The Cryosphere
The Cryosphere
TC
Articles | Volume 13, issue 6
Articles | Volume 13, issue 6
https://doi.org/10.5194/tc-13-1729-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-13-1729-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 13, issue 6
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

Supplement

https://doi.org/10.5194/tc-13-1729-2019-supplement

Data sets

The calving fronts delineated by the network in Jakobshavn Isbræ Enze Zhang, Lin Liu, and Lingcao Huang https://doi.pangaea.de/10.1594/PANGAEA.897064

Video supplement

Calving front variations in Jakobshavn Isbræ Enze Zhang, Lin Liu, and Lingcao Huang https://doi.org/10.1594/PANGAEA.897062

The comparison between calving front variations and bed elevation of Branch A in Jakobshavn Isbræ Enze Zhang, Lin Liu, and Lingcao Huang https://doi.org/10.1594/PANGAEA.897080

The comparison between calving front variations and bed elevation of Branch B in Jakobshavn Isbræ Enze Zhang, Lin Liu, and Lingcao Huang https://doi.org/10.1594/PANGAEA.897063

Download
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.
Read more