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  4. An objective assessment of hyperspectral indicators for the detection of buried archaeological relics
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An objective assessment of hyperspectral indicators for the detection of buried archaeological relics

Journal
Remote Sensing
Date Issued
April 1, 2018
Author(s)
Cerra, Daniele  
Agapiou, Athos  
Cavalli R., Rosa Maria  
Sarris, Apostolos  
DOI
10.3390/rs10040500
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.
Funding(s)
ATHENA. Remote Sensing Science Center for Cultural Heritage  
Subjects

Archaeology

Crop marks

Cultural heritage

Hyperspectral imaging...

Mutual information

Spectral indices

File(s)
Thumbnail Image
Name

remotesensing-10-00500-v2.pdf

Size

24.29 MB

Format

Adobe PDF

Checksum (MD5)

f97a02026e70c3ca7d6352aeafd0cea5

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