Articles | Volume 16, issue 8
https://doi.org/10.5194/tc-16-3215-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-3215-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
TermPicks: a century of Greenland glacier terminus data for use in scientific and machine learning applications
Sophie Goliber
CORRESPONDING AUTHOR
Department of Geological Sciences, University of Texas at Austin, Austin, TX, USA
Institute for Geophysics, University of Texas at Austin, Austin, TX, USA
Taryn Black
Department of Earth and Space Sciences, University of Washington, Seattle, WA, USA
Polar Science Center, Applied Physics Laboratory, University of Washington, Seattle, WA, USA
Ginny Catania
Department of Geological Sciences, University of Texas at Austin, Austin, TX, USA
Institute for Geophysics, University of Texas at Austin, Austin, TX, USA
James M. Lea
Department of Geography and Planning, University of Liverpool, Liverpool, UK
Helene Olsen
Institute for Geophysics, University of Texas at Austin, Austin, TX, USA
Daniel Cheng
Department of Computer Science, University of California at Irvine, Irvine, CA, USA
Suzanne Bevan
Geography Department, College of Science, Swansea University, Swansea, UK
Anders Bjørk
Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
Charlie Bunce
School of Geography, Politics and Sociology, Newcastle University, Newcastle upon Tyne, UK
School of Geosciences, University of Edinburgh, Edinburgh, UK
Stephen Brough
Department of Geography and Planning, University of Liverpool, Liverpool, UK
J. Rachel Carr
School of Geography, Politics and Sociology, Newcastle University, Newcastle upon Tyne, UK
Tom Cowton
School of Geography and Sustainable Development, University of St Andrews, St Andrews, UK
Alex Gardner
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Dominik Fahrner
Department of Geography and Planning, University of Liverpool, Liverpool, UK
Institute for Risk and Uncertainty, University of Liverpool, Liverpool, UK
Emily Hill
Department of Geography and Environmental Sciences, University of Northumbria, Newcastle upon Tyne, UK
Ian Joughin
Polar Science Center, Applied Physics Laboratory, University of Washington, Seattle, WA, USA
Niels J. Korsgaard
The Geological Survey of Denmark and Greenland, Østervoldgade 10, 1350 København K, Copenhagen, Denmark
Adrian Luckman
Geography Department, College of Science, Swansea University, Swansea, UK
Twila Moon
National Snow and Ice Data Center, Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA
Tavi Murray
Geography Department, College of Science, Swansea University, Swansea, UK
Andrew Sole
Department of Geography, University of Sheffield, Sheffield, UK
Michael Wood
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Enze Zhang
Earth System Science Programme, The Chinese University of Hong Kong, Hong Kong SAR, China
Data sets
TermPicks: A century of Greenland glacier terminus data for use in machine learning applications Sophie Goliber and Taryn Black https://doi.org/10.5281/zenodo.6557981
Model code and software
goliber/TermPicks: (v1.0.0) Sophie Goliber https://doi.org/10.5281/zenodo.6954113
Co-editor-in-chief
Goliber et al. present a rich new dataset for the lengths of 278 glaciers around Greenland. This dataset, "TermPicks", contains 39,060 detailed traces of the edges of these glaciers, where ice meets ocean. TermPicks spans the entire satellite record (1970s-present), with air photo coverage for some glaciers going back >100 years to 1916. TermPicks is designed for use as training data in machine learning applications, which are the future of the tedious "terminus picking" work that has largely been performed by students to date. Thus, TermPicks will facilitate a significant leap forward in Greenland glacier research by facilitating machine-learning-enabled analysis of the continual high-flux, big-data output of high-resolution imagery by our international constellation of earth-observing satellites.
Goliber et al. present a rich new dataset for the lengths of 278 glaciers around Greenland. This...
Short summary
Terminus traces have been used to understand how Greenland's glaciers have changed over time; however, manual digitization is time-intensive, and a 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.
Terminus traces have been used to understand how Greenland's glaciers have changed over time;...