Looting historical heritage is an illicit phenomenon that affects archaeological areas worldwide, particularly where surveillance is low, and access proves difficult. The most efficient approach relies on Earth Observation (EO) data exploitation. In critical areas, such as conflict zones, country borders, desert areas, and remote regions, the analysis of EO data can often be the only way to determine when, how, and where looting happens.

The ALCEO project, in collaboration with and co-financed by the European Space Agency, aims to develop next-generation Artificial Intelligence methods to automatise the detection of looted sites on time series of EO data by building innovative Machine-Learning algorithms to fully exploit the large amount of data produced by satellite-based sensors. By measuring the dissimilarities between consecutive satellite imagery, the system is be able to automatically detect the relevant ‘anomalies’ recognising typical patterns and features of looting activities.