Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE

Autor: Griffiths, Haïfa Ben-Romdhane, Diana Francis, Charfeddine Cherif, Kosmas Pavlopoulos, Hosni Ghedira, Steven
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Geosciences; Volume 13; Issue 6; Pages: 179
ISSN: 2076-3263
DOI: 10.3390/geosciences13060179
Popis: In this paper, the feasibility of satellite remote sensing in detecting and predicting locations of buried objects in the archaeological site of Saruq Al-Hadid, United Arab Emirates (UAE) was investigated. Satellite-borne synthetic aperture radar (SAR) is proposed as the main technology for this initial investigation. In fact, SAR is the only satellite-based technology able to detect buried artefacts from space, and it is expected that fine-resolution images of ALOS/PALSAR-2 (L-band SAR) would be able to detect large features (>1 m) that might be buried in the subsurface (
Databáze: OpenAIRE