AI accelerates discovery of Nazca geoglyphs

By Johannah Lopez
Last updated: April 24, 2025
1:57 PM

Researchers from Yamagata University’s Institute of Nazca in Peru, led by Prof. Masato Sakai, partnered with IBM scientists to teach AI how to analyze aerial imagery, identifying previously hidden geoglyphs. This collaboration has significantly accelerated the process, making it possible to conduct surveys in a fraction of the time it would normally take.

As Sakai explains, “The ability to conduct the survey in such a short period was thanks to the use of AI.”

This technology is not only helping to identify more geoglyphs but also changing how archaeologists approach the study of ancient civilizations. By processing aerial imagery, AI can spot patterns that might have otherwise gone unnoticed by the human eye, offering a more efficient way to map and understand historical remains. The success of AI in the Nazca Desert is only the beginning, as the technology is already being applied to other archaeological sites worldwide.

The Nazca Lines represent one of the first successful uses of AI in archaeology. These lines, created by scraping away the top layer of soil to expose lighter-colored material underneath, are intricate and precise, showcasing the Nazca people’s advanced understanding of geometry and proportion. Historically, archaeologists relied on traditional methods such as ground surveys, photography, and manual mapping to study these ancient sites.

However, digital tools such as photogrammetry and remote sensing technologies are now being adopted, allowing archaeologists to study vast areas more quickly and accurately. One of the most intriguing aspects of this AI-driven discovery is the potential to understand the purpose of the Nazca Lines better. Sakai’s team suggests that many of the new geoglyphs were part of ritual walkways, where individuals would walk along the lines to engage with the landscape and commune with the gods.

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https://www.devx.com/daily-news/ai-accelerates-discovery-of-nazca-geoglyphs/