Department of Agroecology, Aarhus University, Blichers Allé 20, 8830 Tjele, Denmark
Márcio Rocha Francelino
Department of Soil Science, Federal University of Viçosa, Viçosa, Brazil
Carlos Ernesto Gonçalves Reynaud Schaefer
Department of Soil Science, Federal University of Viçosa, Viçosa, Brazil
Elpídio Inácio Fernandes-Filho
Department of Soil Science, Federal University of Viçosa, Viçosa, Brazil
Edgar Batista de Medeiros Júnior
Department of Soil Science, Federal University of Viçosa, Viçosa, Brazil
Fabio Soares de Oliveira
Department of Geography, Federal University of Minas Gerais, Belo Horizonte, Brazil
José João Lelis Leal Souza
Department of Soil Science, Federal University of Viçosa, Viçosa, Brazil
Tiago Osório Ferreira
Department of Soil Science, “Luiz de Queiroz” College of Agriculture, University of São Paulo, Av. Pádua Dias, 11, CP 9, Piracicaba, SP 13418-900, Brazil
José A. M. Demattê
Department of Soil Science, “Luiz de Queiroz” College of Agriculture, University of São Paulo, Av. Pádua Dias, 11, CP 9, Piracicaba, SP 13418-900, Brazil
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1,643
583
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125
173
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PDF: 583
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BibTeX: 125
EndNote: 173
Views and downloads (calculated since 15 Apr 2024)
Cumulative views and downloads
(calculated since 15 Apr 2024)
Total article views: 928 (including HTML, PDF, and XML)
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640
228
60
928
44
56
HTML: 640
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BibTeX: 44
EndNote: 56
Views and downloads (calculated since 25 Nov 2025)
Cumulative views and downloads
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Total article views: 1,415 (including HTML, PDF, and XML)
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1,003
355
57
1,415
81
117
HTML: 1,003
PDF: 355
XML: 57
Total: 1,415
BibTeX: 81
EndNote: 117
Views and downloads (calculated since 15 Apr 2024)
Cumulative views and downloads
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Viewed (geographical distribution)
Total article views: 2,343 (including HTML, PDF, and XML)
Thereof 2,322 with geography defined
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Total article views: 928 (including HTML, PDF, and XML)
Thereof 917 with geography defined
and 11 with unknown origin.
Total article views: 1,415 (including HTML, PDF, and XML)
Thereof 1,405 with geography defined
and 10 with unknown origin.
The study explores Maritime Antarctica's geology, shaped by periglacial forces, using pioneering gamma-spectrometric and magnetic surveys on igneous rocks due to limited Antarctic surveys. Machine learning predicts radionuclide and magnetic content based on terrain features, linking their distribution to landscape processes, morphometrics, lithology, and pedogeomorphology. Inaccuracies arise due to complex periglacial processes and landscape complexities.
The study explores Maritime Antarctica's geology, shaped by periglacial forces, using pioneering...