Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/8614
Title: Orthogonal Equations of Multi-Spectral Satellite Imagery for the Identification of Un-Excavated Archaeological Sites
Authors: Agapiou, Athos 
Alexakis, Dimitrios 
Sarris, Apostolos 
Hadjimitsis, Diofantos G. 
Major Field of Science: Engineering and Technology
Field Category: Environmental Engineering
Keywords: Spectral enhancement;Remote sensing archaeology;Ground spectroscopy;Crop marks
Issue Date: Dec-2013
Source: Remote Sensing, 2013, vol. 5, no. 12, pp. 6560-6586
Volume: 5
Issue: 12
Start page: 6560
End page: 6586
Journal: Remote Sensing 
Abstract: This paper aims to introduce new linear orthogonal equations for different satellite data derived from QuickBird; IKONOS; WorldView-2; GeoEye-1, ASTER; Landsat 4 TM and Landsat 7 ETM+ sensors, in order to enhance the exposure of crop marks. The latest are of significant value for the detection of buried archaeological features using remote sensing techniques. The proposed transformations, re-projects the initial VNIR bands of the satellite image, into a new 3D coordinate system where the first component is the so called “crop mark”, the second component “vegetation” and the third component “soil”. For the purpose of this study, a large ground spectral signature database has been explored and analyzed separately for each different satellite image. The narrow band reflectance has been re-calculated using the Relative Spectral Response filters of each sensor, and then a PCA analysis was carried out. Subsequently, the first three PCA components were rotated in order to enhance the detection of crop marks. Finally, all proposed transformations have been successfully evaluated in different existing archaeological sites and some interesting crop marks have been exposed.
URI: https://hdl.handle.net/20.500.14279/8614
ISSN: 20724292
DOI: 10.3390/rs5126560
Rights: © MDPI
Type: Article
Affiliation : Cyprus University of Technology 
Institute for Mediterranean Studies 
Appears in Collections:Άρθρα/Articles

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