The aim of this project is the definition of a methodology, designed to create socionatural models able to improve our understanding of ancient populations dynamics and settlement patterns. We propose the integration of Geographic Information Systems exploiting the advantages of free software combined with traditional archaeological techniques (field walking and survey). This work shows the application of this approach in a particular case study of the NE Iberian Peninsula, the middle basin of Ripoll river (Catalonia, Spain) as well as the theoretical and methodological discussions about the use of spatial analysis in archaeology. Also, we used the Libre Office suite for the creation of the database, and Quantum GIS and GRASS for geographical modeling and spatial analysis.The latest rescue excavations in this area has generated a huge volume of information about prehistoric sites. Nevertheless, it is not being used by common research due to the fragmentation and heterogeneity of data. There is some evidence that these prehistoric settlements have been closely related to the location of various water bodies and fertile soil areas.In particular, the Ripoll river are home to the first human groups established within this region. The river and its basin offered Paleolithic groups and early farmers a wide range of animal resources, plants and materials. This landscape was formed by rolling hills and meadows, forests, natural water springs and streams. Moreover, the river can be understood as a place of passage, a real path of cultural transmission and economic and social communication.We suggest spatial analysis and geostatistics as a basic research tool to explore these questions in relation to our area of study. This type of techniques are able to combine geographical, ecological and cultural variables. For this reason we suggest that they could be used to validate or refuse old hypotheses. Moreover, GIS can also integrate data coming from different paleoenviromental analysis, as well as radiocarbon dates.The main aim of this work is to present a useful methodology to integrate data from areas where a high number of rescue excavations were developed. In this sense, spatial analysis and predictive models are excellent tools devised to improve the planning of new excavations and support better management systems.
