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|Title:||Study of the variations of archaeological marks at Neolithic site of Lucera, Italy using multispectral high resolution datasets||Authors:||Agapiou, Athos
Hadjimitsis, Diofantos G.
|Major Field of Science:||Engineering and Technology||Field Category:||Civil Engineering||Keywords:||Remote sensing archaeology;Crop marks;Linear equations;Lucera archaeological site;Vegetation indices;Ratio indices;Shadow areas||Issue Date:||1-Sep-2016||Source:||Remote Sensing, 2016, vol. 8, no. 9||Volume:||8||Issue:||9||Project:||ATHENA. Remote Sensing Science Center for Cultural Heritage||Journal:||Remote Sensing||Abstract:||Satellite images have been systematically explored by archaeologists to detect crop marks, which are considered as a proxy for the identification of buried archaeological remains. Even though several existing algorithms are frequently applied, such as histogram enhancements and vegetation indices, the detection of crop marks still remains a difficult task, while the final interpretation results can be very poor. This paper aims to present some of the current difficulties of remote sensing archaeology in terms of detection and interpretation of crop marks due to the crops' phenological variations. At the same time, the presented work seeks to evaluate the recently proposed linear equations for the enhancement of crop marks, initially developed for the eastern Mediterranean region. These linear equations re-project the initial n-space spectral into a new 3D orthogonal space determined by three components: a crop mark component, a vegetation component, and a soil component. For the aims of this study, the Lucera archaeological site (southern Italy), where several Neolithic trenches have been identified, was selected. QuickBird and GeoEye high-resolution satellite images were analysed, indicating that vegetation indices may mismatch some crop marks depending on the phenological stage of the vegetation cultivated in the area of the archaeological site. On the contrary, ratios from linear equations were able to spot these crop marks even in shadow areas, indicating that improvements and developments of novel methodologies and equations based on remote sensing datasets can further assist archaeological research.||URI:||https://hdl.handle.net/20.500.14279/9900||ISSN:||2072-4292||DOI:||10.3390/rs8090723||Rights:||© Multidisciplinary Digital Publishing Institute||Type:||Article||Affiliation :||Cyprus University of Technology
CNR - National Research Council of Italy
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