Articles | Volume 15, issue 3
The Cryosphere, 15, 1663–1675, 2021
https://doi.org/10.5194/tc-15-1663-2021
The Cryosphere, 15, 1663–1675, 2021
https://doi.org/10.5194/tc-15-1663-2021

Research article 01 Apr 2021

Research article | 01 Apr 2021

Calving Front Machine (CALFIN): glacial termini dataset and automated deep learning extraction method for Greenland, 1972–2019

Daniel Cheng et al.

Download

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by editor and referees) (18 Jan 2021) by Stef Lhermitte
AR by Daniel Cheng on behalf of the Authors (18 Jan 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (18 Jan 2021) by Stef Lhermitte
RR by Anonymous Referee #2 (20 Jan 2021)
RR by Anonymous Referee #1 (25 Jan 2021)
ED: Publish subject to minor revisions (review by editor) (28 Jan 2021) by Stef Lhermitte
AR by Daniel Cheng on behalf of the Authors (10 Feb 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (10 Feb 2021) by Stef Lhermitte
Download
Short summary
Tracking changes in Greenland's glaciers is important for understanding Earth's climate, but it is time consuming to do so by hand. We train a program, called CALFIN, to automatically track these changes with human levels of accuracy. CALFIN is a special type of program called a neural network. This method can be applied to other glaciers and eventually other tracking tasks. This will enhance our understanding of the Greenland Ice Sheet and permit better models of Earth's climate.