The use of non-invasive methodologies is becoming essential for archaeological research, and ground penetrating radar is one of the most important techniques to obtain high resolution information. In this paper we present the analysis of a full 3-D GPR dataset integrated with a high-resolution photogrammetric survey acquired in a Roman archaeological site located in Aquileia (Northeast Italy) within the partially excavated area known as “Fondo Pasqualis”. We evaluated the importance of dense and accurate data collection and of processing of the GPR signal for characterization of the archaeological features. We further discuss the parametrization and the applicability of GPR attributes, in particular amplitude-based and coherence attributes, to better identify and characterise the archaeological buried targets. Furthermore, autopicking procedures for isosurfaces mapping were critically evaluated with the objective of detecting complex structures. The final interpretation of all the GPR features, with the support of digital terrain modelling and orthophotos from unmanned aerial vehicles, guided the archaeologists to open and excavate newly selected areas, which revealed interesting structures and contributed to the understanding of the historical events that characterized the Aquileia city.

Burrows are tunnels or holes excavated into the ground by certain types of animals, to be used as habitation or temporary refuge, or as a by-product of their locomotion. Burrows provide a form of shelter against predation and exposure to the elements, and can be found in nearly every biome and among various biological interaction types. River bank burrowing weakens the soil structure, increases the risk of erosion, and may lead to bank retreat and landslides. Currently, burrow watching, mapping, and prevention are human-only activities, and there are no conventional data or information systems designed for this purpose. In this paper, we design, implement, and test a novel AI-based solution that, starting with drone-acquired imagery, allows the user to automatically identify and map potentially dangerous burrows in the target area, and lays the basis for the digitization and systematic conservation of such information, to be later used for intervention and planning. Our solution contributes to the environmental sustainability of rivers, especially close to densely populated areas.