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Distribution analysis of bone findings in the prehistoric site of Mondeval de Sora (Belluno - Italy): issues and proposals
Last modified: 2011-12-22
Abstract
The use of total station in the excavation of prehistoric sites and the processing of the excavation data with GIS has been introduced gradually since the 90s of last century. Such use is intended, among other things, to determine the spatial coordinates of the different archaeological objects, in order to perform an analysis of their distribution within the occupation area. This type of study aims to identify a possible intentional use of space by the ancient inhabitants, an aspect which could not be applied prior to the introduction of the practice of coordinating the findings, because of the lack of necessary data (spatial coordinates) of the individual findings. The only possibility is to readjust the excavation data and the database associated with them. This paper presents the results obtained from the attempt in this direction, made for a stratigraphic unit of the site Mondeval de Sora (Belluno - Italy), excavated from 1986 till 2000.
Mondeval de Sora is situated in the heart of the Dolomites (South Western Alps, Italy) at an altitude of about 2150 m asl; it represents a key deposits for the study of occupation and exploitation patterns of mountain areas on the Southern slope of the Alps during the early Holocene. This site was characterized by the presence of large quantities of finds, so that it became necessary to excavate through the square and sub-square method. For this reason the only data related to the findings from this site, which were useful for analysing their spatial distribution, were the number of objects, broken down by type and material, found in each square. A further complication arose also because the squares of side 1m, were excavated through sub-squares with sides of 33 cm, or 25 cm, or 10 cm, due to the abundance of findings, and sometimes a single square was excavated through several layers (up to 3), each consisting of sub-squares with different size. The first part of the work was dedicated to homogenize the number of findings which were redistributed into sub-squares of 33 cm, for all the squares; then the database was changed in order to make it usable within a GIS. Finally, an analysis was made of distribution of the finds, which for this work were only bones. This analysis was performed by the method of interpolation, using the Krige algorithm, and through a classification of the different sub-squares, using the statistical method of "quintiles", adapted to the needs of this case. In the final phase of the work the results obtained with the two methods were compared, pointing out the strengths and weaknesses of each.
Mondeval de Sora is situated in the heart of the Dolomites (South Western Alps, Italy) at an altitude of about 2150 m asl; it represents a key deposits for the study of occupation and exploitation patterns of mountain areas on the Southern slope of the Alps during the early Holocene. This site was characterized by the presence of large quantities of finds, so that it became necessary to excavate through the square and sub-square method. For this reason the only data related to the findings from this site, which were useful for analysing their spatial distribution, were the number of objects, broken down by type and material, found in each square. A further complication arose also because the squares of side 1m, were excavated through sub-squares with sides of 33 cm, or 25 cm, or 10 cm, due to the abundance of findings, and sometimes a single square was excavated through several layers (up to 3), each consisting of sub-squares with different size. The first part of the work was dedicated to homogenize the number of findings which were redistributed into sub-squares of 33 cm, for all the squares; then the database was changed in order to make it usable within a GIS. Finally, an analysis was made of distribution of the finds, which for this work were only bones. This analysis was performed by the method of interpolation, using the Krige algorithm, and through a classification of the different sub-squares, using the statistical method of "quintiles", adapted to the needs of this case. In the final phase of the work the results obtained with the two methods were compared, pointing out the strengths and weaknesses of each.