Codes/Rasters - Application of machine learning to proximal gamma-ray and magnetic susceptibility surveys in the Maritime Antarctic: assessing the influence of periglacial processes and landforms

• Main Author: Moquedace, Cássio Marques
• Format: Report
• Language: unknown
• Published: Zenodo 2024
• Subjects: Antarc*; Antarctic
• Online Access: https://doi.org/10.5281/zenodo.10828305

This dataset and related code accompany the study "Application of Machine Learning to Proximal Gamma-ray and Magnetic Susceptibility Surveys in the Maritime Antarctic: Assessing the Influence of Periglacial Processes and Landforms." The study investigates the application of machine learning techniques to nearby gamma-ray and magnetic susceptibility surveys in the Maritime Antarctic region, with the aim of understanding the influence of periglacial processes and landforms. The data and code provided here allow for a detailed analysis of the results presented in the study, offering valuable insights for researchers interested in periglacial dynamics and geomorphology in the Antarctic region. The study is still in pre-print version; When the final version is published, the codes and rasters can be updated. Instructions for use: This dataset and code is publicly available on Zenodo for academic and research use. Users are encouraged to cite this work when using these resources in their own research.