Kongsvegen, Svalbard: late quiescent-stage glacier geometry and dynamics
GB/NERC/BAS/PDC/01334
Abstract:
This dataset consists of a bed DEM and four velocity maps of Kongsvegen, a surge-type glacier in Svalbard. The bed DEM was generated from ground-penetrating radar surveys in spring 2016 and 2018, and the velocity maps span the period Dec 2017 to Feb 2019. The velocity maps show the initial speed-up of the glacier as it transitions from quiescence to surge.
Data acquisition was funded by NERC Urgency Grant NE/R018243/1 REBUS (Resolving Enthalpy Budget to Understand Surges).
Citation:
Luckman, A., Kohler, J., & Benn, D. (2020). Kongsvegen, Svalbard: late quiescent-stage glacier geometry and dynamics (Version 1.0) [Data set]. UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation. https://doi.org/10.5285/8f94782a-87a1-4e54-a911-89aee1f15aea
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License
| Access: | No restrictions apply. |
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| Use: | This data is governed by the NERC data policy http://www.nerc.ac.uk/research/sites/data/policy/ and supplied under Open Government Licence v3 http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/. |
Basic Information
| Creation Date: | 2020-05-29 |
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| Dataset Progress: | Complete |
| Dataset Language: | English |
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| Parameters: |
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Additional Information
| Reference: | D'Errico, J. (2018). Surface Fitting using gridfit (https://www.mathworks.com/matlabcentral/fileexchange/8998-surface-fitting-using-gridfit), MATLAB Central File Exchange. Retrieved July 28, 2010. Luckman, A., Benn, D. I., Cottier, F., Bevan, S., Nilsen, F., Inall, M., Oct. 2015. Calving rates at tidewater glaciers vary strongly with ocean temperature. Nature Communications 6, 8566+. https://doi.org/10.1038/ncomms9566 |
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| Quality: | The ice thickness and bed elevation data are accurate to +/- 10 m. Uncertainties in ice surface velocity are estimated to be 0.4m per day, and comprise co-registration error (±0.2 pixels) and error arising from smoothing of the velocity field over the feature-tracking window size (400x400 m). |
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| Lineage/Methodology: | The data used for generating the bed DEM comprise ice thickness measured with 5-MHz radar and surface elevations derived from concurrent differential GNSS measurements. The DEM was generated in Matlab using the interpolation scheme "gridfit" (D'Errico, 2010). The velocity maps were generated by feature-tracking pairs of Synthetic Aperture Radar (SAR) images acquired by the TerraSAR-X satellite operated by the German Space Agency DLR. Pairs of 'Stripmap Mode' images separated by 11 days (the satellite orbital cycle) from December 2017, March and April 2019, and February/March 2019 were acquired especially for the project. Velocity map dates are embedded within the filenames. Feature tracking was applied using the methods described in Luckman et al. (2015), which also explains the uncertainties in the measurements. |
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Extent
| Temporal Coverage: | |
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| Start Date | 2016-01-01 |
| End Date | 2019-02-28 |
| Spatial Coverage: | |
| Latitude | |
| Southernmost | 78.70699 |
| Northernmost | 78.88033 |
| Longitude | |
| Westernmost | 12.39992 |
| Easternmost | 13.58087 |
| Altitude | |
| Min Altitude | -99 masl |
| Max Altitude | 1255 masl |
| Depth | |
| Min Depth | N/A |
| Max Depth | N/A |
| Location: | |
| Location | Arctic |
| Detailed Location | Kongsvegen (glacier), Svalbard |
Instrumentation
| Sensor(s): |
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| Data Collection: | 5-MHz radar: National Instruments PXI controller and digital oscilloscope, Kentech pulse transmitter, 5 Mhz resistively loaded dipole antennas. |
Storage
| Distribution: | |
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| Distribution Media | Online Internet (HTTP) |
| Distribution Size | 63.4 MB |
| Distribution Format | TIFF |
| Fees | N/A |
| Data Storage: | The dataset comprises five geoTIFFs. A bed DEM, and four velocity maps. |