Articles | Volume 13, issue 6
https://doi.org/10.5194/tc-13-1729-2019
https://doi.org/10.5194/tc-13-1729-2019
Research article
 | 
28 Jun 2019
Research article |  | 28 Jun 2019

Automatically delineating the calving front of Jakobshavn Isbræ from multitemporal TerraSAR-X images: a deep learning approach

Enze Zhang, Lin Liu, and Lingcao Huang

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Enze Zhang on behalf of the Authors (30 Apr 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (14 May 2019) by Stef Lhermitte
RR by Anonymous Referee #2 (19 May 2019)
ED: Publish subject to minor revisions (review by editor) (22 May 2019) by Stef Lhermitte
AR by Enze Zhang on behalf of the Authors (23 May 2019)  Author's response    Manuscript
ED: Publish as is (06 Jun 2019) by Stef Lhermitte
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Short summary
Conventionally, calving front positions have been manually delineated from remote sensing images. We design a novel method to automatically delineate the calving front positions of Jakobshavn Isbræ based on deep learning, the first of this kind for Greenland outlet glaciers. We generate high-temporal-resolution (about two measurements every month) calving fronts, demonstrating our methodology can be applied to many other tidewater glaciers through this successful case study on Jakobshavn Isbræ.