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Automated spatial attribute correlation towards minoan findings prediction with the use of a geographic information system

Sartzetaki Maria

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Year 2019
Type of Item Master Thesis
Bibliographic Citation Maria Sartzetaki, "Automated spatial attribute correlation towards minoan findings prediction with the use of a geographic information system", Master Thesis, School of Mineral Resources Engineering, Technical University of Crete, Chania, Greece, 2019
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Geographic Information Systems (GIS) offer a variety of tools and methodologies for organizing, processing and displaying spatial data, bringing new technological and research approaches to sciences such as archeology.Knowledge about the geographic location of archaeological finds, mobile or not, is based on spatial or temporal trends, choices, phenomena, processes, conditions, correlations and is incomplete but can be approached by modeling systems with main reference to the geographical area. In this paper we propose the synthesis of a series of spatial and temporal correlations between archaeological, geographic, anthropogenic and natural data, for the prediction of archaeological finds through a GIS.As a case of study, the Akrotiri area of Chania was chosen, the area of which is approximately 112 km2. For this area, data were collected from public services, altitude data and data about archaeological sites of the area of interest, which were collected by the Institute of Mediterranean Studies of the Foundation for Research and Technology based in Rethymnon. Within the framework of the work, automatic and semiautomatic tools for determining spatial and temporal properties / correlations were developed Moreover, an integrated database which allows the formulation and retrieval of complex queries for specific archaeological sites taking into account the time parameter was also created.With the introduction of the concept of autocorrelation and among the new types of data , of queries and the findings themselves, we can create a series of complex probability maps that predict the existence of archaeological finds in the study area.

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