Standard high-resolution LiDAR analysis has changed landscape archaeology, yet it faces a critical limitation: the inability to distinguish between man-made lithic structures and natural geological features based solely on morphological footprints. This paper introduces the Archeoacoustic Stress Testing (AST) framework, a theoretical model designed to resolve this problem through simulated active acoustic sounding. The theory proposes that, by introducing an active kinetic pulse and measuring the return frequency through surface sensors, one can calculate a volume's acoustic impedance (Z) and reflection coefficient (R). The framework is applied to an identified northwest circular anomaly at the Gallo-Roman Villa in Jette. While the anomaly exhibits a visual footprint consistent with Roman infrastructure, its composition remains unverified. The AST model could theoretically resolve this by running two comparative scenarios. Scenario A assigns the subsurface volume the high-density parameters of Opus Caementicium (Absorption Coefficient: α = 0.02), simulating a structural lithic core. Scenario B assigns the low-density parameters of organic topsoil, simulating a natural earthwork. By comparing the predicted acoustic returns against the anomaly’s actual morphology, the model could theoretically identify high-impedance nuclei. A high-reflectance return would indicate a dense structural foundation, such as a signal tower or burial cist, whereas an attenuated signal suggests an acoustic null zone indicative of organic debris. This research argues that AST could theoretically provide the necessary bridge between optical surface data and subsurface material identification, offering a non-invasive methodology to reduce topographic misinterpretation in Roman provincial contexts.
Damian Noah Dimitrov (Thu,) studied this question.