Learning the shape of coasts: automated detection of Quaternary paleo-landforms for the assessment of climatic-driven modifications in the south-Tyrrhenian 

Learning the shape of coasts: automated detection of Quaternary paleo-landforms for the assessment of climatic-driven modifications in the south-Tyrrhenian | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Learning the shape of coasts: automated detection of Quaternary paleo-landforms for the assessment of climatic-driven modifications in the south-Tyrrhenian Gaia Mattei, Alessia Sorrentino, Gerardo Pappone, Angelo Ciaramella, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7319870/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted 13 You are reading this latest preprint version Abstract Coastal landforms preserve key evidence of past sea-level fluctuations, tectonic activity, and paleoclimate variability. In this study, we implement a supervised machine learning approach, trained on an original, expert-labeled geomorphological dataset, to detect and classify inherited and active coastal features - such as paleo-seacliffs and polycyclic sea cliffs - along the south-Tyrrhenian. Using high-resolution DTM and morphometric indicators, our model accurately identifies the spatial signatures of Quaternary coastal evolution. These results are cross-validated against independent geological mapping, and sea-level reconstruction datasets. The integration of geomorphological classification with paleo–sea level markers enables us to reconstruct coastal morphogenesis in relation to the last interglacial cycle. Our findings highlight the potential of machine learning to automate the identification of coastal paleo-landscapes and contribute to refining the timing and extent of marine transgressions and regressions across the Mediterranean. This approach offers a scalable framework for investigating past climate–landscape interactions and for supporting future coastal hazard assessments under changing climate conditions. Earth and environmental sciences/Climate sciences Biological sciences/Ecology Earth and environmental sciences/Ecology Earth and environmental sciences/Ocean sciences Earth and environmental sciences/Solid earth sciences Climatic change sea level change coastal paleo-landscape machine learning automated mapping Mediterranean area Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial1MorphometricAnalysis.docx SupplementaryMaterial2Terrainderivatives.docx SupplementaryMaterial3Tables.docx Cite Share Download PDF Status: Published Journal Publication published 17 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 17 Sep, 2025 Reviews received at journal 12 Sep, 2025 Reviews received at journal 12 Sep, 2025 Reviews received at journal 03 Sep, 2025 Reviewers agreed at journal 24 Aug, 2025 Reviewers agreed at journal 22 Aug, 2025 Reviewers agreed at journal 17 Aug, 2025 Reviewers agreed at journal 16 Aug, 2025 Reviewers invited by journal 15 Aug, 2025 Editor invited by journal 12 Aug, 2025 Editor assigned by journal 11 Aug, 2025 Submission checks completed at journal 08 Aug, 2025 First submitted to journal 07 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7319870","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":504740190,"identity":"b95ee611-dcdd-4ec3-8b14-e67898b544bb","order_by":0,"name":"Gaia Mattei","email":"","orcid":"","institution":"Parthenope University of Naples","correspondingAuthor":false,"prefix":"","firstName":"Gaia","middleName":"","lastName":"Mattei","suffix":""},{"id":504740191,"identity":"42a3f5e1-66fc-44f4-8683-12242b3448e7","order_by":1,"name":"Alessia 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