1 km sea-ice concentration from Sentinel-2 reflectances in the Arctic marginal seas between February and May 2019 ...
This dataset comprises quality-checked sea-ice concentration at 1 km spatial resolution from Sentinel-2 imagery. 83 Sentinel-2 scenes distributed over the East Siberian, Laptev, Kara, Barents and Beaufort Seas as well as the Fram Strait between February and May 2019 are analysed. For each scene, we...
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Online Access: | https://dx.doi.org/10.1594/pangaea.933913 https://doi.pangaea.de/10.1594/PANGAEA.933913 |
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ftdatacite:10.1594/pangaea.933913 2024-02-27T08:37:33+00:00 1 km sea-ice concentration from Sentinel-2 reflectances in the Arctic marginal seas between February and May 2019 ... Ludwig, Valentin Spreen, Gunnar Pedersen, Leif Toudal 2021 application/zip https://dx.doi.org/10.1594/pangaea.933913 https://doi.pangaea.de/10.1594/PANGAEA.933913 en eng PANGAEA https://dx.doi.org/10.3390/rs12193183 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 Sea-ice concentration Sentinel-2 optical Arctic satellite reflectance Processes and impacts of climate change in the North Atlantic Ocean and the Canadian Arctic ArcTrain dataset Dataset 2021 ftdatacite https://doi.org/10.1594/pangaea.93391310.3390/rs12193183 2024-02-01T14:42:11Z This dataset comprises quality-checked sea-ice concentration at 1 km spatial resolution from Sentinel-2 imagery. 83 Sentinel-2 scenes distributed over the East Siberian, Laptev, Kara, Barents and Beaufort Seas as well as the Fram Strait between February and May 2019 are analysed. For each scene, we investigated histograms of the Level 1C (L1C) reflectance of band 4 (665 nm) at 10 m resolution and manually identified two thresholds for each scene to separate it into water, thin ice and thick ice. We use the classified water/thin-ice/thick-ice images to create two sea-ice concentration datasets at 1 km spatial resolution: One which contains the thin ice (sic_thin in the netCDF files) and one which contains the thick ice (sic_thick in the netCDF files). To this end, we average the images over 100x100 pixels and interpret the ratio of sea-ice pixels within these 100x100 pixel windows as sea-ice concentration. The total sea-ice concentration can be obtained as the sum of sic_thin and sic_thick. The ice thickness ... Dataset Arctic Climate change Fram Strait laptev North Atlantic Sea ice DataCite Metadata Store (German National Library of Science and Technology) Arctic |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
topic |
Sea-ice concentration Sentinel-2 optical Arctic satellite reflectance Processes and impacts of climate change in the North Atlantic Ocean and the Canadian Arctic ArcTrain |
spellingShingle |
Sea-ice concentration Sentinel-2 optical Arctic satellite reflectance Processes and impacts of climate change in the North Atlantic Ocean and the Canadian Arctic ArcTrain Ludwig, Valentin Spreen, Gunnar Pedersen, Leif Toudal 1 km sea-ice concentration from Sentinel-2 reflectances in the Arctic marginal seas between February and May 2019 ... |
topic_facet |
Sea-ice concentration Sentinel-2 optical Arctic satellite reflectance Processes and impacts of climate change in the North Atlantic Ocean and the Canadian Arctic ArcTrain |
description |
This dataset comprises quality-checked sea-ice concentration at 1 km spatial resolution from Sentinel-2 imagery. 83 Sentinel-2 scenes distributed over the East Siberian, Laptev, Kara, Barents and Beaufort Seas as well as the Fram Strait between February and May 2019 are analysed. For each scene, we investigated histograms of the Level 1C (L1C) reflectance of band 4 (665 nm) at 10 m resolution and manually identified two thresholds for each scene to separate it into water, thin ice and thick ice. We use the classified water/thin-ice/thick-ice images to create two sea-ice concentration datasets at 1 km spatial resolution: One which contains the thin ice (sic_thin in the netCDF files) and one which contains the thick ice (sic_thick in the netCDF files). To this end, we average the images over 100x100 pixels and interpret the ratio of sea-ice pixels within these 100x100 pixel windows as sea-ice concentration. The total sea-ice concentration can be obtained as the sum of sic_thin and sic_thick. The ice thickness ... |
format |
Dataset |
author |
Ludwig, Valentin Spreen, Gunnar Pedersen, Leif Toudal |
author_facet |
Ludwig, Valentin Spreen, Gunnar Pedersen, Leif Toudal |
author_sort |
Ludwig, Valentin |
title |
1 km sea-ice concentration from Sentinel-2 reflectances in the Arctic marginal seas between February and May 2019 ... |
title_short |
1 km sea-ice concentration from Sentinel-2 reflectances in the Arctic marginal seas between February and May 2019 ... |
title_full |
1 km sea-ice concentration from Sentinel-2 reflectances in the Arctic marginal seas between February and May 2019 ... |
title_fullStr |
1 km sea-ice concentration from Sentinel-2 reflectances in the Arctic marginal seas between February and May 2019 ... |
title_full_unstemmed |
1 km sea-ice concentration from Sentinel-2 reflectances in the Arctic marginal seas between February and May 2019 ... |
title_sort |
1 km sea-ice concentration from sentinel-2 reflectances in the arctic marginal seas between february and may 2019 ... |
publisher |
PANGAEA |
publishDate |
2021 |
url |
https://dx.doi.org/10.1594/pangaea.933913 https://doi.pangaea.de/10.1594/PANGAEA.933913 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Climate change Fram Strait laptev North Atlantic Sea ice |
genre_facet |
Arctic Climate change Fram Strait laptev North Atlantic Sea ice |
op_relation |
https://dx.doi.org/10.3390/rs12193183 |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_doi |
https://doi.org/10.1594/pangaea.93391310.3390/rs12193183 |
_version_ |
1792044538481606656 |