Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/105318
DC FieldValueLanguage
dc.contributor.authorCoelho, João Pedro de Oliveira-
dc.contributor.authorAnemone, Robert L.-
dc.contributor.authorCarvalho, Susana-
dc.date.accessioned2023-02-16T12:20:12Z-
dc.date.available2023-02-16T12:20:12Z-
dc.date.issued2021-
dc.identifier.issn2167-8359pt
dc.identifier.urihttps://hdl.handle.net/10316/105318-
dc.description.abstractPaleoanthropological research focus still devotes most resources to areas generally known to be fossil rich instead of a strategy that first maps and identifies possible fossil sites in a given region. This leads to the paradoxical task of planning paleontological campaigns without knowing the true extent and likely potential of each fossil site and, hence, how to optimize the investment of time and resources. Yet to answer key questions in hominin evolution, paleoanthropologists must engage in fieldwork that targets substantial temporal and geographical gaps in the fossil record. How can the risk of potentially unsuccessful surveys be minimized, while maximizing the potential for successful surveys?pt
dc.language.isoengpt
dc.publisherPeerJpt
dc.relationSFRH/BD/122306/2016pt
dc.relationThe Boise Trust Fundpt
dc.relationGorongosa Restoration Project, the National Geographic Society, the John Fell Fund Oxford, and the Leverhulme Trustpt
dc.rightsopenAccesspt
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt
dc.subjectGeospatial Paleontologypt
dc.subjectSoutheast Africapt
dc.subjectLate Miocenept
dc.subjectRemote Sensingpt
dc.subjectUnsupervised Learningpt
dc.subject.meshAnthropologypt
dc.subject.meshEvolutionary Studiespt
dc.subject.meshPaleontologypt
dc.subject.meshData Mining and Machine Learningpt
dc.subject.meshSpatial and Geographic Information Sciencept
dc.titleUnsupervised learning of satellite images enhances discovery of late Miocene fossil sites in the Urema Rift, Gorongosa, Mozambiquept
dc.typearticle-
degois.publication.firstPagee11573pt
degois.publication.titlePeerJpt
dc.peerreviewedyespt
dc.identifier.doi10.7717/peerj.11573pt
degois.publication.volume9pt
dc.date.embargo2021-01-01*
uc.date.periodoEmbargo0pt
item.grantfulltextopen-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.openairetypearticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextCom Texto completo-
crisitem.author.researchunitCFE - Centre for Functional Ecology - Science for People & the Planet-
crisitem.author.orcid0000-0003-0871-1926-
crisitem.author.orcid0000-0003-4542-3720-
Appears in Collections:I&D CFE - Artigos em Revistas Internacionais
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