Percolation Theory and the Effectiveness of Adaptive Sampling in Subsurface Survey
Percolation theory, used mainly in physics and materials science, describes the behavior of interconnected clusters in spatial lattices, but is also relevant to an age-old problem in archaeology: how best to detect buried sites with subsurface testing. It can provide insights into adaptive sampling protocols applied to two-dimensional scatters of artifacts. Our research focuses on adaptive sampling's impacts on our understanding of underlying distributions of artifacts and sites in survey by shovel tests, augering, or coring. Does adaptive sampling improve our ability to detect and recognize sites? Does it help us define site's boundaries or estimate their sizes? Or do we risk defining "sites" that are simply a creation of the research method?
We evaluate adaptive subsurface sampling and compare it to simple subsurface survey through simulation. This allows us to control for artifact density and clustering, size of artifact clusters, and orientation and spacing of the lattice. We also experiment with different versions of the method, varying, for example, the size or definition of the "neighborhood." The simulations and comparison to predictions based on percolation theory help us evaluate the utility of current survey protocols and to suggest improvements for future work.
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Percolation Theory and the Effectiveness of Adaptive Sampling in Subsurface Survey. Edward Banning, Isaac Ullah. Presented at The 81st Annual Meeting of the Society for American Archaeology, Vancouver, British Columbia. 2017 ( tDAR id: 429208)
Abstract Id(s): 16996