Earth Surface Dynamics
Earth Surface Dynamics
ESurf
Articles | Volume 8, issue 3
Articles | Volume 8, issue 3
https://doi.org/10.5194/esurf-8-809-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esurf-8-809-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 8, issue 3
Research article
 | Highlight paper
 | 
25 Sep 2020
Research article | Highlight paper |  | 25 Sep 2020

Dominant process zones in a mixed fluvial–tidal delta are morphologically distinct

Mariela Perignon, Jordan Adams, Irina Overeem, and Paola Passalacqua

Viewed

Total article views: 4,619 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,627 868 124 4,619 115 110
  • HTML: 3,627
  • PDF: 868
  • XML: 124
  • Total: 4,619
  • BibTeX: 115
  • EndNote: 110
Views and downloads (calculated since 22 Apr 2020)
Cumulative views and downloads (calculated since 22 Apr 2020)

Viewed (geographical distribution)

Total article views: 4,619 (including HTML, PDF, and XML) Thereof 4,042 with geography defined and 577 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 13 Dec 2024
Download
Short summary
We propose a machine learning approach for the classification and analysis of large delta systems. The approach uses remotely sensed data, channel network extraction, and the analysis of 10 metrics to identify clusters of islands with similar characteristics. The 12 clusters are grouped in six main classes related to morphological processes acting on the system. The approach allows us to identify spatial patterns in large river deltas to inform modeling and the collection of field observations.
Read more