Predicting the geographic distribution of ancient Amazonian archaeological sites with machine learning.

Walker, Robert S; Ferguson, Jeffrey R; Olmeda, Angelica; Hamilton, Marcus J; Elghammer, Jim; Buchanan, Briggs

Walker, Robert S; Ferguson, Jeffrey R; Olmeda, Angelica; Hamilton, Marcus J; Elghammer, Jim; Buchanan, Briggs.

Afiliación

Walker RS; Department of Anthropology, University of Missouri - Columbia, Columbia, MO, United States of America.
Ferguson JR; Department of Anthropology, University of Missouri - Columbia, Columbia, MO, United States of America.
Olmeda A; Archaeometry Laboratory, University of Missouri Research Reactor Center, University of Missouri - Columbia, Columbia, MO, United States of America.
Hamilton MJ; Department of Anthropology, University of Missouri - Columbia, Columbia, MO, United States of America.
Elghammer J; Department of Anthropology, University of Texas at San Antonio, San Antonio, TX, United States of America.
Buchanan B; Department of Anthropology, University of Missouri - Columbia, Columbia, MO, United States of America.

PeerJ ; 11: e15137, 2023.

Article en En | MEDLINE | ID: mdl-37020851

Asunto(s)

Bosque Lluvioso; Suelo; Humanos; Brasil; Ríos; Arqueología

Palabras clave

Agriculture; Amazonia; Amazonian Dark Earths; Archaeology; Deforestation; Geoglyphs; Human-environment interactions; Machine learning; Random forest; Remote sensing

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Suelo / Bosque Lluvioso Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: America do sul / Brasil Idioma: En Revista: PeerJ Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

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