Abstract Between 2023 and 2024, the Endangered Archaeology in the Middle East and North Africa (EAMENA) project, in collaboration with the Libyan Department of Antiquities (DoA), organised and conducted a series of training workshops and fieldwork campaigns in Libya, funded by the British Council’s Cultural Protection Fund (CPF). The workshops provided training to over 20 members of the DoA in a newly-developed Machine Learning Automated Change Detection (MLACD) tool. This remote sensing method was developed by the Leicester EAMENA team to detect landscape change and aid heritage monitoring efforts. The MLACD method was applied to four case studies in Libya: Lefakat (Cyrenaica), Bani Walid (Tripolitania), the region south of Derna (Cyrenaica) and Jarma (Fazzan). Each of these case studies was followed by a survey campaign by Libyan archaeologists to validate the results of the method, survey the archaeological sites identified, record their condition and assess the disturbances and threats affecting them. This article will provide an overview of the aims and successful outcomes of the EAMENA-CPF training programme, as well as an introduction to the MLACD method and its application to Libyan heritage, providing background and context for the individual case studies, which will be published more fully in separate articles.
Sheldrick et al. (Tue,) studied this question.