Featured Article - May 2021
Clarkson, Chris; Bellas, Angelo. Mapping stone: using GIS spatial modelling to predict lithic source zones. Journal of Archeological Science, Volume 46, June 2014, Pages 324-333.*
We present a new approach to predicting the location of sources of flakeable stone using GIS modelling of raw material proportions obtained from site assemblage data. This approach offers a valuable tool for locating potential source areas and investigating past lithic provisioning and landuse when abundant site assemblage data is available but precise source locations are unknown. Using published and grey literature on raw material composition for 84 sites, we generate a model of varying raw material concentrations for the Moreton Region of Southeast Queensland, Australia, and test our predicted source locations against known prehistoric quarries, geology maps and ground truthing of two key predicted areas with distinctive raw materials. Our results suggest distinct source areas are identifiable, suggesting that primary outcrops are more important sources of stone in this region than large streams and rivers.
We have presented a novel approach to locating possible lithic source zones using site material composition data where diverse raw material sources exist but their locations are largely unknown. Our analysis was able to yield four significant findings that would be important to any field project concerned with understanding the distribution and use of raw materials in the landscape:
1. prediction of the locations of likely source zones that fit well with the location
of known quarries,
2. detection of inconsistencies in material identification that may confuse predictive models and suggest the need to build consensus among local archaeologists over material identification,
3. generation of distance decay models that portray the influence of secondary sources on material concentrations and may be helpful in predictive modelling for heritage and research,
4. demonstration of the power of GIS in interrogating and making use of data languishing in grey literature, reports and museum collections to solve new research problems.