The Use of Bayesian Allocation for the Optimization of Archaeological Survey Effort

Summary

This is an abstract from the "Bayesian Archaeology" session, at the 86th annual meeting of the Society for American Archaeology.

Today, many archaeological surveys have the goal of documenting, as completely as possible, the locations and character of sites, many of which are rare, unobtrusive, or both. Increasingly over the last three decades, archaeologists have used predictive models in a GIS to help them target spaces that are most likely to contain sites of interest, or sites under threat. However, they have largely ignored the very useful method of Bayesian allocation, which uses prior information to optimize the distribution of survey effort over space, in an interative fashion, so that the survey finds more sites, or finds particular sites more quickly and with less cost. With examples from Cyprus and Jordan, we demonstrate how we use prior knowledge about landscapes, coverage estimates, and number of surveyors available to allocate survey effort each day, with daily updates on coverage to provide new priors for the next day’s allocation. This has been successful for the detection of rarely discovered site types, such as Epipalaeolithic and early Neolithic sites in Cyprus, and Late Neolithic sites in northern Jordan.

This Resource is Part of the Following Collections

• Society for American Archaeology 86th Annual Meeting, Online (2021)   •
• Bayesian Archaeology

Keywords

Spatial Coverage

Record Identifiers

Abstract Id(s): 32663