Assessing manual, unsupervised, supervised and automatic change detection methods for detection of l
Channel: Recording Archaeology
Date: 16/09/2020

Apamea  is  a  Hellenistic  town  in  western  Syria  that  has  sadly  become  one  of  the  symbols  of  cultural heritage in the Middle East devastated by systematic looting. Since 2011, looting holes spread massively across the archaeological site, pockmarking both the ruins and monuments already excavated and the sectors of the site that had not been yet unexcavated by archaeolo-gists. From a scientific point of view, Apamea is an ideal testbed to undertake a comparative assessment  of  different  satellite-based  methods  for  detection,  mapping  and  quantification  of  looting holes and rates, owing to the distinct shape and clear visibility of the looting features. We tested different methods of supervised and unsupervised classification, as well as automat-ic change detection, relying on either brightness, texture, morphology, or size of the pits. The tests were undertaken using bespoke high spatial resolution time series of X-band Synthetic Aperture Radar (SAR), very high resolution optical images by commercial satellites, and tens of  freely-available  optical  Sentinel-2  time  series  at  high  temporal  resolution.  Combining  the  analysis of all these satellite datasets, we were also able to present the first comprehensive ac-count of the spatial and temporal evolution of looting in Apamea since its onset, and provide a proof of concept of how to combine radar and optical satellite observations for multi-sensor looting tracking from space.


Francesca Cigna, Deodato Tapete