Retrieve Ice Velocities and Invert Spatial Rigidity of the Larsen C Ice Shelf Based on Sentinel-1 Interferometric Data

The Larsen C Ice Shelf (LCIS) is the largest ice shelf in the Antarctica Peninsula, and its state can be considered to be an indicator of local climate change. The goal of this paper is to invert the rigidity of the LCIS based on the interferometric synthetic aperture radar (InSAR) technique using S...

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Published in:Remote Sensing
Main Authors: Faming Gong, Kui Zhang, Shujun Liu
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2021
Subjects:
Online Access:https://doi.org/10.3390/rs13122361
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spelling ftmdpi:oai:mdpi.com:/2072-4292/13/12/2361/ 2023-08-20T04:01:57+02:00 Retrieve Ice Velocities and Invert Spatial Rigidity of the Larsen C Ice Shelf Based on Sentinel-1 Interferometric Data Faming Gong Kui Zhang Shujun Liu agris 2021-06-17 application/pdf https://doi.org/10.3390/rs13122361 EN eng Multidisciplinary Digital Publishing Institute Engineering Remote Sensing https://dx.doi.org/10.3390/rs13122361 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 13; Issue 12; Pages: 2361 InSAR ice velocity field Sentinel-1 images missing data recovering ice rigidity inversion Text 2021 ftmdpi https://doi.org/10.3390/rs13122361 2023-08-01T01:58:08Z The Larsen C Ice Shelf (LCIS) is the largest ice shelf in the Antarctica Peninsula, and its state can be considered to be an indicator of local climate change. The goal of this paper is to invert the rigidity of the LCIS based on the interferometric synthetic aperture radar (InSAR) technique using Sentinel-1 images. A targeted processing chain is first used to obtain reliable interferometric phase measurements under the circumstance of rapid ice flow. Unfortunately, only the descending data are available, which disallows the corresponding 2-D velocity field to be directly obtained from such measurements. A new approach is thus proposed to estimate the interferometric phase-based 2-D velocity field with the assistance of speckle tracking offsets. This approach establishes an implicit relationship between range and azimuth displacements based on speckle tracking observations. By taking advantage of such a relationship, the equivalent interferometric signals in the azimuth direction are estimated, thereby recovering the interferometric phase-based 2-D ice velocity field of the LCIS. To further investigate the state of the LCIS, the recovered 2-D velocity field is utilized to invert the ice rigidity. The shallow-shelf approximation (SSA) is the core of the reverse model, which is closely dependent on boundary conditions, including kinematic and dynamic conditions. The experimental results demonstrate that the spatial distribution of the rigidity varies approximately from 70 MPa·s1/3 to 300 MPa·s1/3. This rigidity distribution can reproduce a similar ice flow pattern to the observations. Text Antarc* Antarctica Ice Shelf MDPI Open Access Publishing Remote Sensing 13 12 2361
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic InSAR
ice velocity field
Sentinel-1 images
missing data recovering
ice rigidity inversion
spellingShingle InSAR
ice velocity field
Sentinel-1 images
missing data recovering
ice rigidity inversion
Faming Gong
Kui Zhang
Shujun Liu
Retrieve Ice Velocities and Invert Spatial Rigidity of the Larsen C Ice Shelf Based on Sentinel-1 Interferometric Data
topic_facet InSAR
ice velocity field
Sentinel-1 images
missing data recovering
ice rigidity inversion
description The Larsen C Ice Shelf (LCIS) is the largest ice shelf in the Antarctica Peninsula, and its state can be considered to be an indicator of local climate change. The goal of this paper is to invert the rigidity of the LCIS based on the interferometric synthetic aperture radar (InSAR) technique using Sentinel-1 images. A targeted processing chain is first used to obtain reliable interferometric phase measurements under the circumstance of rapid ice flow. Unfortunately, only the descending data are available, which disallows the corresponding 2-D velocity field to be directly obtained from such measurements. A new approach is thus proposed to estimate the interferometric phase-based 2-D velocity field with the assistance of speckle tracking offsets. This approach establishes an implicit relationship between range and azimuth displacements based on speckle tracking observations. By taking advantage of such a relationship, the equivalent interferometric signals in the azimuth direction are estimated, thereby recovering the interferometric phase-based 2-D ice velocity field of the LCIS. To further investigate the state of the LCIS, the recovered 2-D velocity field is utilized to invert the ice rigidity. The shallow-shelf approximation (SSA) is the core of the reverse model, which is closely dependent on boundary conditions, including kinematic and dynamic conditions. The experimental results demonstrate that the spatial distribution of the rigidity varies approximately from 70 MPa·s1/3 to 300 MPa·s1/3. This rigidity distribution can reproduce a similar ice flow pattern to the observations.
format Text
author Faming Gong
Kui Zhang
Shujun Liu
author_facet Faming Gong
Kui Zhang
Shujun Liu
author_sort Faming Gong
title Retrieve Ice Velocities and Invert Spatial Rigidity of the Larsen C Ice Shelf Based on Sentinel-1 Interferometric Data
title_short Retrieve Ice Velocities and Invert Spatial Rigidity of the Larsen C Ice Shelf Based on Sentinel-1 Interferometric Data
title_full Retrieve Ice Velocities and Invert Spatial Rigidity of the Larsen C Ice Shelf Based on Sentinel-1 Interferometric Data
title_fullStr Retrieve Ice Velocities and Invert Spatial Rigidity of the Larsen C Ice Shelf Based on Sentinel-1 Interferometric Data
title_full_unstemmed Retrieve Ice Velocities and Invert Spatial Rigidity of the Larsen C Ice Shelf Based on Sentinel-1 Interferometric Data
title_sort retrieve ice velocities and invert spatial rigidity of the larsen c ice shelf based on sentinel-1 interferometric data
publisher Multidisciplinary Digital Publishing Institute
publishDate 2021
url https://doi.org/10.3390/rs13122361
op_coverage agris
genre Antarc*
Antarctica
Ice Shelf
genre_facet Antarc*
Antarctica
Ice Shelf
op_source Remote Sensing; Volume 13; Issue 12; Pages: 2361
op_relation Engineering Remote Sensing
https://dx.doi.org/10.3390/rs13122361
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs13122361
container_title Remote Sensing
container_volume 13
container_issue 12
container_start_page 2361
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