Iban Berganzo: “Estamos transformando la forma de descubrir yacimientos arqueológicos”

Iban Berganzo: “Estamos transformando la forma de descubrir yacimientos arqueológicos”

🎙 Iban Berganzo 👥 20K 📅 March 16, 2026 ⏱ 12 min 👁 97 📄 expert opinion 🧭 2026-08-06
Available in: English (current) Français

Keywords

archaeologyartificial intelligenceremote sensingdeep learningopen access

Summary

In this interview, Iban Berganzo, winner of the IV Prize for Best Doctoral Thesis in Digital Humanities, discusses his research on large-scale archaeological site detection using digital tools. He explains that his thesis is based on remote sensing and artificial intelligence, enabling the detection of sites that are not visible on the ground, automating processes, and creating probabilistic maps for protection. He details applications in Catalonia, Galicia, India, Pakistan, and Greece, using satellite imagery, LiDAR, drones, and historical maps. The methods involve deep learning models trained on known sites to identify new ones. He emphasizes the importance of open-access repositories for sharing methods and data, and highlights the potential of these techniques in other fields like cancer detection and climate change monitoring. He also discusses the transition from digital to computational humanities, with applications in phytolith analysis, seed identification, text transcription, and art analysis. Berganzo concludes that this approach represents a paradigm shift comparable to radiocarbon dating.

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Critical Evaluation

The interview provides a compelling overview of how artificial intelligence and remote sensing are transforming archaeological research. Berganzo’s expertise is evident, and he clearly explains the technical aspects of his work, making it accessible to a broad audience. The discussion of specific projects, such as the detection of 10,000 potential sites in Galicia and 6,000 in the Indus Valley, demonstrates the practical impact of his methods. The emphasis on open science is commendable, as it promotes reproducibility and collaboration. However, the interview lacks critical discussion of limitations and potential biases in the AI models. For instance, the reliance on historical maps may introduce biases, and the accuracy of the detections is not quantified. The claims about the paradigm shift are bold but not fully substantiated with comparative data. The sources cited are limited to the awarding institution and the foundation, with no direct references to peer-reviewed publications. Despite these shortcomings, the interview is informative and highlights important trends in digital archaeology. The title accurately reflects the content, and the overall quality is high, though a more critical examination of the methods would enhance its scientific rigor.

186 words

Title / Content Match

The title accurately reflects the content, as the interview focuses on transforming archaeological discovery through digital tools.

Quality & Reliability

8/10

The interview presents a researcher's expert opinion on his own doctoral work, with clear descriptions of methods and applications. The claims are plausible and align with current trends in digital archaeology, but the video lacks detailed methodological transparency and peer-reviewed references, limiting full verification.

Key Moments

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Contribution & Novelties

The interview highlights the innovative application of AI and remote sensing to archaeology, enabling large-scale detection and protection of sites. The open-access repository is a notable contribution to the field.

Pour aller plus loin :

74 words

Radar Profile

The radar chart shows high scores in quantity and quality of information, with a slightly lower technical level, indicating a well-balanced presentation that is both informative and accessible. The reliability score is also high, reflecting the expert nature of the content.

Reliability 8/10