Preprints
https://doi.org/10.5194/tc-2021-311
https://doi.org/10.5194/tc-2021-311

  14 Oct 2021

14 Oct 2021

Review status: this preprint is currently under review for the journal TC.

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

Sophie Goliber1,2, Taryn Black3,4, Ginny Catania1,2, James M. Lea5, Helene Olsen2, Daniel Cheng6, Suzanne Bevan7, Anders Bjørk8, Charlie Bunce9,10, Stephen Brough5, J. Rachel Carr9, Tom Cowton11, Alex Gardner12, Dominik Fahrner5,13, Emily Hill14, Ian Joughin4, Niels Korsgaard15, Adrian Luckman7, Twila Moon16, Tavi Murray7, Andrew Sole17, Michael Wood12, and Enze Zhang18 Sophie Goliber et al.
  • 1Department of Geological Sciences, University of Texas at Austin
  • 2Institute for Geophysics, University of Texas at Austin
  • 3Department of Earth and Space Sciences, University of Washington, Seattle, WA, USA
  • 4Polar Science Center, Applied Physics Laboratory, University of Washington, Seattle, WA, USA
  • 5Department of Geography and Planning, University of Liverpool
  • 6University of California at Irvine, Irvine, CA, USA
  • 7Geography Department, College of Science, Swansea University, Swansea, UK
  • 8Department of Geosciences and Natural Resource Management,University of Copenhagen, Copenhagen, Denmark
  • 9School of Geography, Politics and Sociology, Newcastle University, Newcastle-Upon-Tyne, UK
  • 10School of Geosciences, University of Edinburgh, Edinburgh, UK
  • 11School of Geography and Sustainable Development, University of St Andrews, UK
  • 12Jet Propulsion Laboratory, California Institute of Technology
  • 13Institute for Risk and Uncertainty, University of Liverpool
  • 14Department of Geography and Environmental Sciences, University of Northumbria, Newcastle upon Tyne, United Kingdom
  • 15The Geological Survey of Denmark and Greenland, Østervoldgade 10, 1350 København K, Danmark
  • 16National Snow and Ice Data Center, Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder
  • 17Department of Geography, University of Sheffield, Sheffield, UK
  • 18Earth System Science Programme, The Chinese University of Hong Kong

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 time scales. 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 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 and median number of traces per glacier of 136 ± 190 and 93, respectively. Across all glaciers, 32,567 dates have been picked, of which 4,467 have traces from more than one author (duplication of 14 %). 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.

Sophie Goliber et al.

Status: open (until 09 Dec 2021)

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Sophie Goliber et al.

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TermPicks: A century of Greenland glacier terminus data for use in machine learning applications Sophie Goliber https://doi.org/10.5281/zenodo.5512724

Sophie Goliber et al.

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Short summary
Terminus traces have been used to understand how Greenland's glaciers have changed over time, however, manual tracing is time-intensive and lack of coordination leads to duplication of efforts. We have compiled a dataset of over 39,000 terminus traces for 278 glaciers for scientific and machine learning applications. We also provide an overview of an updated version of The Google Earth Engine Digitization Tool (GEEDiT), which has been developed specifically for the Greenland Ice Sheet.