Automated ArcticDEM iceberg detection tool: insights into area and volume distributions, and their potential application to satellite imagery and modelling of glacier–iceberg–ocean systems
<jats:p>Abstract. Iceberg calving accounts for up to half of mass loss from the Greenland Ice Sheet (GrIS), with their size distributions providing insights into glacier calving dynamics and impacting fjord environments through their melting and subsequent freshwater release. Iceberg area and...
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Language: | English |
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Copernicus GmbH
2023
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Online Access: | http://livrepository.liverpool.ac.uk/3167004/ https://doi.org/10.5194/tc-17-15-2023 |
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ftunivliverpool:oai:livrepository.liverpool.ac.uk:3167004 2023-05-15T15:15:40+02:00 Automated ArcticDEM iceberg detection tool: insights into area and volume distributions, and their potential application to satellite imagery and modelling of glacier–iceberg–ocean systems Shiggins, Connor J Lea, James M Brough, Stephen 2023 http://livrepository.liverpool.ac.uk/3167004/ https://doi.org/10.5194/tc-17-15-2023 en eng Copernicus GmbH Shiggins, Connor J, Lea, James M orcid:0000-0003-1885-0858 and Brough, Stephen orcid:0000-0002-6581-6081 (2023) Automated ArcticDEM iceberg detection tool: insights into area and volume distributions, and their potential application to satellite imagery and modelling of glacier–iceberg–ocean systems. The Cryosphere, 17 (1). pp. 15-32. Article NonPeerReviewed 2023 ftunivliverpool https://doi.org/10.5194/tc-17-15-2023 2023-02-09T23:27:14Z <jats:p>Abstract. Iceberg calving accounts for up to half of mass loss from the Greenland Ice Sheet (GrIS), with their size distributions providing insights into glacier calving dynamics and impacting fjord environments through their melting and subsequent freshwater release. Iceberg area and volume data for the GrIS are currently limited to a handful of fjord locations, while existing approaches to iceberg detection are often time-consuming and are not always suited for long time series analysis over large spatial scales. This study presents a highly automated workflow that detects icebergs and appends their associated metadata within Google Earth Engine using high spatial resolution timestamped ArcticDEM (Arctic Digital Elevation Model) strip data. This is applied to three glaciers that exhibit a range of different iceberg concentrations and size distributions: Sermeq Kujalleq (Jakobshavn Isbræ), Umiammakku Isbræ and Kangiata Nunaata Sermia. A total of 39 ArcticDEM scenes are analysed, detecting a total of 163 738 icebergs with execution times of 6 min to 2 h for each glacier depending on the number of DEMs available and total area analysed, comparing well with the mapping of manually digitised outlines. Results reveal two distinct iceberg distributions at Sermeq Kujalleq and Kangiata Nunaata Sermia where iceberg density is high, and one distribution at Umiammakku Isbræ where iceberg density is low. Small icebergs (< 1000 m2) are found to account for over 80 % of each glacier's icebergs; however, they only contribute to 10 %–37 % of total iceberg volume suggesting that large icebergs are proportionally more important for glacier mass loss and as fjord freshwater reservoirs. The overall dataset is used to construct new area-to-volume conversions (with associated uncertainties) that can be applied elsewhere to two-dimensional iceberg outlines derived from optical or synthetic aperture radar imagery. When data are expressed in terms of total iceberg count and volume, insight is provided into iceberg ... Article in Journal/Newspaper Arctic glacier Greenland Ice Sheet Iceberg* Jakobshavn Jakobshavn isbræ Kujalleq Sermeq Kujalleq The Cryosphere The University of Liverpool Repository Arctic Greenland Jakobshavn Isbræ ENVELOPE(-49.917,-49.917,69.167,69.167) Kujalleq ENVELOPE(-46.037,-46.037,60.719,60.719) Umiammakku Isbræ ENVELOPE(-52.250,-52.250,71.850,71.850) The Cryosphere 17 1 15 32 |
institution |
Open Polar |
collection |
The University of Liverpool Repository |
op_collection_id |
ftunivliverpool |
language |
English |
description |
<jats:p>Abstract. Iceberg calving accounts for up to half of mass loss from the Greenland Ice Sheet (GrIS), with their size distributions providing insights into glacier calving dynamics and impacting fjord environments through their melting and subsequent freshwater release. Iceberg area and volume data for the GrIS are currently limited to a handful of fjord locations, while existing approaches to iceberg detection are often time-consuming and are not always suited for long time series analysis over large spatial scales. This study presents a highly automated workflow that detects icebergs and appends their associated metadata within Google Earth Engine using high spatial resolution timestamped ArcticDEM (Arctic Digital Elevation Model) strip data. This is applied to three glaciers that exhibit a range of different iceberg concentrations and size distributions: Sermeq Kujalleq (Jakobshavn Isbræ), Umiammakku Isbræ and Kangiata Nunaata Sermia. A total of 39 ArcticDEM scenes are analysed, detecting a total of 163 738 icebergs with execution times of 6 min to 2 h for each glacier depending on the number of DEMs available and total area analysed, comparing well with the mapping of manually digitised outlines. Results reveal two distinct iceberg distributions at Sermeq Kujalleq and Kangiata Nunaata Sermia where iceberg density is high, and one distribution at Umiammakku Isbræ where iceberg density is low. Small icebergs (< 1000 m2) are found to account for over 80 % of each glacier's icebergs; however, they only contribute to 10 %–37 % of total iceberg volume suggesting that large icebergs are proportionally more important for glacier mass loss and as fjord freshwater reservoirs. The overall dataset is used to construct new area-to-volume conversions (with associated uncertainties) that can be applied elsewhere to two-dimensional iceberg outlines derived from optical or synthetic aperture radar imagery. When data are expressed in terms of total iceberg count and volume, insight is provided into iceberg ... |
format |
Article in Journal/Newspaper |
author |
Shiggins, Connor J Lea, James M Brough, Stephen |
spellingShingle |
Shiggins, Connor J Lea, James M Brough, Stephen Automated ArcticDEM iceberg detection tool: insights into area and volume distributions, and their potential application to satellite imagery and modelling of glacier–iceberg–ocean systems |
author_facet |
Shiggins, Connor J Lea, James M Brough, Stephen |
author_sort |
Shiggins, Connor J |
title |
Automated ArcticDEM iceberg detection tool: insights into area and volume distributions, and their potential application to satellite imagery and modelling of glacier–iceberg–ocean systems |
title_short |
Automated ArcticDEM iceberg detection tool: insights into area and volume distributions, and their potential application to satellite imagery and modelling of glacier–iceberg–ocean systems |
title_full |
Automated ArcticDEM iceberg detection tool: insights into area and volume distributions, and their potential application to satellite imagery and modelling of glacier–iceberg–ocean systems |
title_fullStr |
Automated ArcticDEM iceberg detection tool: insights into area and volume distributions, and their potential application to satellite imagery and modelling of glacier–iceberg–ocean systems |
title_full_unstemmed |
Automated ArcticDEM iceberg detection tool: insights into area and volume distributions, and their potential application to satellite imagery and modelling of glacier–iceberg–ocean systems |
title_sort |
automated arcticdem iceberg detection tool: insights into area and volume distributions, and their potential application to satellite imagery and modelling of glacier–iceberg–ocean systems |
publisher |
Copernicus GmbH |
publishDate |
2023 |
url |
http://livrepository.liverpool.ac.uk/3167004/ https://doi.org/10.5194/tc-17-15-2023 |
long_lat |
ENVELOPE(-49.917,-49.917,69.167,69.167) ENVELOPE(-46.037,-46.037,60.719,60.719) ENVELOPE(-52.250,-52.250,71.850,71.850) |
geographic |
Arctic Greenland Jakobshavn Isbræ Kujalleq Umiammakku Isbræ |
geographic_facet |
Arctic Greenland Jakobshavn Isbræ Kujalleq Umiammakku Isbræ |
genre |
Arctic glacier Greenland Ice Sheet Iceberg* Jakobshavn Jakobshavn isbræ Kujalleq Sermeq Kujalleq The Cryosphere |
genre_facet |
Arctic glacier Greenland Ice Sheet Iceberg* Jakobshavn Jakobshavn isbræ Kujalleq Sermeq Kujalleq The Cryosphere |
op_relation |
Shiggins, Connor J, Lea, James M orcid:0000-0003-1885-0858 and Brough, Stephen orcid:0000-0002-6581-6081 (2023) Automated ArcticDEM iceberg detection tool: insights into area and volume distributions, and their potential application to satellite imagery and modelling of glacier–iceberg–ocean systems. The Cryosphere, 17 (1). pp. 15-32. |
op_doi |
https://doi.org/10.5194/tc-17-15-2023 |
container_title |
The Cryosphere |
container_volume |
17 |
container_issue |
1 |
container_start_page |
15 |
op_container_end_page |
32 |
_version_ |
1766346020225024000 |