TermPicks:a century of Greenland glacier terminus data for use in machine learning applications

Marine-terminating outlet glacier terminus traces, mapped from satellite and aerial imagery, have been used extensively in understanding how outlet glaciers adjust to climate change variability over a range of timescales. Numerous studies have digitized termini manually, but this process is labor in...

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Main Authors: Goliber, Sophie, Black, Taryn, Catania, Ginny, Lea, James, Olsen, Helene, Cheng, Daniel, Bevan, Suzanne, Bjork, Anders, Bunce, Charlie, Brough, Stephen, Carr, Rachel, Cowton, Tom, Gardner, Alex, Fahrner, Dominik, Hill, Emily, Joughin, Ian, Korsgaard, Niels, Luckman, Adrian, Moon, Twila, Murray, Tavi, Sole, Andrew, Wood, Michael, Zhang, Enze
Format: Article in Journal/Newspaper
Language:English
Published: 2022
Subjects:
Online Access:https://risweb.st-andrews.ac.uk/portal/en/researchoutput/termpicks(4bf93b28-cfd4-4586-9db3-21f210d5f00f).html
https://doi.org/10.5194/tc-2021-311
https://research-repository.st-andrews.ac.uk/bitstream/10023/25931/1/Goliber_2022_Cryosphere_TermPicks_CC.pdf
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spelling ftunstandrewcris:oai:risweb.st-andrews.ac.uk:publications/4bf93b28-cfd4-4586-9db3-21f210d5f00f 2023-05-15T16:21:05+02:00 TermPicks:a century of Greenland glacier terminus data for use in machine learning applications Goliber, Sophie Black, Taryn Catania, Ginny Lea, James Olsen, Helene Cheng, Daniel Bevan, Suzanne Bjork, Anders Bunce, Charlie Brough, Stephen Carr, Rachel Cowton, Tom Gardner, Alex Fahrner, Dominik Hill, Emily Joughin, Ian Korsgaard, Niels Luckman, Adrian Moon, Twila Murray, Tavi Sole, Andrew Wood, Michael Zhang, Enze 2022-08-12 application/pdf https://risweb.st-andrews.ac.uk/portal/en/researchoutput/termpicks(4bf93b28-cfd4-4586-9db3-21f210d5f00f).html https://doi.org/10.5194/tc-2021-311 https://research-repository.st-andrews.ac.uk/bitstream/10023/25931/1/Goliber_2022_Cryosphere_TermPicks_CC.pdf eng eng info:eu-repo/semantics/openAccess Goliber , S , Black , T , Catania , G , Lea , J , Olsen , H , Cheng , D , Bevan , S , Bjork , A , Bunce , C , Brough , S , Carr , R , Cowton , T , Gardner , A , Fahrner , D , Hill , E , Joughin , I , Korsgaard , N , Luckman , A , Moon , T , Murray , T , Sole , A , Wood , M & Zhang , E 2022 , ' TermPicks : a century of Greenland glacier terminus data for use in machine learning applications ' , The Cryosphere , vol. 16 , pp. 3215–3233 . https://doi.org/10.5194/tc-2021-311 , https://doi.org/10.5194/tc-16-3215-2022 article 2022 ftunstandrewcris https://doi.org/10.5194/tc-2021-311 2022-10-13T15:27:18Z Marine-terminating outlet glacier terminus traces, mapped from satellite and aerial imagery, have been used extensively in understanding how outlet glaciers adjust to climate change variability over a range of timescales. Numerous studies have digitized termini manually, but this process is labor intensive, and no consistent approach exists. A lack of coordination leads to duplication of efforts, particularly for Greenland, which is a major scientific research focus. At the same time, machine learning techniques are rapidly making progress in their ability to automate accurate extraction of glacier termini, with promising developments across a number of optical and synthetic aperture radar (SAR) satellite sensors. These techniques rely on high-quality, manually digitized terminus traces to be used as training data for robust automatic traces. Here we present a database of manually digitized terminus traces for machine learning and scientific applications. These data have been collected, cleaned, assigned with appropriate metadata including image scenes, and compiled so they can be easily accessed by scientists. The TermPicks data set includes 39 060 individual terminus traces for 278 glaciers with a mean of 136 ± 190 and median of 93 of traces per glacier. Across all glaciers, 32 567 dates have been digitized, of which 4467 have traces from more than one author, and there is a duplication rate of 17 %. We find a median error of ∼ 100 m among manually traced termini. Most traces are obtained after 1999, when Landsat 7 was launched. We also provide an overview of an updated version of the Google Earth Engine Digitization Tool (GEEDiT), which has been developed specifically for future manual picking of the Greenland Ice Sheet. Article in Journal/Newspaper glacier Greenland Ice Sheet The Cryosphere University of St Andrews: Research Portal Greenland
institution Open Polar
collection University of St Andrews: Research Portal
op_collection_id ftunstandrewcris
language English
description Marine-terminating outlet glacier terminus traces, mapped from satellite and aerial imagery, have been used extensively in understanding how outlet glaciers adjust to climate change variability over a range of timescales. Numerous studies have digitized termini manually, but this process is labor intensive, and no consistent approach exists. A lack of coordination leads to duplication of efforts, particularly for Greenland, which is a major scientific research focus. At the same time, machine learning techniques are rapidly making progress in their ability to automate accurate extraction of glacier termini, with promising developments across a number of optical and synthetic aperture radar (SAR) satellite sensors. These techniques rely on high-quality, manually digitized terminus traces to be used as training data for robust automatic traces. Here we present a database of manually digitized terminus traces for machine learning and scientific applications. These data have been collected, cleaned, assigned with appropriate metadata including image scenes, and compiled so they can be easily accessed by scientists. The TermPicks data set includes 39 060 individual terminus traces for 278 glaciers with a mean of 136 ± 190 and median of 93 of traces per glacier. Across all glaciers, 32 567 dates have been digitized, of which 4467 have traces from more than one author, and there is a duplication rate of 17 %. We find a median error of ∼ 100 m among manually traced termini. Most traces are obtained after 1999, when Landsat 7 was launched. We also provide an overview of an updated version of the Google Earth Engine Digitization Tool (GEEDiT), which has been developed specifically for future manual picking of the Greenland Ice Sheet.
format Article in Journal/Newspaper
author Goliber, Sophie
Black, Taryn
Catania, Ginny
Lea, James
Olsen, Helene
Cheng, Daniel
Bevan, Suzanne
Bjork, Anders
Bunce, Charlie
Brough, Stephen
Carr, Rachel
Cowton, Tom
Gardner, Alex
Fahrner, Dominik
Hill, Emily
Joughin, Ian
Korsgaard, Niels
Luckman, Adrian
Moon, Twila
Murray, Tavi
Sole, Andrew
Wood, Michael
Zhang, Enze
spellingShingle Goliber, Sophie
Black, Taryn
Catania, Ginny
Lea, James
Olsen, Helene
Cheng, Daniel
Bevan, Suzanne
Bjork, Anders
Bunce, Charlie
Brough, Stephen
Carr, Rachel
Cowton, Tom
Gardner, Alex
Fahrner, Dominik
Hill, Emily
Joughin, Ian
Korsgaard, Niels
Luckman, Adrian
Moon, Twila
Murray, Tavi
Sole, Andrew
Wood, Michael
Zhang, Enze
TermPicks:a century of Greenland glacier terminus data for use in machine learning applications
author_facet Goliber, Sophie
Black, Taryn
Catania, Ginny
Lea, James
Olsen, Helene
Cheng, Daniel
Bevan, Suzanne
Bjork, Anders
Bunce, Charlie
Brough, Stephen
Carr, Rachel
Cowton, Tom
Gardner, Alex
Fahrner, Dominik
Hill, Emily
Joughin, Ian
Korsgaard, Niels
Luckman, Adrian
Moon, Twila
Murray, Tavi
Sole, Andrew
Wood, Michael
Zhang, Enze
author_sort Goliber, Sophie
title TermPicks:a century of Greenland glacier terminus data for use in machine learning applications
title_short TermPicks:a century of Greenland glacier terminus data for use in machine learning applications
title_full TermPicks:a century of Greenland glacier terminus data for use in machine learning applications
title_fullStr TermPicks:a century of Greenland glacier terminus data for use in machine learning applications
title_full_unstemmed TermPicks:a century of Greenland glacier terminus data for use in machine learning applications
title_sort termpicks:a century of greenland glacier terminus data for use in machine learning applications
publishDate 2022
url https://risweb.st-andrews.ac.uk/portal/en/researchoutput/termpicks(4bf93b28-cfd4-4586-9db3-21f210d5f00f).html
https://doi.org/10.5194/tc-2021-311
https://research-repository.st-andrews.ac.uk/bitstream/10023/25931/1/Goliber_2022_Cryosphere_TermPicks_CC.pdf
geographic Greenland
geographic_facet Greenland
genre glacier
Greenland
Ice Sheet
The Cryosphere
genre_facet glacier
Greenland
Ice Sheet
The Cryosphere
op_source Goliber , S , Black , T , Catania , G , Lea , J , Olsen , H , Cheng , D , Bevan , S , Bjork , A , Bunce , C , Brough , S , Carr , R , Cowton , T , Gardner , A , Fahrner , D , Hill , E , Joughin , I , Korsgaard , N , Luckman , A , Moon , T , Murray , T , Sole , A , Wood , M & Zhang , E 2022 , ' TermPicks : a century of Greenland glacier terminus data for use in machine learning applications ' , The Cryosphere , vol. 16 , pp. 3215–3233 . https://doi.org/10.5194/tc-2021-311 , https://doi.org/10.5194/tc-16-3215-2022
op_rights info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.5194/tc-2021-311
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