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

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...

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Published in:The Cryosphere
Main Authors: C. J. Shiggins, J. M. Lea, S. Brough
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2023
Subjects:
Online Access:https://doi.org/10.5194/tc-17-15-2023
https://doaj.org/article/a27424f87b6945f98d82d68aa467ccc0
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spelling ftdoajarticles:oai:doaj.org/article:a27424f87b6945f98d82d68aa467ccc0 2023-05-15T15:15:21+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 C. J. Shiggins J. M. Lea S. Brough 2023-01-01T00:00:00Z https://doi.org/10.5194/tc-17-15-2023 https://doaj.org/article/a27424f87b6945f98d82d68aa467ccc0 EN eng Copernicus Publications https://tc.copernicus.org/articles/17/15/2023/tc-17-15-2023.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-17-15-2023 1994-0416 1994-0424 https://doaj.org/article/a27424f87b6945f98d82d68aa467ccc0 The Cryosphere, Vol 17, Pp 15-32 (2023) Environmental sciences GE1-350 Geology QE1-996.5 article 2023 ftdoajarticles https://doi.org/10.5194/tc-17-15-2023 2023-01-15T01:29:07Z 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 m 2 ) 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 distributions that have ... Article in Journal/Newspaper Arctic glacier Greenland Ice Sheet Iceberg* Jakobshavn Jakobshavn isbræ Kujalleq Sermeq Kujalleq The Cryosphere Directory of Open Access Journals: DOAJ Articles 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 Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Environmental sciences
GE1-350
Geology
QE1-996.5
spellingShingle Environmental sciences
GE1-350
Geology
QE1-996.5
C. J. Shiggins
J. M. Lea
S. Brough
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
topic_facet Environmental sciences
GE1-350
Geology
QE1-996.5
description 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 m 2 ) 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 distributions that have ...
format Article in Journal/Newspaper
author C. J. Shiggins
J. M. Lea
S. Brough
author_facet C. J. Shiggins
J. M. Lea
S. Brough
author_sort C. J. Shiggins
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 Publications
publishDate 2023
url https://doi.org/10.5194/tc-17-15-2023
https://doaj.org/article/a27424f87b6945f98d82d68aa467ccc0
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_source The Cryosphere, Vol 17, Pp 15-32 (2023)
op_relation https://tc.copernicus.org/articles/17/15/2023/tc-17-15-2023.pdf
https://doaj.org/toc/1994-0416
https://doaj.org/toc/1994-0424
doi:10.5194/tc-17-15-2023
1994-0416
1994-0424
https://doaj.org/article/a27424f87b6945f98d82d68aa467ccc0
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
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