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Detecting Change at Archaeological Sites in North Africa Using Open-Source Satellite Imagery

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posted on 2022-03-09, 11:18 authored by Louise Rayne, Maria Carmela Gatto, Lamin Abdulaati, Muftah Al-Haddad, Martin Sterry, Nichole Sheldrick, David Mattingly
Our paper presents a remote sensing workflow for identifying modern activities that threaten archaeological sites, developed as part of the work of the Endangered Archaeology of the Middle East and North Africa (EAMENA) project. We use open-source Sentinel-2 satellite imagery and the free tool Google Earth Engine to run a per-pixel change detection to make the methods and data as accessible as possible for heritage professionals. We apply this and perform validation at two case studies, the Aswan and Kom-Ombo area in Egypt, and the Jufra oases in Libya, with an overall accuracy of the results ranging from 85–91%. Human activities, such as construction, agriculture, rubbish dumping and natural processes were successfully detected at archaeological sites by the algorithm, allowing these sites to be prioritised for recording. A few instances of change too small to be detected by Sentinel-2 were missed, and false positives were caused by registration errors, shadow and movements of sand. This paper shows that the expansion of agricultural and urban areas particularly threatens the survival of archaeological sites, but our extensive online database of archaeological sites and programme of training courses places us in a unique position to make our methods widely available.

Funding

The EAMENA research was funded by the Arcadia Fund, building on initial work in al-Jufra by the Trans-SAHARA project, with funding from the European Research Council (grant number 269418). AKAP was funded by the University of Bologna, the Italian Ministry of Foreign Affairs, EAMENA/Arcadia Fund.

History

Citation

Rayne, L.; Gatto, M.C.; Abdulaati, L.; Al-Haddad, M.; Sterry, M.; Sheldrick, N.; Mattingly, D. Detecting Change at Archaeological Sites in North Africa Using Open-Source Satellite Imagery. Remote Sens. 2020, 12, 3694. https://doi.org/10.3390/rs12223694

Author affiliation

School of Archaeology and Ancient History

Version

  • VoR (Version of Record)

Published in

Remote Sensing

Volume

12

Issue

22

Pagination

3694

Publisher

MDPI

eissn

2072-4292

Acceptance date

2020-11-09

Copyright date

2020

Available date

2020-11-11

Language

English