Imaging the past using methods of the future: computer-aided interpretation of ground-penetrating radar data collected at Roman towns in Italy

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Because of its extensive character, geophysical prospection is well-suited to investigate the overall character and development of Roman cities. Whereas currently our understanding relies on a few largely excavated sites (e.g. Pompeii, Ostia), prospection can help answering questions on city planning, street network, the size of inhabited areas, population estimations, and the interaction between city boundaries and urban development. However, a key bottleneck is the time consuming character of the traditional interpretation of geophysical data (manual delineation of anomalies). This is best illustrated by the ground-penetrating radar (GPR) technique, which reveals detailed plans of Roman towns, but produces enormous amounts of data because of its high-resolution and 3-D nature. Today, the potential of powerful machine learning techniques such as deep convolutional neural networks (DCNNs) for the computer-aided interpretation (CAI) of prospection data is increasingly demonstrated. However, DCNNs need large, manually delineated training sets. Building these is an effort that partially undoes the benefit of CAI. In this project, I will investigate novel approaches that train DCNNs from a small amount of manual delineations (while delivering competitive results), and apply them to GPR data from Roman towns in Italy. Furthermore, I will combine these and other CAI algorithms in a user-friendly toolbox that can be disseminated among the archaeological community. Finally, on the basis of the CAI results, I will provide an archaeological interpretation of the GPR dataset from Falerii Novi (Central-Italy) using GIS, data fusion and space syntax. I will be trained in Roman urbanism and machine learning, and in computing skills during a secondment at a commercial software developer. By stimulating non-invasive investigation, this interdisciplinary project will enhance the understanding of Roman urbanism, and promote the preservation of these important cultural heritage sites.