of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Cover illustration: The roman amphitheatre of Catania: Reconstructive hypothesis with the various entrances to the monument. The research undertaken by IBAM-CNR between 2014 and 2015 aimed towards obtaining a three-dimensional reconstruction of the monument by combining diverse methods (virtual archaeology, digital archaeology, NDT integrated technologies) of data acquisition and processing. This made it possible to acquire important data for the creation of an exact reproduction of the parts of the monument that are still hidden and provide a faithful reconstruction of the entire architectural structure. The virtual reconstruction was performed by the Information Technologies Laboratory (ITLab) of the IBAM-CNR (itlab.ibam.cnr.it) (with kind permission of Arch Francesco Gabellone scientific director of ITLab_IBAM-CNR).

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This paper is focused on the presentation and discussion of an object oriented approach, applied to the Hierapolis (Turkey) site, to automatically detect the subtle features linked to buried archaeological remains. The data processing is applied twice: (i) first, globally at the whole image and, (ii) second, at the significant subsets identified by global analysis, in order to refine the previously obtained categorization. Object oriented approaches are usually based on two main steps: i) first the segmentation, ii) then the classification. Herein, we first performed the unsupervised classification step and, then, the segmentation. This choice is given by the specificity of archaeological issue, in particular: (i) the subtle features/targets to be identified are partially or totally unknown and characterized by a very small spectral separability from the background, and therefore (ii) the discrimination between archaeological class and substrates likely suffers significant confusion. To cope with these issues, the first step is based on an unsupervised classification, which provides a first 'rough' categorization of pixels; the second step, based on the segmentation, enables us to extract the geometric shape, and, in turn, to only categorize as archaeological class those pixels belonging to geometrically (rectangular and linear) shaped clusters. Outputs from this classification identify rectangular and linear features of archaeological interest whose size suggested that they may be a farm and some sectors of an aqueduct, respectively. Results from satellite based analysis were successfully evaluated by georadar and geomagnetic prospection along with field survey. From georadar and geomagnetic prospection we were able i) to confirm the presence of buried remains and ii) to detail and characterize these archaeological features at the subsoil level as well as to define the local stratigraphy. From field survey we dated the detected buried remains to a period spanning from Imperial Roman to early Byzantine historical times.