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Geosciences 2017, 7(2), 40; doi:10.3390/geosciences7020040

Fusion of Satellite Multispectral Images Based on Ground-Penetrating Radar (GPR) Data for the Investigation of Buried Concealed Archaeological Remains

1
Remote Sensing and Geo-Environment Laboratory, Eratosthenes Research Centre, Department of Civil Engineering and Geomatics, Cyprus University of Technology, Saripolou 2-8, 3603 Limassol, Cyprus
2
Laboratory of Geophysical-Satellite Remote Sensing & Archaeoenvironment, Foundation for Research & Technology-Hellas (F.O.R.T.H.), Nik. Foka 130, Rethymno, 74100 Crete, Greece
*
Author to whom correspondence should be addressed.
Academic Editors: Deodato Tapete and Jesus Martinez-Frias
Received: 28 April 2017 / Revised: 1 June 2017 / Accepted: 2 June 2017 / Published: 6 June 2017
(This article belongs to the Special Issue Remote Sensing and Geosciences for Archaeology)
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Abstract

The paper investigates the superficial layers of an archaeological landscape based on the integration of various remote sensing techniques. It is well known in the literature that shallow depths may be rich in archeological remains, which generate different signal responses depending on the applied technique. In this study three main technologies are examined, namely ground-penetrating radar (GPR), ground spectroscopy, and multispectral satellite imagery. The study aims to propose a methodology to enhance optical remote sensing satellite images, intended for archaeological research, based on the integration of ground based and satellite datasets. For this task, a regression model between the ground spectroradiometer and GPR is established which is then projected to a high resolution sub-meter optical image. The overall methodology consists of nine steps. Beyond the acquirement of the in-situ measurements and their calibration (Steps 1–3), various regression models are examined for more than 70 different vegetation indices (Steps 4–5). The specific data analysis indicated that the red-edge position (REP) hyperspectral index was the most appropriate for developing a local fusion model between ground spectroscopy data and GPR datasets (Step 6), providing comparable results with the in situ GPR measurements (Step 7). Other vegetation indices, such as the normalized difference vegetation index (NDVI), have also been examined, providing significant correlation between the two datasets (R = 0.50). The model is then projected to a high-resolution image over the area of interest (Step 8). The proposed methodology was evaluated with a series of field data collected from the Vésztő-Mágor Tell in the eastern part of Hungary. The results were compared with in situ magnetic gradiometry measurements, indicating common interpretation results. The results were also compatible with the preliminary archaeological investigations of the area (Step 9). The overall outcomes document that fusion models between various types of remote sensing datasets frequently used to support archaeological research can further expand the current capabilities and applications for the detection of buried archaeological remains. View Full-Text
Keywords: enhancement; fusion; ground spectroscopy; ground-penetrating radar (GPR); GeoEye; geophysics; remote sensing archaeology enhancement; fusion; ground spectroscopy; ground-penetrating radar (GPR); GeoEye; geophysics; remote sensing archaeology
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Agapiou, A.; Lysandrou, V.; Sarris, A.; Papadopoulos, N.; Hadjimitsis, D.G. Fusion of Satellite Multispectral Images Based on Ground-Penetrating Radar (GPR) Data for the Investigation of Buried Concealed Archaeological Remains. Geosciences 2017, 7, 40.

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