Abstract
Predictive Archaeological Modeling Using GIS-Based Fuzzy Set Estimation
Track: Archaeology
Author(s): Philip Mink, Ted Grossardt, John Ripy, Keiron Bailey
Analytic predictive archaeological models can have great utility for state Departments of Transportation, but it is difficult to model the likelihood of prehistoric settlement using geographical proxy predictor variables because of the complexity of how settlement choices were actually made, and the complex interaction between these variables using GIS. In many cases classic statistical modeling approaches require too much data to be useful. This research reports on a preliminary predictive model that combines Spatial Analyst and fuzzy logic modeling to capture expert archaeological knowledge and convert this into predictive surface. A test area was defined in Woodford County, KY and five influencing factors were defined and calculated using ArcMap. Locations were sampled and probabilities estimated using both small and large group structured processes from a range of archeologists that fed an iterative fuzzy logic induction process. An output probability function was generated to create a predictive decision support layer.
Philip Mink
Kentucky Archaeological Survey
1020a Export Street
Lexington , Kentucky 40506-9854
United States
Phone: 859-257-1944
E-mail: philip.mink@uky.edu
Ted Grossardt
Univerisyt of Kentucky Transportation Center
176 Raymond Bldg
Lexington , Kentucky 40506-0281
United States
Phone: 8592577522
E-mail: tgrossardt@uky.edu
John Ripy
University of Kentucky Transportation Center
176 Raymond Bldg
Lexington , Kentucky 40506-0281
United States
Phone: 8592577536
E-mail: jripy@uky.edu
Keiron Bailey
University of Arizona
Harvill Building Box #2
Department of Geography and Regional Development
Tucson , Arizona 85712
United States
Phone: 5206121652
E-mail: kbailey@email.arizona.edu