Sakai, Masato and Sakurai, Akihisa and Lu, Siyuan and Olano, Jorge and Albrecht, Conrad M and Hamann, Hendrik and 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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Official URL: https://www.pnas.org/doi/10.1073/pnas.2407652121
Abstract
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.
| Item URL in elib: | https://elib.dlr.de/206765/ | ||||||||||||||||||||||||||||||||
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| Document Type: | Article | ||||||||||||||||||||||||||||||||
| Title: | AI-accelerated Nazca survey nearly doubles the number of known figurative geoglyphs and sheds light on their purpose | ||||||||||||||||||||||||||||||||
| Authors: |
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| Date: | September 2024 | ||||||||||||||||||||||||||||||||
| Journal or Publication Title: | Proceedings of the National Academy of Sciences of the United States of America (PNAS) | ||||||||||||||||||||||||||||||||
| Refereed publication: | Yes | ||||||||||||||||||||||||||||||||
| Open Access: | Yes | ||||||||||||||||||||||||||||||||
| Gold Open Access: | No | ||||||||||||||||||||||||||||||||
| In SCOPUS: | Yes | ||||||||||||||||||||||||||||||||
| In ISI Web of Science: | Yes | ||||||||||||||||||||||||||||||||
| Volume: | 121 | ||||||||||||||||||||||||||||||||
| DOI: | 10.1073/pnas.2407652121 | ||||||||||||||||||||||||||||||||
| Page Range: | e2407652121 | ||||||||||||||||||||||||||||||||
| Publisher: | National Academy of Sciences | ||||||||||||||||||||||||||||||||
| ISSN: | 0027-8424 | ||||||||||||||||||||||||||||||||
| Status: | Published | ||||||||||||||||||||||||||||||||
| Keywords: | Nasca culture, remote sensing, machine learning, artificial intelligence, UNESCO World Heritage | ||||||||||||||||||||||||||||||||
| HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||||||||||||||||||||||
| HGF - Program: | Space | ||||||||||||||||||||||||||||||||
| HGF - Program Themes: | Earth Observation | ||||||||||||||||||||||||||||||||
| DLR - Research area: | Raumfahrt | ||||||||||||||||||||||||||||||||
| DLR - Program: | R EO - Earth Observation | ||||||||||||||||||||||||||||||||
| DLR - Research theme (Project): | R - Optical remote sensing, R - Artificial Intelligence | ||||||||||||||||||||||||||||||||
| Location: | Oberpfaffenhofen | ||||||||||||||||||||||||||||||||
| Institutes and Institutions: | Remote Sensing Technology Institute > EO Data Science | ||||||||||||||||||||||||||||||||
| Deposited By: | Albrecht, Conrad M | ||||||||||||||||||||||||||||||||
| Deposited On: | 30 Sep 2024 12:30 | ||||||||||||||||||||||||||||||||
| Last Modified: | 02 Oct 2024 11:11 |
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