Use of a GIS predictive model for the identification of high altitude prehistoric human frequentations. Results of the Sessera valley project (Piedmont, Italy)
| Autor: | Davide Bertè, Sara Daffara, Gabriele Luigi Francesco Berruti, Sandro Caracausi, Francesco Rubat Borel |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
010506 paleontology
Population Socio-culturale 01 natural sciences Prehistory Human settlement Field research 0601 history and archaeology Glacial period education Holocene 0105 earth and related environmental sciences Earth-Surface Processes GIS predictive modelling Landscape archaeology Piedmont Settlement dynamics Western Alps education.field_of_study geography.geographical_feature_category 060102 archaeology Glacier 06 humanities and the arts Geography Physical geography Predictive modelling |
| Popis: | Starting from statistical samplings or anthropological dynamics hypothesis, GIS predictive models are particularly helpful for archaeological site detection. About 11,000 B.P., during the transition from the last glacial period and Holocene, there was a gradual decrease of glacier in Europe and groups of hunter-gatherers began to populate extensive lands in central-northern Europe and in the Alpine region. Currently, the most documented and known prehistoric human settlement are those located in the eastern Italian Alps, where data collected for more than thirty years allowed to formulate realistic hypothesis about the dynamics of human population in the region. In the western Alps, data about this subject are limited: the project “Survey Alta Valsessera (Piedmont, Italy)” is aimed to fill this gap by combining field research with methodologies elaborated in the eastern Alps to find traces of prehistoric and late roman human settlements. A GIS predictive model was realized in accordance with the parameters exposed in the model elaborated for the eastern Alps and the field records collected. This GIS predictive modelling allowed to identify different areas with high archaeological potential. Two of the areas so identified have been investigated in 2016 and two new sites have been localized. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|