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

  • Sophie Goliber
  • , Taryn Black
  • , Ginny Catania
  • , James M. Lea
  • , Helene Olsen
  • , Daniel Cheng
  • , Suzanne Bevan
  • , Anders Bjørk
  • , Charlie Bunce
  • , Stephen Brough
  • , J. Rachel Carr
  • , Tom Cowton
  • , Alex Gardner
  • , Dominik Fahrner
  • , Emily Hill
  • , Ian Joughin
  • , Niels J. Korsgaard
  • , Adrian Luckman
  • , Twila Moon
  • , Tavi Murray
  • Andrew Sole, Michael Wood, Enze Zhang
  • University of Washington
  • University of Texas at Austin
  • University of Liverpool
  • University of California at Irvine
  • Swansea University
  • University of Copenhagen
  • Newcastle University
  • University of Edinburgh
  • University of St Andrews
  • Jet Propulsion Laboratory, California Institute of Technology
  • Northumbria University
  • Geological Survey of Denmark and Greenland
  • University of Colorado Boulder
  • University of Sheffield
  • Chinese University of Hong Kong

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)3215-3233
Number of pages19
JournalCryosphere
Volume16
Issue number8
DOIs
StatePublished - Aug 12 2022

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