Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/27746
Title: An application of integration approaches for archaeo-geophysical data: Case study from Aizanoi
Authors: Küçükdemirci, Melda
Özer, Elif
Piro, Salvatore
Baydemir, Niyazi
Zamuner, Daniela
Keywords: geophysical data integration
graphical integration
ground penetrating radar
magnetometry
mathematical integration
principal component analyse
GPR
PCA
Publisher: WILEY, 111 RIVER ST, HOBOKEN 07030-5774, NJ USA
Abstract: Transforming multi-dimensional datasets, containing measurements of different physical parameters recorded at the same location, into a single composite imagery is quite important and frequently used in geophysical analysis as well as other scientific disciplines. This study focuses on the application of several different integration approaches for archaeo-geophysical data with a purpose of achieving complementary and improved information about the buried archaeological target by generating a single data set from multiple geophysical methods. An extensive geophysical survey using ground penetrating radar (GPR) and differential magnetic methods was made in different parts of the Aizanoi archaeological site (Cavdarhisar, Kutahya, Turkey) to locate and enhance subsurface archaeological structures. However, in this article, the outputs of graphical, mathematical and statistical integration approaches, which are applied both on synthetic images and real field case data, are presented and discussed. Comparing these results and experimental applications, mathematical and statistical integration approaches provide more useful and practicable information than just the single distinct datasets from each geophysical parameter studied.
URI: https://hdl.handle.net/11499/27746
https://doi.org/10.1002/arp.1583
ISSN: 1075-2196
Appears in Collections:Fen-Edebiyat Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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