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5 results for “snow height”
Average glacier stake height and snow depth measurements, McMurdo Dry Valleys, Antarctica (1993-2023, ongoing)
As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a systematic sampling program has been undertaken to monitor glacial mass balance and meltwater flow. This data package includes stake height and snow depth measurements to the surface of six glaciers (Canada, Commonwealth, Hughes, Suess, Howard, and Taylor) in Taylor Valley and one glacier (Adams) in Miers Valley, all of which are located in the McMurdo Dry Valleys of Antarctica. Most measurements began during the 93-94 field season. Adams measurements were established during the 14-15 field season. Measurements are ongoing except at Hughes and Suess Glaciers where monitoring ceased following the 08-09 field season. Monitoring the changes in these measurements over time provides a record of mass balance, and aids in determining the role of glaciers in the polar hydrologic cycle.
Snow Height Classification Dataset
<div> <p>Snow Height Classification dataset provides manually annotated snow height data that can be used for development and evaluation of automatic snow height classification approaches.</p> <p><strong>Main Dataset</strong></p> <p>A subset of 20 IMIS stations which span different locations and elevations and vary in underlying surface (e.g., vegetation, bare ground, glacier, etc.) were selected and manually annotated with binary two-class ground truth information regarding snow height data:</p> <ul> <li><strong>Class 0 - Snow</strong> - the surface is covered by snow</li> <li><strong>Class 1 - No Snow</strong> - the surface is snow-free (e.g., vegetation, soil, rocks, etc.)</li> </ul> <p>Data has been annotated with the help of domain experts. It should be mentioned that annotating historical data is problematic, as there is no way of checking whether there really was snow at the station or not. This means that assessing the presence of snow with the help of information from other sensors should be considered a best effort approach.</p> <p><strong>Additional Data</strong></p> <p>Besides the annotated snow height data, the dataset also contains additional data which are relevant to reproduce results in presented together with the following software: <a href="https://doi.org/10.5281/zenodo.12698070">https://doi.org/10.5281/zenodo.12698070</a></p> <p><strong>License</strong></p> <p>Any further use of the data has to comply with the CC BY-NC license: <a href="https://creativecommons.org/licenses/by-nc/4.0/">https://creativecommons.org/licenses/by-nc/4.0/</a></p> </div> <h4>Funding Information:</h4> <div>This work was supported by: <ul> <li>Swiss Data Science Center <a href="https://www.datascience.ch/projects/climis4aval" target="_blank" rel="noopener">(link) </a>(Grant/Award: C21-15L)</li> <li>WSL Institute for Snow and Avalanche Research SLF</li> </ul> </div>
Snow height at the Admunsen-Nobile Climate Change Tower, Svalbard, Norway
<p>The automated station is operating at the Amundsen-Nobile Climate Change Tower since 2010, which is in a tundra site almost flat, located in the Kolhaugen area. The station is part of a complex infrastructure where multi-disciplinary observations are routinely performed.</p>
Snow height at the Gruvebadet Snow Resarch Site (Ny-Ålesund, Svalbard, Norway)
<p>The automated nivological station was installed in November 2020 in a flat area over the tundra about 80 meters far from the Gruvebadet Atmospheric Laboratory and nearby a snow sampling site from where weekly snow samples are collected for chemical analysis. Sensors have been calibrated by their companies before installation and are connected to a datalogger for continuous acquisition. For all the parameters, data are logged with 10-minute time resolution and then averaged over 1 hour.</p>
SnowEx23 Airborne Lidar-Derived 0.5M Snow Depth and Canopy Height V001
This data set provides digital terrain models, snow depth, and canopy height, acquired by a scanning lidar system and derived from Point Cloud Digital Terrain Models (PCDTMs) from two regions of Alaska, USA collected as part of the NASA SnowEx 2023 field campaign. The study sites include a boreal forest environment in the Fairbanks region of central Alaska (the Bonanza Creek Experimental Forest, Caribou Poker Creek watershed, and Farmer’s Loop/Creamer’s Field) and a coastal tundra environment in the North Slope region of the northern Alaska coastal plain (Arctic coastal plain and Upper Kuparuk Toolik). The raw data from which these data are derived are available as <a href="https://nsidc.org/data/SNEX23_Lidar_Raw">SnowEx23 Airborne Lidar Scans Raw, Version 1</a>.
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