Articles | Volume 14, issue 2
https://doi.org/10.5194/esurf-14-291-2026
https://doi.org/10.5194/esurf-14-291-2026
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

Model code and software

TerraceM-3: Marine terrace mapping using machine learning and satellite altimetry (Version 3) Julius Jara Muñoz et al. https://doi.org/10.5281/zenodo.17439972

TerraceM-3: Marine terrace mapping using machine learning and satellite altimetry (v.3.2) Julius Jara Muñoz et al. https://doi.org/10.5281/zenodo.18882765

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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.
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