Semi-automated tracking of iceberg B43 using Sentinel-1 SAR images via Google Earth Engine

Sentinel-1 C-band synthetic aperture radar (SAR) images can be used to observe the drift of icebergs over the Southern Ocean with around 1–3 d of temporal resolution and 10–40 m of spatial resolution. The Google Earth Engine (GEE) cloud-based platform allows processing of a large quantity of Sentine...

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Published in:The Cryosphere
Main Authors: Y. Koo, H. Xie, S. F. Ackley, A. M. Mestas-Nuñez, G. J. Macdonald, C.-U. Hyun
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2021
Subjects:
geo
Online Access:https://doi.org/10.5194/tc-15-4727-2021
https://tc.copernicus.org/articles/15/4727/2021/tc-15-4727-2021.pdf
https://doaj.org/article/e89898e4f5e74ddda4c15cc93048cacd
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spelling fttriple:oai:gotriple.eu:oai:doaj.org/article:e89898e4f5e74ddda4c15cc93048cacd 2023-05-15T13:24:18+02:00 Semi-automated tracking of iceberg B43 using Sentinel-1 SAR images via Google Earth Engine Y. Koo H. Xie S. F. Ackley A. M. Mestas-Nuñez G. J. Macdonald C.-U. Hyun 2021-10-01 https://doi.org/10.5194/tc-15-4727-2021 https://tc.copernicus.org/articles/15/4727/2021/tc-15-4727-2021.pdf https://doaj.org/article/e89898e4f5e74ddda4c15cc93048cacd en eng Copernicus Publications doi:10.5194/tc-15-4727-2021 1994-0416 1994-0424 https://tc.copernicus.org/articles/15/4727/2021/tc-15-4727-2021.pdf https://doaj.org/article/e89898e4f5e74ddda4c15cc93048cacd undefined The Cryosphere, Vol 15, Pp 4727-4744 (2021) geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2021 fttriple https://doi.org/10.5194/tc-15-4727-2021 2023-01-22T18:10:42Z Sentinel-1 C-band synthetic aperture radar (SAR) images can be used to observe the drift of icebergs over the Southern Ocean with around 1–3 d of temporal resolution and 10–40 m of spatial resolution. The Google Earth Engine (GEE) cloud-based platform allows processing of a large quantity of Sentinel-1 images, saving time and computational resources. In this study, we process Sentinel-1 data via GEE to detect and track the drift of iceberg B43 during its lifespan of 3 years (2017–2020) in the Southern Ocean. First, to detect all candidate icebergs in Sentinel-1 images, we employ an object-based image segmentation (simple non-iterative clustering – SNIC) and a traditional backscatter threshold method. Next, we automatically choose and trace the location of the target iceberg by comparing the centroid distance histograms (CDHs) of all detected icebergs in subsequent days with the CDH of the reference target iceberg. Using this approach, we successfully track iceberg B43 from the Amundsen Sea to the Ross Sea and examine its changes in area, speed, and direction. Three periods with sudden losses of area (i.e., split-offs) coincide with periods of low sea ice concentration, warm air temperature, and high waves. This implies that these variables may be related to mechanisms causing the split-off of the iceberg. Since the iceberg is generally surrounded by compacted sea ice, its drift correlates in part with sea ice motion and wind velocity. Given that the bulk of the iceberg is under water (∼30–60 m freeboard and ∼150–400 m thickness), its motion is predominantly driven by the westward-flowing Antarctic Coastal Current, which dominates the circulation of the region. Considering the complexity of modeling icebergs, there is a demand for a large iceberg database to better understand the behavior of icebergs and their interactions with surrounding environments. The semi-automated iceberg tracking based on the storage capacity and computing power of GEE can be used for this purpose. Article in Journal/Newspaper Amundsen Sea Antarc* Antarctic Iceberg* Ross Sea Sea ice Southern Ocean The Cryosphere Unknown Amundsen Sea Antarctic Ross Sea Southern Ocean The Cryosphere 15 10 4727 4744
institution Open Polar
collection Unknown
op_collection_id fttriple
language English
topic geo
envir
spellingShingle geo
envir
Y. Koo
H. Xie
S. F. Ackley
A. M. Mestas-Nuñez
G. J. Macdonald
C.-U. Hyun
Semi-automated tracking of iceberg B43 using Sentinel-1 SAR images via Google Earth Engine
topic_facet geo
envir
description Sentinel-1 C-band synthetic aperture radar (SAR) images can be used to observe the drift of icebergs over the Southern Ocean with around 1–3 d of temporal resolution and 10–40 m of spatial resolution. The Google Earth Engine (GEE) cloud-based platform allows processing of a large quantity of Sentinel-1 images, saving time and computational resources. In this study, we process Sentinel-1 data via GEE to detect and track the drift of iceberg B43 during its lifespan of 3 years (2017–2020) in the Southern Ocean. First, to detect all candidate icebergs in Sentinel-1 images, we employ an object-based image segmentation (simple non-iterative clustering – SNIC) and a traditional backscatter threshold method. Next, we automatically choose and trace the location of the target iceberg by comparing the centroid distance histograms (CDHs) of all detected icebergs in subsequent days with the CDH of the reference target iceberg. Using this approach, we successfully track iceberg B43 from the Amundsen Sea to the Ross Sea and examine its changes in area, speed, and direction. Three periods with sudden losses of area (i.e., split-offs) coincide with periods of low sea ice concentration, warm air temperature, and high waves. This implies that these variables may be related to mechanisms causing the split-off of the iceberg. Since the iceberg is generally surrounded by compacted sea ice, its drift correlates in part with sea ice motion and wind velocity. Given that the bulk of the iceberg is under water (∼30–60 m freeboard and ∼150–400 m thickness), its motion is predominantly driven by the westward-flowing Antarctic Coastal Current, which dominates the circulation of the region. Considering the complexity of modeling icebergs, there is a demand for a large iceberg database to better understand the behavior of icebergs and their interactions with surrounding environments. The semi-automated iceberg tracking based on the storage capacity and computing power of GEE can be used for this purpose.
format Article in Journal/Newspaper
author Y. Koo
H. Xie
S. F. Ackley
A. M. Mestas-Nuñez
G. J. Macdonald
C.-U. Hyun
author_facet Y. Koo
H. Xie
S. F. Ackley
A. M. Mestas-Nuñez
G. J. Macdonald
C.-U. Hyun
author_sort Y. Koo
title Semi-automated tracking of iceberg B43 using Sentinel-1 SAR images via Google Earth Engine
title_short Semi-automated tracking of iceberg B43 using Sentinel-1 SAR images via Google Earth Engine
title_full Semi-automated tracking of iceberg B43 using Sentinel-1 SAR images via Google Earth Engine
title_fullStr Semi-automated tracking of iceberg B43 using Sentinel-1 SAR images via Google Earth Engine
title_full_unstemmed Semi-automated tracking of iceberg B43 using Sentinel-1 SAR images via Google Earth Engine
title_sort semi-automated tracking of iceberg b43 using sentinel-1 sar images via google earth engine
publisher Copernicus Publications
publishDate 2021
url https://doi.org/10.5194/tc-15-4727-2021
https://tc.copernicus.org/articles/15/4727/2021/tc-15-4727-2021.pdf
https://doaj.org/article/e89898e4f5e74ddda4c15cc93048cacd
geographic Amundsen Sea
Antarctic
Ross Sea
Southern Ocean
geographic_facet Amundsen Sea
Antarctic
Ross Sea
Southern Ocean
genre Amundsen Sea
Antarc*
Antarctic
Iceberg*
Ross Sea
Sea ice
Southern Ocean
The Cryosphere
genre_facet Amundsen Sea
Antarc*
Antarctic
Iceberg*
Ross Sea
Sea ice
Southern Ocean
The Cryosphere
op_source The Cryosphere, Vol 15, Pp 4727-4744 (2021)
op_relation doi:10.5194/tc-15-4727-2021
1994-0416
1994-0424
https://tc.copernicus.org/articles/15/4727/2021/tc-15-4727-2021.pdf
https://doaj.org/article/e89898e4f5e74ddda4c15cc93048cacd
op_rights undefined
op_doi https://doi.org/10.5194/tc-15-4727-2021
container_title The Cryosphere
container_volume 15
container_issue 10
container_start_page 4727
op_container_end_page 4744
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