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...
Main Author: | |
---|---|
Format: | Dataset |
Language: | unknown |
Published: |
Zenodo
2021
|
Subjects: | |
Online Access: | https://dx.doi.org/10.5281/zenodo.5195365 https://zenodo.org/record/5195365 |
id |
ftdatacite:10.5281/zenodo.5195365 |
---|---|
record_format |
openpolar |
spelling |
ftdatacite:10.5281/zenodo.5195365 2023-05-15T15:04:53+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 https://dx.doi.org/10.5281/zenodo.5195365 https://zenodo.org/record/5195365 unknown Zenodo https://dx.doi.org/10.5281/zenodo.5195366 Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess CC-BY sea ice sea ice deformation sea ice drift remote sensing Sentinel-1 dataset Dataset 2021 ftdatacite https://doi.org/10.5281/zenodo.5195365 https://doi.org/10.5281/zenodo.5195366 2021-11-05T12:55:41Z 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. Cold Regions Science and Technology , 52(2) , 207-223, https://doi.org/10.1016/j.coldregions.2007.06.006 Thomas, Mani; Kambhamettu, Chandra; Geiger, Cathleen A (2011): Motion Tracking of Discontinuous Sea Ice. IEEE Transactions on Geoscience and Remote Sensing , 49(12) , 5064-5079, https://doi.org/10.1109/TGRS.2011.2158005 Dataset Arctic Arctic Ocean Sea ice DataCite Metadata Store (German National Library of Science and Technology) Arctic Arctic Ocean Geiger ENVELOPE(-62.900,-62.900,-64.300,-64.300) |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
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. Cold Regions Science and Technology , 52(2) , 207-223, https://doi.org/10.1016/j.coldregions.2007.06.006 Thomas, Mani; Kambhamettu, Chandra; Geiger, Cathleen A (2011): Motion Tracking of Discontinuous Sea Ice. IEEE Transactions on Geoscience and Remote Sensing , 49(12) , 5064-5079, https://doi.org/10.1109/TGRS.2011.2158005 |
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 |
publisher |
Zenodo |
publishDate |
2021 |
url |
https://dx.doi.org/10.5281/zenodo.5195365 https://zenodo.org/record/5195365 |
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 |
https://dx.doi.org/10.5281/zenodo.5195366 |
op_rights |
Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.5281/zenodo.5195365 https://doi.org/10.5281/zenodo.5195366 |
_version_ |
1766336633929465856 |