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...
Published in: | The Cryosphere |
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Language: | English |
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Copernicus Publications
2021
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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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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 |
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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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1766378663395196928 |