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11 results for “Calving Front”
Calving Front Dataset for Marine-Terminating Glaciers in Svalbard 1985-2023
<p>Svalbard has experienced increased climate variability as a result of global warming, leading to significant mass loss in its marine-terminating glaciers over recent decades. Nevertheless, the mechanisms driving this mass loss remain less understood, primarily due to a limited understanding of calving dynamics. Here we present a new high-resolution calving front dataset of 149 marine-terminating glaciers in Svalbard, comprising 124919 glacier calving front positions during the period of 1985-2023. This dataset was generated using a novel automated deep learning framework and multiple optical and SAR satellite images from Landsat, Terra-ASTER, Sentinel-2, and Sentinel-1 satellite missions.</p> <p>The information regarding the glacier calving front terminal traces, glacier centrelines, glacier domains, fjord masks and the along-centreline glacier calving front change time series is consolidated into a single Geopackage file named "Svalbard_Calving_Front_Product.gpkg." The specific file structure for this data file is detailed in Table 1, and the feature attribute table for the different data layers recorded in this data file can be found in Table 2.</p> <p>Furthermore, we have included spatial distribution map plots of the glacier calving front traces and line plots depicting the time series of calving front changes for each individual glacier. These plots are provided in .PNG file format and can be accessed within the Figures folder.</p> <p>Table 1. The layer structure of the Svalbard calving front data product.</p> <table> <tbody> <tr> <td> <p><strong>Layer Name</strong></p> </td> <td> <p><strong>Details</strong></p> </td> </tr> <tr> <td> <p>traces</p> </td> <td> <p>Line geometries recording the terminal traces of all the glaciers (EPSG:3995).</p> </td> </tr> <tr> <td> <p>centrelines</p> </td> <td> <p>Line geometries recording the glacier centrelines used in calving front change estimation (EPSG:3995).</p> </td> </tr> <tr> <td> <p>domains</p> </td> <td> <p>Polygon geometries recording the glacier domains (EPSG:3995).</p> </td> </tr> <tr> <td> <p>fjord_masks</p> </td> <td> <p>Polygon geometries recording the fjord masks (EPSG:3995).</p> </td> </tr> <tr> <td> <p>front_change_time_series</p> </td> <td> <p>Point geometries recording the along-centreline glacier calving front change time series (EPSG:4326).</p> </td> </tr> </tbody> </table> <p> </p> <p>Table 2. The feature attribute table of the data layer.</p> <table> <tbody> <tr> <td> <p><strong>Data Field</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>Glacier</p> </td> <td> <p>The Randolph Glacier Inventory (RGI) version 6 (RGI Consortium, 2017) glacier id.</p> </td> </tr> <tr> <td> <p>Sensor</p> </td> <td> <p>The satellite platform used in mapping glacier calving front, including “Landsat”, “Terra-ASTER”, “Sentinel2” and “Sentinel1”.</p> </td> </tr> <tr> <td> <p>ImageId</p> </td> <td> <p>The image id of the satellite image used in mapping the glacier calving front.</p> </td> </tr> <tr> <td> <p>DateString</p> </td> <td> <p>The datetime string of the satellite image in the format of “YYYYMMDD”.</p> </td> </tr> <tr> <td> <p>CFL_Change</p> </td> <td> <p>The calving front location (CFL) changes in meters along the glacier centreline in relation to the earliest calving front location in the time series.</p> </td> </tr> <tr> <td> <p>glacier_lat</p> </td> <td> <p>The latitude of the glacier location (WGS84 coordinate system).</p> </td> </tr> <tr> <td> <p>glacier_lon</p> </td> <td> <p>The longitude of the glacier location (WGS84 coordinate system).</p> </td> </tr> </tbody> </table>
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>
Out-of-the-box calving front detection method using deep learning
<p>The calving front predictions of the <a href="https://www.nature.com/articles/s41592-020-01008-z">nnU-Net</a> on a benchmark <a href="https://doi.pangaea.de/10.1594/PANGAEA.940950">dataset</a>.<br> GitHub: https://github.com/ho11laqe/nnUNet_calvingfront_detection<br> Publication: https://tc.copernicus.org/preprints/tc-2023-34/</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>
CALFIN: Calving front dataset for East/West Greenland, 1972-2019
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Additional Visualizations for Glacier Calving Front Delineation on Synthetic Aperture Radar Imagery
<p>Additional visualizations showing the time series of each glacier included in the <a href="https://doi.pangaea.de/10.1594/PANGAEA.940950" target="_blank" rel="noopener">CaFFe</a> dataset and comparing predictions from different deep learning models and human annotations for glacier calving front delineation on Synthetic Aperture Radar imagery.</p>
Dataset for: Evaluation of low-cost Raspberry Pi sensors for photogrammetry of glacier calving fronts
<p>Points clouds of Fjallsjökull calving front, as derived by a Raspberry Pi and a Unoccupied Aerial Vehicle. For each sensor, eight sub-sections are analysed. Point clouds are provided in .las format. Each sub-section is generated within its own spatial reference (matching that of the other sensor to allow for comparison). </p>
Data from: A boulder beach formed by waves from a calving glacier revisited: multidecadal -tsunami- controlled coastal changes in front of Eqip Sermia
<div>This study is a contribution to the National Science Centre project ‘GLAVE’ (Award No. UMO-2020/38/E/ST10/00042)</div> <div> </div>
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