A team of researchers at Khalifa University in Abu Dhabi has developed a high-tech solution to searching for potential archaeological sites in large, arid areas like the Rub al-Khali desert on the Arabian Peninsula. The team created a machine learning algorithm that analyzes images collected by synthetic aperture radar (SAR), a satellite imagery technique that uses radio waves to detect objects hidden beneath surfaces.
The algorithm was trained using data from a known archaeological site, Saruq Al-Hadid, and once it was trained, it gave the researchers an indication of other potential areas nearby that are still not excavated. The technology is precise to within 50 centimeters and can create 3D models of the expected structure, giving archaeologists a better idea of what’s buried below.
The team collaborated with Dubai Culture, the government organization that manages the site, to conduct a ground survey using ground-penetrating radar, which replicated what the satellite measured from space. The new technique has identified areas for excavation, and Dubai Culture plans to uncover more archaeological treasures in the future.
Experts believe this technology can accelerate tedious work in archaeology, especially in harsh environments like deserts where other methods struggle. While some researchers are excited about the potential of AI-driven searches, others are cautious about relying too heavily on technology.
The real test of the technology will come next month when excavations begin at Saruq Al Hadid complex. If archaeologists find the structures predicted by the algorithm, it could validate the technology and pave the way for its use in other areas. The team is continuing to improve the algorithm’s precision and plans to export it to other regions with similar desert landscapes.
Source: https://edition.cnn.com/science/artificial-intelligence-archaeological-sites-sar-spc/index.html