TerraceM 3.0: Advancing marine terrace mapping through integrated machine learning methods - INSU - Institut national des sciences de l'Univers
Communication Dans Un Congrès Année : 2024

TerraceM 3.0: Advancing marine terrace mapping through integrated machine learning methods

Julius Jara Muñoz
  • Fonction : Auteur
Jurgen Mey
  • Fonction : Auteur
Roland Freisleben
  • Fonction : Auteur
Kevin Pedoja
Daniel Melnick
  • Fonction : Auteur

Résumé

TerraceM is an open-source software written in MATLAB for mapping and analyzing marine terraces. In this latest release, TerraceM-3 has undergone significant evolution, which leverages the capabilities of machine learning to introduce an automated marine terrace mapping feature. This new version includes a neural network that has been meticulously trained with over 1000 mapped marine terraces. This allows TerraceM-3 users to effortlessly map marine terraces and precisely determine their elevation through the automated mapping of their shoreline angles. In addition, TerraceM-3 incorporates two new functionalities: 1) Photon profile mapping, which includes mapping of satellite LiDAR profiles from the IceSat-2 mission, which broadens the applicability of TerraceM-3 beyond the availability of topographic data. 2) Indicative meaning calculator that accounts for the factors that can alter the initial sea-level position using global datasets (wave conditions and tidal ranges). This method facilitates the direct assessment of uncertainties in the reconstructions of the paleo-sea-level based on marine terraces. TerraceM-3 is a complete toolkit for researchers and students engaged in marine terrace analysis by offering a unique blend of numerical methods, statistical analyses techniques and additional enhanced functionalities to precisely map marine terraces and using them as markers of tectonic deformation.
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Dates et versions

insu-04725538 , version 1 (08-10-2024)

Identifiants

Citer

Julius Jara Muñoz, Jurgen Mey, Roland Freisleben, Kevin Pedoja, Daniel Melnick. TerraceM 3.0: Advancing marine terrace mapping through integrated machine learning methods. European Geosciences Union General Assembly 2024 (EGU24), 0000, à renseigner, Unknown Region. ⟨10.5194/egusphere-egu24-5716⟩. ⟨insu-04725538⟩
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