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...
Main Authors: | , , , , , , , , , , , , , , , , , , , , , , |
---|---|
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 |
id |
ftunstandrewcris:oai:risweb.st-andrews.ac.uk:publications/4bf93b28-cfd4-4586-9db3-21f210d5f00f |
---|---|
record_format |
openpolar |
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 |
_version_ |
1766009106310627328 |