Sakai, Masato und Sakurai, Akihisa und Lu, Siyuan und Olano, Jorge und Albrecht, Conrad M und Hamann, Hendrik und Freitag, Marcus (2024) AI-accelerated Nazca survey nearly doubles the number of known figurative geoglyphs and sheds light on their purpose. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 121 (40), e2407652121. National Academy of Sciences. doi: 10.1073/pnas.2407652121. ISSN 0027-8424.
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Offizielle URL: https://www.pnas.org/doi/10.1073/pnas.2407652121
Kurzfassung
It took nearly a century to discover a total of 430 figurative Nazca geoglyphs, which offer significant insights into the ancient cultures at the Nazca Pampa. Here, we report the deployment of an AI system to the entire Nazca region, a UNESCO World Heritage site, leading to the discovery of 303 new figurative geoglyphs within only 6 mo of field survey, nearly doubling the number of known figurative geoglyphs. Even with limited training examples, the developed AI approach is demonstrated to be effective in detecting the smaller relief-type geoglyphs, which unlike the giant line-type geoglyphs are very difficult to discern. The improved account of figurative geoglyphs enables us to analyze their motifs and distribution across the Nazca Pampa. We find that relief-type geoglyphs depict mainly human motifs or motifs of things modified by humans, such as domesticated animals and decapitated heads (81.6%). They are typically located within viewing distance (on average 43 m) of ancient trails that crisscross the Nazca Pampa and were most likely built and viewed at the individual or small-group level. On the other hand, the giant line-type figurative geoglyphs mainly depict wild animals (64%). They are found an average of 34 m from the elaborate linear/trapezoidal network of geoglyphs, which suggests that they were probably built and used on a community level for ritual activities.
elib-URL des Eintrags: | https://elib.dlr.de/206765/ | ||||||||||||||||||||||||||||||||
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Dokumentart: | Zeitschriftenbeitrag | ||||||||||||||||||||||||||||||||
Titel: | AI-accelerated Nazca survey nearly doubles the number of known figurative geoglyphs and sheds light on their purpose | ||||||||||||||||||||||||||||||||
Autoren: |
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Datum: | September 2024 | ||||||||||||||||||||||||||||||||
Erschienen in: | Proceedings of the National Academy of Sciences of the United States of America (PNAS) | ||||||||||||||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||||||||||||||
Open Access: | Ja | ||||||||||||||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||||||||||||||||||
In ISI Web of Science: | Ja | ||||||||||||||||||||||||||||||||
Band: | 121 | ||||||||||||||||||||||||||||||||
DOI: | 10.1073/pnas.2407652121 | ||||||||||||||||||||||||||||||||
Seitenbereich: | e2407652121 | ||||||||||||||||||||||||||||||||
Verlag: | National Academy of Sciences | ||||||||||||||||||||||||||||||||
ISSN: | 0027-8424 | ||||||||||||||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||||||||||||||
Stichwörter: | Nasca culture, remote sensing, machine learning, artificial intelligence, UNESCO World Heritage | ||||||||||||||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||||||||||||||
HGF - Programm: | Raumfahrt | ||||||||||||||||||||||||||||||||
HGF - Programmthema: | Erdbeobachtung | ||||||||||||||||||||||||||||||||
DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||||||||||||||||||
DLR - Forschungsgebiet: | R EO - Erdbeobachtung | ||||||||||||||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | R - Optische Fernerkundung, R - Künstliche Intelligenz | ||||||||||||||||||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||||||||||||||||||
Institute & Einrichtungen: | Institut für Methodik der Fernerkundung > EO Data Science | ||||||||||||||||||||||||||||||||
Hinterlegt von: | Albrecht, Conrad M | ||||||||||||||||||||||||||||||||
Hinterlegt am: | 30 Sep 2024 12:30 | ||||||||||||||||||||||||||||||||
Letzte Änderung: | 02 Okt 2024 11:11 |
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