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

      , , , , , ,
      Remote Sensing
      MDPI AG

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          Abstract

          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.

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          Google Earth Engine: Planetary-scale geospatial analysis for everyone

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            A review of assessing the accuracy of classifications of remotely sensed data

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              Change detection from remotely sensed images: From pixel-based to object-based approaches

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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Remote Sensing
                Remote Sensing
                MDPI AG
                2072-4292
                November 2020
                November 11 2020
                : 12
                : 22
                : 3694
                Article
                10.3390/rs12223694
                a5212d03-8c99-4f8e-a945-75c93ab3de33
                © 2020

                https://creativecommons.org/licenses/by/4.0/

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