Remote sensing is widely used in archaeological prospection to detect surface anomalies (crop marks) indicating buried remains, typically through recognition of visual patterns in high- or very high-resolution imagery acquired by means of satellite, airborne, or drone sensors. In contrast, spectroscopic approaches focusing on variations in spectral signatures still remain rarely applied in archaeological research. This study proposes a technological barrier-free method addressed to archaeologists which is based on pixel-level analysis of the Reflectance Values (RV) and spectral shape variations in the visible, near-infrared and short-wave infrared (VIS-NIR-SWIR) range derived from Sentinel-2 imagery. Spectral signatures are extracted through sampling polygons designed to account for the spatial resolution of the different Sentinel-2 bands and their spatial relationship with the location and size of the archaeological features. The RV method is tested on two Roman archaeological contexts: the ancient city of Telesia Vetere (San Salvatore Telesino, Benevento) and a Roman villa at Podere Colle Agnano (Labro, Rieti) using the full Sentinel-2 archive since 2017. While Telesia has previously been investigated through aerial photo interpretation and archaeological fieldwork, the Roman villa at Labro is documented here for the first time. Results show consistent seasonal repeated spectral separability between areas corresponding to known buried archaeological features and surrounding areas. Similar anomalies were also detected in areas without previously documented remains, thus suggesting the possible presence of buried structures and highlighting the predictive potential of the RV method. Owing to its easiness to use beyond image processing specialism and reliance on open-access data, the method can support archaeological decision-making and guide further investigation with higher-resolution remote sensing data or targeted field surveys, particularly in the framework of preventive archaeology.
Corbo et al. (Wed,) studied this question.