Abstract
Hyperspectral images can highlight crop marks in vegetated areas, which may indicate the presence of underground buried structures, by exploiting the spectral information conveyed in reflected solar radiation. In recent years, different vegetation indices and several other image features have been used, with varying success, to improve the interpretation of remotely sensed images for archaeological research. However, it is difficult to assess the derived maps quantitatively and select the most meaningful one for a given task, in particular for a non-specialist in image processing. This paper estimates for the first time objectively the suitability of maps derived from spectral features for the detection of buried archaeological structures in vegetated areas based on information theory. This is achieved by computing the statistical dependence between the extracted features and a digital map indicating the presence of buried structures using information theoretical notions. Based on the obtained scores on known targets, the features can be ranked and the most suitable can be chosen to aid in the discovery of previously undetected crop marks in the area under similar conditions. Three case studies are reported: the Roman buried remains of Carnuntum (Austria), the underground structures of Selinunte in the South of Italy, and the buried street relics of Pherai (Velestino) in central Greece.
Highlights
Remote sensing allows performing non-invasive large-scale analysis and monitoring of archaeological sites
In some cases, improved versions of already existing indices are tested, such as the Atmospherically Resistant Vegetation Index (ARVI) [30] which can be considered as an improved Normalized Difference Vegetation Index (NDVI) [17] robust to atmospheric effects, or the improved version of the Modified Chlorophyll Absorption Ratio Index (CARI) [31] among several variants of the CARI
This paper focuses on the evaluation of information extracted from hyperspectral dataset for the detection of concealed archaeological structures, usually performed indirectly by observing stressed or very vigorous vegetation through the appearance of the so-called crop marks
Summary
Remote sensing allows performing non-invasive large-scale analysis and monitoring of archaeological sites. The presence of buried archaeological structures can be detected by observing below the surface usually using ground-penetrating radar sensors [1,2]. Laser scanning has been employed in different applications [3] such as mapping areas beneath the vegetation [4], as in the recent case of the discovery of previously undocumented settlement features in Cambodia [5]. For the case of optical sensors, buried structures are usually detected in vegetated areas (cultivated or not) by studying vegetation anomalies on the surface known as crop marks, which are caused by differential growth in the vegetation. Differences in humidity or soil filling below the surface may generate anomalies in the soil known as soil marks, which can be remotely observed
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