4.7 Article

Appraisal of Opportunities and Perspectives for the Systematic Condition Assessment of Heritage Sites with Copernicus Sentinel-2 High-Resolution Multispectral Imagery

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REMOTE SENSING
卷 10, 期 4, 页码 -

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MDPI
DOI: 10.3390/rs10040561

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optical remote sensing; multispectral imagery; Sentinel-2; Google Earth; feature extraction; change detection; damage assessment; cultural heritage; Syria; Libya

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Very high-resolution (VHR) optical satellite imagery (<= 5 m) is nowadays an established source of information to monitor cultural and archaeological heritage that is exposed to hazards and anthropogenic threats to their conservation, whereas few publications specifically investigate the role that regularly acquired images from high-resolution (HR) satellite sensors (5-30 m) may play in this application domain. This paper aims to appraise the potential of the multispectral constellation Sentinel-2 of the European Commission Earth observation programme Copernicus to detect prominent features and changes in heritage sites, during both ordinary times and crisis. We test the 10 m spatial resolution of the 3 visible spectral bands of Sentinel-2 for substantiation of single local events-that is, wall collapses in the UNESCO World Heritage site of the Old City of Aleppo (Syria)-and for hotspot mapping of recurrent incidents-that is, the archaeological looting in the archaeological site of Apamea (Syria). By screening long Sentinel-2 time series consisting of 114 images for Aleppo and 57 images for Apamea, we demonstrate that changes of textural properties and surface reflectance can be logged accurately in time and space and can be associated to events relevant for conservation. VHR imagery from Google Earth was used for the validation and identification of trends occurring prior to the Sentinel-2 launch. We also demonstrate how to exploit the Sentinel-2 short revisiting time (5 days) and large swath (290 km) for multi-temporal tracking of spatial patterns of urban sprawl across the cultural landscape of the World Heritage Site of Cyrene (Libya), and the three coastal ancient Greek sites of Tocra, Ptolemais, and Apollonia in Cyrenaica. With the future development of tailored machine learning approaches of feature extraction and pattern detection, Sentinel-2 can become extremely useful to screen wider regions with short revisiting times and to undertake comparative condition assessment analyses of different heritage sites.

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