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Publication Date
3-1-2022
Publication Title
Journal of Archaeological Method and Theory
Abstract
Spatial analysis studies in Palaeolithic archaeology arise as indispensable research tools for understanding archaeopalaeontological sites. In general terms, spatial studies have been specialised in the description of the distribution of materials and in the definition of accumulation areas, with the aim of distinguishing intentional activities or studying postdepositional processes. In recent decades, the development of GIS tools has enabled huge strides forward in the field of spatial archaeology research, such as spatial inferential statistics. These tools are particularly useful in the identification and location of clustering from statistical criteria, facilitating the subsequent analysis of accumulations through other archaeological, taphonomic and spatial techniques, such as fabric analysis or directional distribution. The cluster analysis, and its contextualisation considering all the archaeological and stratigraphical variables, allows the inference of some of the processes and factors that could have taken part in the accumulation of materials, as well as assessing how this affected the composition and preservation of the archaeological assemblage. The present article reviews the more traditional and innovative methods for studying horizontal distribution patterns and the objective definition of clusters, highlighting the parameters, uses and limitations of these techniques. We present an application of these methods to different Palaeolithic sites, going through different scenarios, such as location (open-air vs. cave), context, scale (large vs. small area), excavation methodology and spatial record methods.
Document Type
Article
Digital Object Identifier (DOI)
https://doi.org/10.1007/s10816-021-09524-8
Recommended Citation
Sánchez-Romero, Laura; Benito-Calvo, Alfonso; and Rios-Garaizar, Joseba, "Defining and Characterising Clusters in Palaeolithic Sites: a Review of Methods and Constraints" (2022). KIP Articles. 8787.
https://digitalcommons.usf.edu/kip_articles/8787
