High-resolution sea ice drift and deformation example data derived from Sentinel-1 in the Arctic Ocean during MOSAiC

This data set contains two high-resolution sea ice drift and deformation fields from 30/31 December 2019 and 20/21 June 2021. They were acquired in the Transpolar Drift along the drift track of the research campaign "Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC...

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Main Author: von Albedyll, Luisa
Format: Dataset
Language:unknown
Published: 2021
Subjects:
Online Access:https://zenodo.org/record/5195366
https://doi.org/10.5281/zenodo.5195366
id ftzenodo:oai:zenodo.org:5195366
record_format openpolar
spelling ftzenodo:oai:zenodo.org:5195366 2023-05-15T15:03:34+02:00 High-resolution sea ice drift and deformation example data derived from Sentinel-1 in the Arctic Ocean during MOSAiC von Albedyll, Luisa 2021-08-13 https://zenodo.org/record/5195366 https://doi.org/10.5281/zenodo.5195366 unknown doi:10.5281/zenodo.5195365 https://zenodo.org/record/5195366 https://doi.org/10.5281/zenodo.5195366 oai:zenodo.org:5195366 info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode sea ice sea ice deformation sea ice drift remote sensing Sentinel-1 info:eu-repo/semantics/other dataset 2021 ftzenodo https://doi.org/10.5281/zenodo.519536610.5281/zenodo.5195365 2023-03-11T00:50:18Z This data set contains two high-resolution sea ice drift and deformation fields from 30/31 December 2019 and 20/21 June 2021. They were acquired in the Transpolar Drift along the drift track of the research campaign "Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC). Drift fields were calculated from Sentinel-1, HH polarization SAR images acquired in enhanced wide mode. These had a pixel resolution of 50 m in Polar Stereographic North projection (latitude of true scale: 70 N, center longitude: 45 W). We used an ice tracking algorithm introduced by Thomas et al. (2008, 2011) and modified by Hollands and Dierking (2011) to derive drift from sequential pairs. The time step between two sequential images is approximately one day. The resulting drift data set was defined on a regular grid with a spatial resolution of 700 m. Outliers in the velocity data were reduced by a 3x3 point running median filter covering an area of 2.1x2.1 km. For the deformation estimates, we calculated deformation using a linear approximation based on Green's Theorem that relates the double integral over a plane to the line integral along a simple curve surrounding the plane. We discretized the curve applying the trapezoid method that linearly interpolates velocity between the vertices of the grid cells. This work contains modified Copernicus Sentinel data (2020) Related publications: von Albedyll, L., Haas, C., and Dierking, W.: Linking sea ice deformation to ice thickness redistribution using high-resolution satellite and airborne observations, The Cryosphere, 15, 2167–2186, https://doi.org/10.5194/tc-15-2167-2021, 2021. Hollands, Thomas; Dierking, Wolfgang (2011): Performance of a multiscale correlation algorithm for the estimation of sea-ice drift from SAR images: initial results. Annals of Glaciology, 52(57), 311-317, https://doi.org/10.3189/172756411795931462 Thomas, Mani; Geiger, Cathleen A; Kambhamettu, Chandra (2008): High resolution (400 m) motion characterization of sea ice using ERS-1 SAR imagery. ... Dataset Arctic Arctic Ocean Sea ice Zenodo Arctic Arctic Ocean Geiger ENVELOPE(-62.900,-62.900,-64.300,-64.300)
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language unknown
topic sea ice
sea ice deformation
sea ice drift
remote sensing
Sentinel-1
spellingShingle sea ice
sea ice deformation
sea ice drift
remote sensing
Sentinel-1
von Albedyll, Luisa
High-resolution sea ice drift and deformation example data derived from Sentinel-1 in the Arctic Ocean during MOSAiC
topic_facet sea ice
sea ice deformation
sea ice drift
remote sensing
Sentinel-1
description This data set contains two high-resolution sea ice drift and deformation fields from 30/31 December 2019 and 20/21 June 2021. They were acquired in the Transpolar Drift along the drift track of the research campaign "Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC). Drift fields were calculated from Sentinel-1, HH polarization SAR images acquired in enhanced wide mode. These had a pixel resolution of 50 m in Polar Stereographic North projection (latitude of true scale: 70 N, center longitude: 45 W). We used an ice tracking algorithm introduced by Thomas et al. (2008, 2011) and modified by Hollands and Dierking (2011) to derive drift from sequential pairs. The time step between two sequential images is approximately one day. The resulting drift data set was defined on a regular grid with a spatial resolution of 700 m. Outliers in the velocity data were reduced by a 3x3 point running median filter covering an area of 2.1x2.1 km. For the deformation estimates, we calculated deformation using a linear approximation based on Green's Theorem that relates the double integral over a plane to the line integral along a simple curve surrounding the plane. We discretized the curve applying the trapezoid method that linearly interpolates velocity between the vertices of the grid cells. This work contains modified Copernicus Sentinel data (2020) Related publications: von Albedyll, L., Haas, C., and Dierking, W.: Linking sea ice deformation to ice thickness redistribution using high-resolution satellite and airborne observations, The Cryosphere, 15, 2167–2186, https://doi.org/10.5194/tc-15-2167-2021, 2021. Hollands, Thomas; Dierking, Wolfgang (2011): Performance of a multiscale correlation algorithm for the estimation of sea-ice drift from SAR images: initial results. Annals of Glaciology, 52(57), 311-317, https://doi.org/10.3189/172756411795931462 Thomas, Mani; Geiger, Cathleen A; Kambhamettu, Chandra (2008): High resolution (400 m) motion characterization of sea ice using ERS-1 SAR imagery. ...
format Dataset
author von Albedyll, Luisa
author_facet von Albedyll, Luisa
author_sort von Albedyll, Luisa
title High-resolution sea ice drift and deformation example data derived from Sentinel-1 in the Arctic Ocean during MOSAiC
title_short High-resolution sea ice drift and deformation example data derived from Sentinel-1 in the Arctic Ocean during MOSAiC
title_full High-resolution sea ice drift and deformation example data derived from Sentinel-1 in the Arctic Ocean during MOSAiC
title_fullStr High-resolution sea ice drift and deformation example data derived from Sentinel-1 in the Arctic Ocean during MOSAiC
title_full_unstemmed High-resolution sea ice drift and deformation example data derived from Sentinel-1 in the Arctic Ocean during MOSAiC
title_sort high-resolution sea ice drift and deformation example data derived from sentinel-1 in the arctic ocean during mosaic
publishDate 2021
url https://zenodo.org/record/5195366
https://doi.org/10.5281/zenodo.5195366
long_lat ENVELOPE(-62.900,-62.900,-64.300,-64.300)
geographic Arctic
Arctic Ocean
Geiger
geographic_facet Arctic
Arctic Ocean
Geiger
genre Arctic
Arctic Ocean
Sea ice
genre_facet Arctic
Arctic Ocean
Sea ice
op_relation doi:10.5281/zenodo.5195365
https://zenodo.org/record/5195366
https://doi.org/10.5281/zenodo.5195366
oai:zenodo.org:5195366
op_rights info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/4.0/legalcode
op_doi https://doi.org/10.5281/zenodo.519536610.5281/zenodo.5195365
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