Integrating Point Pattern Analysis and Logistic Regression approaches for exploring the settlement pattern of the Versilia and Garfagnana mountains in Roman times
- Title
- Integrating Point Pattern Analysis and Logistic Regression approaches for exploring the settlement pattern of the Versilia and Garfagnana mountains in Roman times
- Creator(s)
- Basile, Salvatore
- Campus, Antonio
- Date
- 2023
- Is Part Of
-
Archeologia e Calcolatori
- Volume
- 34
- Issue
- 2
- Pages
- 87–104
- Language
- eng
- Rights
- CC BY-NC-ND 4.0
- Abstract
- Mountain archaeology has a long research tradition and in recent years the number of studies on this topic has increased considerably, shedding new light on the dynamics of mountain’s communities. Versilia and Garfagnana districts (Lucca, North-Western Tuscany) largely fall between the Apuan Alps and the Apennine ridge. Although these territories have never been systematically investigated, the collection of all available archaeological legacy data indicates a settlement pattern of undoubted interest for the Roman times. This paper aims at exploring the settlement pattern of these mountain territories, integrating Point Pattern Analysis and Logistic Regression to achieve a predictive map of archaeological presences and to analyse their interrelations with the environment. Analyses prove the spatial dependence of finds with geomorphological and pedological variables, but also with the distance to major watercourses and solar irradiation. Based on the considered variables, the predictive map confirms that the foothill and gentler slopes facing E-SE areas have suitable characteristics for permanent settlement. Moving towards the more inland and higher altitude territories, the non-event areas increase proportionally, especially along the ridges, and the steeper, north-facing areas. Thus, the results make it possible to integrate the archaeological framework, clarifying human-environment dynamics, and directing new studies.
- Cites
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- Spatial Point Patterns and Processes
- Archaeology and spatial analysis
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