^2)</div> <div>Area of slopes steeper than 30° (in m^2)</div> <div>The area of total deposits detected (by summing all the pixels of the deposit binary maps) in the ascending obits (in m^2)</div> <div>The area of total deposits detected (by summing all the pixels of the deposit binary maps) in the descending obits (in m^2)</div> <div>The avalanche activity detected (by summing all pixels of the heat maps) in the ascending orbits (in m^2)</div> <div>The avalanche activity detected (by summing all pixels of the heat maps) in the descending orbits (in m^2)</div> <div>The area of the glacier visible in the ascending orbits (in m^2)</div> <div>The area of the glacier visible in the descending orbits (in m^2)</div> <div> </div> <div> </div> <div>The main Google Earth Engine and Matlab scripts used to pre-process the Sentinel-1 GRD images and to map the avalanches are available on GitHub: https://github.com/MarinKneib/S1_avalanches</div> <div> </div>
Supplementary files: A Comparative Study of Active Rock Glaciers Mapped from Geomorphic- and Kinematic-Based Approaches in Daxue Shan, Southeast Tibetan Plateau
<p>Supplement of "A Comparative Study of Active Rock Glaciers Mapped from Geomorphic- and Kinematic-Based Approaches in Daxue Shan, Southeast Tibetan Plateau". The supplementary files provide the outlines and parameters of the rock glaciers inventoried by InSAR-assist kinematic-based approach in the Daxue Shan, Southeast Tibet Plateau. </p> <p>Based on the Sentinel-1A ascending SAR images acquired between 2015 and 2019, we derived a five-year-long LOS mean velocity map of the study area. We then compiled a rock glacier inventory by synergistically interpreting the InSAR-derived surface displacements and geomorphic features based on Google Earth images.</p>
Drone-based glacier mapping of Nordenskiöldbreen and Tunabreen in Svalbard, 2024
<p>This database contains drone-based mapping data of two glaciers, Svalbard, Norway. The glaciers are Tunabreen in Templefjord and Nordenskiöldbreen in Billefjord. The dataset was generated using a structure-from-motion (SfM) method using drone-based imagery. The data was processed with Agisoft Metashape and the processed data consists of digital elevation models (DEMs) in georeferenced .TIF file format, orthomosaic maps in georeferenced .TIF file format, and textured 3D models in .STL and .JPG file format. In addition, a process report in .PDF file format is included for each dataset. Mapping was conducted with a DJI Mavic 3 Pro Enterprise. The mapping area covers the crevassed glacier fronts. Data collection was conducted on Nordenskiöldbreen in Spring 2024 (2024-04-29) and Tunabreen in Summer 2024 (2024-09-04). </p> <p> </p> <p>00_ReadMe.txt <br>01_2024_Tunabreen_Images.zip - Contains all raw images. <br>01_2024_Nordenskiöldbreen_Images.zip- Contains all raw images. <br>02_2024_Tunabreen_DEM.tif - Contains the digital elevation model.<br>02_2024_Nordenskiöldbreen_DEM.tif- Contains the digital elevation model.<br>03_2024_Tunabreen_Ortho.tif - Contains the orthomosaic map.<br>03_2024_Nordenskiöldbreen_Ortho.tif - Contains the orthomosaic map.<br>04_2024_Tunabreen_Report.pdf - Contains the post-processing report. <br>04_2024_Nordenskiöldbreen_Report.pdf- Contains the post-processing report. <br>05_2024_Tunabreen_Model.stl - Contains the 3D model. <br>05_2024_Nordenskiöldbreen_Model.stl - Contains the 3D model. <br>06_2024_Tunabreen_Texture.jpg - Contains the 3D model texture. <br>06_2024_Nordenskiöldbreen_Texture.jpg - Contains the 3D model texture. </p>
Drone-based glacier mapping of Borebreen in Svalbard, 2024
<p>This database contains drone-based glacier mapping data of Borebreen, Svalbard, Norway. The glacier is located in Isfjorden. The dataset was generated using a structure-from-motion (SfM) method using drone-based imagery. The data was processed with Agisoft Metashape and the processed data consists of digital elevation models (DEMs) in georeferenced .TIF file format, orthomosaic maps in georeferenced .TIF file format, and textured 3D models in .STL and .JPG file format. In addition, a process report in .PDF file format is included for each dataset. Mapping was conducted with a DJI Mavic 3 Pro Enterprise. The mapping area covers the crevassed glacier fronts. Data collection was conducted over three days in August/September 2024. The three collection dates were 2024-08-14, 2024-08-28, and 2024-09-25. </p>
Density maps of seismic localization with a low phase coherence at 13 Hz on Argentière glacier
<p>This dataset is associated with the paper:</p> <p>----------</p> <p><strong>Dynamic imaging of glacier structures at high-resolution using source localization: a dense seismic array experiment.</strong></p> <p> </p> <p><em>Ugo Nanni<sup>1,*</sup>, Philippe Roux<sup>2</sup>, Florent Gimbert<sup>1</sup> and Albanne Lecointre<sup>2</sup></em></p> <p> </p> <p><em><sup>1</sup> IGE, Univ. Grenoble Alpes, CNRS, IRD, Grenoble, France</em></p> <p><em><sup>2</sup> ISTerre, Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, IRD, IFSTTAR, Grenoble, France</em></p> <p><em>---------</em></p> <p>It contains 32 maps of seismic localization associated with low phase coherence and frequency of 13 Hz, and represents the events originating from transverse crevasses (see details in the paper).</p> <p>An image of the glacier is also provided to compare the localization to the glacier structure.</p> <p>Dataset is in .mat format</p> <p> </p>
Fracture maps and calving fronts for Thwaites Glacier western terminus 2015-2021
<p>These data comprise observations of severe crevassing and calving front position over the Thwaites Glacier Ice Tongue (TGIT) between 2015 and 2021 in geotiff form, along with bitmap versions of Sentinel-1 backscatter images from which the observations were derived. A version of UNet was used to create the data from the backscatter images.<br> These data were collected in 2021 for the study of structural change on the TGIT.</p> <p>File information: tgit_cfs.tar.gz is a gz-compressed directory of binary calving front segmentations of the Thwaites Glacier Ice Tongue in geotiff format.<br> tgit_fms.tar.gz is a gz-compressed directory of binary fracture segmentations of the Thwaites Glacier Ice Tongue in geotiff format.</p>
Kongsvegen glacier cave map
<p>Mapping data of a glacier cave inside the tidewater glacier Kongsvegen (western Svalbard, Norway), collected on 06th of June 2021. Data was collected using a handheld GPS unit and a DistoX mapping device.</p>
Glacier thickness maps for Ecuador and Colombia
<p>Upload associated with Scientific Data submission: Glacier thickness and ice volume of the inner tropical Andes.</p> <p>The dataset includes:</p> <p>-Ice velocity maps for all 11 glacier regions (5 in Ecuador and 6 in Colombia)</p> <p>-Ice thickness maps for all 11 glacier regions generated using the 6 different thickness calculation methods</p> <p>-Multi-model ensemble mean glacier thickness maps for all 11 glacier regions</p> <p>-Basin-divided ice volumes for each glacier region, with a 1 km, 5 km, and 20 km buffer</p> <p>-Results of a full parameter sensitivity test for the thickness calculation</p> <p>All data are saved in 32-bit floating-point geotiff format. The data are freely available under the Creative Commons Attribution Licence, CC BY 4.0.</p> <p>The feature-tracking code used to derive ice velocities, GIV, is available on github and Zenodo (https://doi.org/10.5281/zenodo.4904544). All other code, including Google Earth Engine download scripts and the ice-thickness inversion code is available on zenodo (https://doi.org/10.5281/zenodo.6323069).</p>
Mapping of the calving front of Eqip Sermia Glacier, West Greenland, by UAV photogrammetry
<p>These data contain photogrammetrical data collected by unmanned aerial vehicle (UAV) in July 2018 at Eqip Sermia Glacier. The data include processed data (orthoimage and digital elevation models) with the Structure-fom-Motion photogrammetrical software Agisoft Photoscan.</p> <p>For each, processed and raw, data are organized by glacier surveys with the following convention GLACIER_YYYYMMDD_HHMM or GLACIER_YYYYMMDD_HHMM_N.</p> <p>For instance : eqip_20180708_1225 contains the Data of the LARGE-SCALE survey of Eqip glacier that started on July 8, 2018 at 12:25 UTC time. eqip_20180707_1245_1 contains the Data of the FIRST repeat survey of the calving front of Eqip glacier that started on July 7, 2018 at 12:45 UTC time, eqip_20180707_1245_2 is the second repeat survey, eqip_20180707_1245_3 is the third and eqip_20180707_1245_4 is the last.</p> <p>Coordinate system used is UTM Zone 22W based on WGS84</p> <p>Take-off and landing site latitude and longitude was ( 69.757767 , - 50.228172 )</p> <p>This dataset is related to the article "High-endurance UAV for monitoring calving glaciers: Application to the Inglefield Bredning and Eqip Sermia, Greenland", G. Jouvet, Y. Weidmann, E. van Dongen, M. Lüthi, A. Vieli, J. V. Ryan, Frontiers in Earth Sciences.</p> <p> </p> <p> </p>
Mapping of the calving front of Hart, Sharp, Melville and Farquhar glaciers, Northwest Greenland, by UAV photogrammetry
<p>These data contain photogrammetrical data collected by unmanned aerial vehicle (UAV) in July 2017 in the Inglefield Bredning. The data include processed data (orthoimage and digital elevation models) with the Structure-fom-Motion photogrammetrical software Agisoft Photoscan.</p> <p>Data are organized by glacier surveys with the following convention GLACIER_YYYYMMDD_HHMM. For instance : farquhar_20170705_1914 contains the Data of the survey of Farquhar glacier that started on July 5, 2017 at 19:14 UTC time.</p> <p>Coordinate system used is UTM Zone 19N based on WGS84</p> <p>Take-off and landing site lattitude and longitude was ( 77.497424 , -66.678433 )</p> <p>This paper is related to the article "High-endurance UAV for monitoring calving glaciers: Application to the Inglefield Bredning and Eqip Sermia, Greenland", G. Jouvet, Y. Weidmann, E. van Dongen, M. Lüthi, A. Vieli, J. V. Ryan, Frontiers in Earth Sciences</p> <p> </p>
Mapping of the calving front of Heilprin Glacier, North West Greenland, by UAV photogrammetry
<p>These data contain photogrammetrical data collected by unmanned aerial vehicle (UAV) in July 2017 in the Inglefield Bredning. The data include processed data (orthoimage and digital elevation models) with the Structure-fom-Motion photogrammetrical software Agisoft Photoscan.</p> <p>Data are organized by glacier surveys with the following convention GLACIER_YYYYMMDD_HHMM. For instance : heilprin_20170705_1914 contains the Data of the survey of Heilprin glacier that started on July 5, 2017 at 19:14 UTC time.</p> <p>Coordinate system used is UTM Zone 19N based on WGS84</p> <p>Take-off and landing site lattitude and longitude was ( 77.497424 , -66.678433 )</p> <p>The data are related to the article "High-endurance UAV for monitoring calving glaciers: Application to the Inglefield Bredning and Eqip Sermia, Greenland", G. Jouvet, Y. Weidmann, E. van Dongen, M. Lüthi, A. Vieli, J. Ryan, Frontiers in Earth Sciences</p>
Mapping of the calving front of Tracy Glacier, North West Greenland, by UAV photogrammetry
<p>These data contain photogrammetrical data collected by unmanned aerial vehicle (UAV) in July 2017 in the Inglefield Bredning. The data include processed data (orthoimage and digital elevation models) with the Structure-fom-Motion photogrammetrical software Agisoft Photoscan.</p> <p>Data are organized by glacier surveys with the following convention GLACIER_YYYYMMDD_HHMM. For instance : tracy_20170705_1914 contains the Data of the survey of Tracy glacier that started on July 5, 2017 at 19:14 UTC time.</p> <p>Coordinate system used is UTM Zone 19N based on WGS84</p> <p>Take-off and landing site lattitude and longitude was ( 77.497424 , -66.678433 )</p> <p>The data are related to the article "High-endurance UAV for monitoring calving glaciers: Application to the Inglefield Bredning and Eqip Sermia, Greenland", G. Jouvet, Y. Weidmann, E. van Dongen, M. Lüthi, A. Vieli, J. Ryan, Frontiers in Earth Sciences</p>
Using a Web Map Service to map Little Ice Age glacier extents at regional scales
<p>Extending the record of glacier area changes into the past improves our understanding of climate change impacts. Although analogue maps showing historic glacier extents are abundant, digital outlines from before the satellite era are sparse as the digitisation of moraines and trimlines on freely available satellite images is challenging. With the now available very high-resolution images provided by Web Map Services (WMS), new doors are open for the precise digitisation. Here, we used the ESRI WMS to digitise Little Ice Age (LIA) glacier extents and present area changes since the LIA in four selected regions along with a detailed uncertainty analysis. We used modern glacier outlines as a starting point and additionally consulted Sentinel-2 images, the ArcticDEM and historic maps for interpretation. Dating records from the literature allowed calculating area change rates. In total, 493 LIA glaciers (4640 km2, now 891 ice bodies with 3590 km2) were digitised, yielding relative area changes of −20% (−0.14% a−1), −15% (−0.10% a−1), −26% (−0.16% a−1) and −61% (−0.19% a−1) for Alaska, Baffin Island, Novaya Zemlya and the tropics, respectively. The ESRI WMS images are a great asset to precisely map moraines and trimlines, but information about the timing of the related extents requires further sources.</p>
Mapped glacier region in BH during LIA
<p>Mapped glacier region in BH during LIA </p>
Map of the rate of elevation change of Mont-Blanc glaciers derived from Pléiades stereo-images
<p>This collection contains three map of elevation changes derived form Pléiades images acquired in 2012, 2021 and 2022 over the Mont-Blanc Massif (Alps) with a horizontal grid spacing of 4 m. They were derived from stereo-pairs acquired 19 August 2012, 15 August 2021, 12 October 2022, 8 August 2022 and 5 October 2022. No data are indicated by the -9999 value.</p> <p>We generated 4-m DEMs from five Pléiades stereo-pairs using the semi-global matching algorithm of the Ames Stereo Pipeline (Beyer et al., 2018) and the set of parameters defined in Deschamps-Berger et al. (2020). The DEMs were first coregistered on stable terrain, masking out glacierized areas using a glacier inventory from year 2015 (Paul et al., 2020). Spatially-coherent biases in the elevation difference maps were next corrected using a polynomial fit across-track and a spline fit in the along-track direction (Falaschi et al., 2023). </p> <p>Pléiades stereo-images were obtained thanks to DINAMIS Project, for “Dispositif Institutionnel National d’Approvisionnement Mutualisé en Imagerie Satellitaire”, a French platform that acquires and distributes very high resolution Earth satellite imagery for French and foreign institutional users under specific subscription conditions.</p>
MEaSUREs Greenland Ice Velocity: Selected Glacier Site Velocity Maps from Optical Images V003
This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, consists of mean monthly velocity maps for selected glacier outlet areas. The maps are generated by tracking visible features between optical image pairs acquired by the Landsat 4 and 5 Thematic Mapper (TM), the Landsat 7 Enhanced Thematic Mapper Plus (ETM+), the Landsat 8 Operational Land Imager (OLI), and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). See <a href="http://nsidc.org/data/measures/gimp">Greenland Ice Mapping Project (GIMP)</a> for related data.
MEaSUREs Greenland Ice Velocity: Selected Glacier Site Single-Pair Velocity Maps from Optical Images V001
This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, consists of surface velocity estimates for selected Greenland Ice Sheet outlet glaciers. Velocity fields were generated by tracking visible features in optical images acquired by the U.S. Geological Survey (USGS) Landsat 8 Operational Land Imager (OLI) and the European Space Agency (ESA) Copernicus Sentinel-2A and Sentinel-2B satellites.
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