Exploring spatial autocorrelation in archaeological spaces using R
Channel: Recording Archaeology
Date: 2019-12-02

Spatial autocorrelation describes how the value of spatial data varies as the distance between the data increases or decreases, and it is based on the general observation that, in a geographical space, near things are more related than distant things (Tobler’s law). This property of spatial data, also known as spatial dependency, has proven extremely useful for the analysis of archaeological settlement patterns and assemblages, and it has contributed to explaining some important spatio-temporal processes at different scales: from the spread of cultural or socio-economical phenomena at continental level to the intra-site distribution of artefacts and ecofacts. Several statistical methods have been developed in different disciplines to assess autocorrelation (Moran’s I statistics, Mantel test, etc.), and most of them are applied using dedicated R packages. In this paper, I will provide an overview of the methods currently used in archaeology, and I will describe the different R packages available. Furthermore, I will explore the potential of new mathematical approaches to spatial dependency, I will show how these algorithms can be implemented using R and I will highlight their relevance for archaeological research. The purpose of this paper is to demonstrate that, for the analysis of spatial autocorrelation, R is more reliable, flexible and customizable than most of the GIS software routinely used by archaeologists.

Full title: Exploring spatial autocorrelation in archaeological spaces using R: state of research and new developments

(Francesco Carrer)