Interpretation of geophysical surveys of archaeological sites using artificial neural networks

Geophysical surveys form a vital component of modern archaeological studies, providing data on the location of surviving sub-surface remains. Unfortunately interpretation of the raw output from geophysical surveys requires considerable expertise and current methods for machine interpretation are computationally expensive. In this paper, we describe the use of multi-layer perceptron neural networks from automated interpretation of geophysical survey data and present promising initial results for a survey taken of the Roman suburb of Butrint, a classical city situated in what is now Albania. Clearly a computationally efficient and straightforward means of inverting geophysical survey data is potentially an extremely useful tool in encouraging public awareness of cultural heritage.