Earth Surface Dynamics
Earth Surface Dynamics
ESurf
Articles | Volume 14, issue 2
Articles | Volume 14, issue 2
https://doi.org/10.5194/esurf-14-291-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esurf-14-291-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 2
Research article
 | 
13 Apr 2026
Research article |  | 13 Apr 2026

TerraceM-3: integrating machine learning and ICESat-2 altimetry to estimate deformation rates from wave-abrasion terraces

Julius Jara-Muñoz, Jürgen Mey, Roland Freisleben, Daniel Melnick, Markus Weiss, Patricio Winckler, Chrystelle Mavoungou, and Manfred R. Strecker

Viewed

Total article views: 2,305 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,540 600 165 2,305 351 141 166
  • HTML: 1,540
  • PDF: 600
  • XML: 165
  • Total: 2,305
  • Supplement: 351
  • BibTeX: 141
  • EndNote: 166
Views and downloads (calculated since 18 Dec 2025)
Cumulative views and downloads (calculated since 18 Dec 2025)

Viewed (geographical distribution)

Total article views: 2,305 (including HTML, PDF, and XML) Thereof 2,236 with geography defined and 69 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Saved (final revised paper)

Latest update: 26 Sep 2026
Download
Short summary
Coastal areas are vulnerable to sea-level rise and earthquakes. Understanding past changes requires precise deformation estimates. Marine terraces record sea-level and tectonic histories but mapping them has relied on subjective criteria. TerraceM-3 introduces standardized workflows and a machine-learning-based approach that, combined with ICESat-2 altimetry, enhances the accuracy and reproducibility of marine terrace mapping.
Read more
Share