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dc.contributor.authorGoliber, Sophie
dc.contributor.authorBlack, Taryn
dc.contributor.authorCatania, Ginny
dc.contributor.authorLea, James
dc.contributor.authorOlsen, Helene
dc.contributor.authorCheng, Daniel
dc.contributor.authorBevan, Suzanne
dc.contributor.authorBjork, Anders
dc.contributor.authorBunce, Charlie
dc.contributor.authorBrough, Stephen
dc.contributor.authorCarr, Rachel
dc.contributor.authorCowton, Tom
dc.contributor.authorGardner, Alex
dc.contributor.authorFahrner, Dominik
dc.contributor.authorHill, Emily
dc.contributor.authorJoughin, Ian
dc.contributor.authorKorsgaard, Niels
dc.contributor.authorLuckman, Adrian
dc.contributor.authorMoon, Twila
dc.contributor.authorMurray, Tavi
dc.contributor.authorSole, Andrew
dc.contributor.authorWood, Michael
dc.contributor.authorZhang, Enze
dc.date.accessioned2022-09-01T13:30:01Z
dc.date.available2022-09-01T13:30:01Z
dc.date.issued2022-08-12
dc.identifier.citationGoliber , 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-16-3215-2022en
dc.identifier.issn1994-0416
dc.identifier.otherPURE: 280489410
dc.identifier.otherPURE UUID: 4bf93b28-cfd4-4586-9db3-21f210d5f00f
dc.identifier.otherORCID: /0000-0003-1668-7372/work/118411712
dc.identifier.urihttp://hdl.handle.net/10023/25931
dc.descriptionAuthors acknowledge support from a NASA Earth and Space Sciences fellowship to Sophie Goliber (18-EARTH18F-323) and terminus tracers everywhere. Niels J. Korsgaard was supported by the Programme for Monitoring of the Greenland Ice Sheet (PROMICE). Michael Wood was supported by an appointment to the NASA Postdoctoral Program at the Jet Propulsion Laboratory, California Institute of Technology, administered by the Universities Space Research Association under contract with NASA. James M. Lea is supported by a UKRI Future Leaders Fellowship (grant no. MR/S017232/1). Dominik Fahrner acknowledges support for this study through the EPSRC and ESRC Centre for Doctoral Training on Quantification and Management of Risk and Uncertainty in Complex Systems Environments (grant no. EP/L015927/1). Tavi Murray is funded by the Leverhulme Trust Research Leadership scheme F/00391/J and the UK NERC NE/G010366/1.en
dc.description.abstractMarine-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.
dc.format.extent19
dc.language.isoeng
dc.relation.ispartofThe Cryosphereen
dc.rightsCopyright © Author(s) 2022. Open Access.This work is distributed under the Creative Commons Attribution 4.0 License.en
dc.subjectGB Physical geographyen
dc.subject3rd-DASen
dc.subject.lccGBen
dc.titleTermPicks : a century of Greenland glacier terminus data for use in machine learning applicationsen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. School of Geography & Sustainable Developmenten
dc.contributor.institutionUniversity of St Andrews. Bell-Edwards Geographic Data Instituteen
dc.contributor.institutionUniversity of St Andrews. Environmental Change Research Groupen
dc.identifier.doihttps://doi.org/10.5194/tc-2021-311
dc.description.statusPeer revieweden


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