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

Viewed

Total article views: 3,586 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,262 1,242 82 3,586 436 80 59
  • HTML: 2,262
  • PDF: 1,242
  • XML: 82
  • Total: 3,586
  • Supplement: 436
  • BibTeX: 80
  • EndNote: 59
Views and downloads (calculated since 07 Feb 2019)
Cumulative views and downloads (calculated since 07 Feb 2019)

Viewed (geographical distribution)

Total article views: 3,586 (including HTML, PDF, and XML) Thereof 2,799 with geography defined and 787 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Discussed (preprint)

Latest update: 28 Mar 2024
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.