Interferometric SAR and Machine Learning: Using Open Source Data to Detect Archaeological Looting and Destruction

Archaeological heritage in the Near East is under an ever increasing threat from multiple vectors such as looting and systematic destruction, militarization, uncontrolled urban expansion absence of governmental control among others. Physically monitoring endangered sites proves to be infeasible due dangerous ground conditions on one hand, vast area land which they are dispersed. In recent years, abundant availability Very High Resolution (VHR) imaging satellites with short revisit times meant that it was possible monitor a large portion these space. However, images relatively expensive beyond means many researchers concerned local authorities. this paper, I present approach uses open source data two European Space Agency’s (ESA) Copernicus Constellation, Sentinel-1 Sentinel-2 order generate disturbance patches, destruction areas classified using Machine Learning. Such opens door towards sustainable over swaths long periods time.