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.
Highlights
Remote sensing space and ground data have been used in recent years for the identification of buried archaeological remains [1,2,3,4]
This study aims to evaluate in a qualitative way the detection of crop marks via image improvement during different phenological stages, based on different enhancement techniques—including linear equations—using two high-resolution satellite images
The detection is usually performed through interpretation of crop marks in multispectral satellite datasets
Summary
Remote sensing space and ground data have been used in recent years for the identification of buried archaeological remains [1,2,3,4]. The technological improvements of satellite sensors, both in terms of spatial as well as spectral resolution, achieved within the last years, can provide archaeologists with further information regarding the landscape, assisting them to better understand and interpret large archaeological areas [5,6,7]. The exposure of buried archaeological features based on image processing techniques is considered a key parameter for landscape studies, while several researchers have already applied and detected hidden remains mainly through the identification of crop marks [8,9,10,11,12,13]. Depending on the type of the buried archaeological features, crop vigour may be enhanced or reduced [14,15]
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