10900/153513

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dc.contributor.author Gennaro, Andrea
dc.contributor.author Mussumeci, Giuseppe
dc.contributor.author Mangiameli, Michele
dc.contributor.author Candiano, Alessio
dc.contributor.author Fargione, Gabriele
dc.date.accessioned 2023-10-17T14:10:01Z
dc.date.available 2024-05-17T09:25:01Z
dc.date.issued 2024-05-17
dc.identifier.uri http://hdl.handle.net/10900/153513
dc.identifier.uri http://dx.doi.org/10.15496/publikation-94852
dc.description Korrigierte Version. Bildunterschriften korrigiert
dc.description.abstract Automated and semi-automated image classifications have made their way into archaeological applications, but early attempts have been strongly criticized. This study examines semi-automated detection methods of archaeological evidence through a comparison of pixel-based and object-oriented data classification. This research has been carried out on high-resolution imagery (WorldView-2) and the selected case study is located on the western slope of Etna (Sicily), the highest volcano in Europe, where a huge variety of settlements can be found from Prehistoric to Medieval times. The methodology of both pixel-based and object-based data classification is described and discussed over to specific case-study. The different nature of the two methods combined with the post-dictive approach adopted provides useful results in order to determine robustness and weakness of techniques presented here. In fact, our goal is to analyze advantages and disadvantages of the usage of pixel and object-based classification techniques and shed light on the significant change in pattern recognition. Finally, the obtained data are compared with manual visual interpretations and analyzed in terms of their accuracy. en
dc.language.iso en de_DE
dc.subject.classification Archäologie de_DE
dc.subject.ddc 930 de_DE
dc.subject.other pixel-based classification en
dc.subject.other OBIA en
dc.subject.other volcanic environment en
dc.type ConferencePaper de_DE
utue.publikation.fachbereich Archäologie de_DE
dc.title.en Multispectral Images Classification Applied to the Identification of Archaeological Remains: a Post-Dictive Perspective
utue.opus.portal caa2018 de_DE
utue.publikation.source CAA 2018: Human History and Digital Future de_DE


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