Finding a Relatively Flat Archaeological Site with Minimal Ceramics: A Case Study from Iraqi Kurdistan

ABSTRACT

We present a new technique to detect flat archaeological sites with minimal ceramics using an unmanned aerial vehicle that maps surface stone concentrations. Methods deployed include point pattern analysis of stone concentrations and a machine-learning technique using unsupervised classification of visible stone signature qualities, which are used in simple linear regressions to compare with geophysical and ceramic surface survey results of a site in Iraqi Kurdistan. There is a stronger fit (r^2?=?0.77) between surface stone concentrations and architecture identified by geophysical measurement, while surveyed ceramics show a weaker fit to defined architecture (r^2?=?0.31). Surface stone concentrations are potentially a better proxy than ceramics for determining the presence of past settlement in regions where stone was commonly used, sites are relatively flat, and ceramics are found in low concentrations. The methods advanced here can be scaled to wider areas, particularly in mountainous regions, where surface stone features are present.