Predictive modeling for preventive Archaeology: overview and case study

Abstract

Abstract The use of GIS and Spatial Analysis for predictive models is an important topic in preventive archaeology. Both of these tools play an important role in the Support Decision System (SDS) for archaeological research and for providing information useful to reduce archaeological risk. Over the years, a number of predictive models in the GIS environment have been developed and proposed. The existing models substantially differ from each other in methodological approaches and parameters used for performing the analysis. Until now, only few works consider spatial autocorrelation, which can provide more effective results. This paper provides a brief review of the existing predictive models, and then proposes a new methodological approach, applied to the neolithic sites in the Apulian Tavoliere (Southern Italy), that combines traditional techniques with methods that allow us to include spatial autocorrelation analysis to take into account the spatial relationships among the diverse sites.