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

Abstract

Wave-abrasion terraces are geomorphic marker horizons that provide information of past water levels, in marine and lacustrine environments. By integrating elevation measurements and age constraints, they serve as strain markers to assess vertical deformation rates associated with tectonic and/or climatic processes. As most geomorphic markers, wave-abrasion terraces are ephemeral features, and their topographic signature has variable levels of noise. Therefore, accurate and precise estimates of marine terrace morphology are essential to obtain significant uplift/subsidence rates. The open source TerraceM-3 enables operators to reduce non-systematic and systematic errors in terrace mapping by integrating machine learning techniques to replicate human mapping criteria, and standardized and reproducible workflows to handle systematic errors. In many regions, the availability of high-resolution topographic data remains relatively scarce limiting precision in geomorphic marker mapping. TerraceM-3 introduces a new module for downloading, filtering, and processing centimeter-resolution topographic data from the ICESat-2 satellite at global scale. The TerraceM-ICESat module produces vegetation-free profiles ready for assisted machine-learning mapping into a graphical user interface. Shallow bathymetry may be also extracted to extend the mapping of drowned terraces offshore. The new functionalities of TerraceM-3 were tested along tectonically active coasts in Peru and Algeria, revealing detailed deformation histories controlled by subducted seamounts and crustal faults. TerraceM-3 is designed to support research in tectonic geomorphology and paleoclimate studies by enhancing the precision and accuracy of wave-abrasion terrace mapping with applications in the assessment of coastal hazards.