Articles | Volume 12, issue 3
https://doi.org/10.5194/esurf-12-801-2024
https://doi.org/10.5194/esurf-12-801-2024
Research article
 | 
10 Jun 2024
Research article |  | 10 Jun 2024

A machine learning approach to the geomorphometric detection of ribbed moraines in Norway

Thomas J. Barnes, Thomas V. Schuler, Simon Filhol, and Karianne S. Lilleøren

Data sets

Aeteia/Ribbed-Moraine: Release ver.8.3 for ribbed moraines detection script Thomas J. Barnes and Simon Filhol https://doi.org/10.5281/zenodo.7991094

Countries, 2020 - Administrative Units - Dataset GISCO https://gisco-services.ec.europa.eu/distribution/v2/countries/

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Short summary
In this paper, we use machine learning to automatically outline landforms based on their characteristics. We test several methods to identify the most accurate and then proceed to develop the most accurate to improve its accuracy further. We manage to outline landforms with 65 %–75 % accuracy, at a resolution of 10 m, thanks to high-quality/high-resolution elevation data. We find that it is possible to run this method at a country scale to quickly produce landform inventories for future studies.