Spatial modelling (also referred to as predictive models, similarity models and site location analysis) covers a range of topics related to developing an understanding of how past societies used and moved about the landscapes they inhabited.
Predictive modelling in archaeology is a technique used to identify the location of archaeological sites or materials in a region via the observed pattern in an archaeological sample (correlative models) or by using theoretical understandings of human behaviour (explanatory models). Willey’s seminal work in the 1950s recognised that environmental variables are a critical factor in human settlement location. As satellite data and improved efficiencies in computing power advanced through the 1970s and 1980s, spatial modelling techniques were developed to understand the relationship between environment and human settlement patterns.
Correlative predictive models seek to identify relationships between archaeological site locations and environmental variables such as elevation, slope and distance to water. Led by mainly North American researchers, these models were primarily developed to assist land/heritage managers to identify archaeologically sensitive areas in a quick and cost-effective manner. Correlative models identify where sites are likely to be located, but not why they are located there. Statements about cultural change and development cannot be derived from correlative models.
Explanatory models rely on archaeological theory to develop testable questions about where we would expect to find sites and what the environmental conditions of those locations would be. Then, areas of the landscape are identified that meet these predefined criteria using available environmental geospatial data. Led predominantly by research in Europe, explanatory predictive models use social variables, in concert with environmental variables, to test theoretical questions about human use of the landscape. By including theoretical perspectives, explanatory models can move beyond the limitations of correlative models, seeking to explain why site locations were chosen, not simply mapping where they are.
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