A Geographic Information Systems Based Predictive Model For Native American Archaeological Sites At Fort Mccoy Monroe County Wisconsin

This research is a multi step method to predict unknown Paleoindian archaeological site locations within Pine Bluffs, Wyoming, situated in the southeastern corner of the state, using a Geographical Information System (GIS). The GIS technology is being used to predict Paleoindian archaeological site locations and will help demonstrate the geographic similarities and differences between already known Paleoindian archaeological sites and random non-site locations in the Pine Bluffs region. Using GIS, one can note the similarities and differences between the Paleoindian sites and the surrounding landscape and, with the help of logistic regression analysis, one can predict the location of unknown Paleoindian sites.

The research conducted under this grant was for the development of a Pilot Archaeological Database (PAD) for the Wisconsin Department of Transportation (WisDOT). The primary objective was to compile information on archaeological sites and to organize it in a centralized database for use by District 3 staff to comply with federal and state historic preservation legislation. The database would include information on archaeological sites in, or adjacent to, Interstate Highways (IH), United States Highways (USH), State Trunk Highways (STH), and County Trunk Highways (CTH). The study focused on three primary WisDOT District user groups: 1) Real Estate for the sale of excess lands; 2) Maintenance for the issuing of utility permits in highway right-of-way; and 3) Planning for use in the initial scoping of new transportation projects. As of 1998 there was no comprehensive and user friendly electronic information retrieval system for data generated during 40 years of archaeological research along Wisconsin's highways. Developing the database involved: 1) identifying user needs; 2) gathering all relevant data fields; 3) verifying the accuracy of the data; and 4) creating data tables structured to meet the needs of the users. This pilot project created a database for archaeological sites along the IH/USH/STH/CTH highway systems in northeastern Wisconsin.

Although archaeologists are using GIS technology at an accelerating rate, publication of their work has not kept pace. A state-of-the-art exploration the subject, GIS and Archaeological Site Location Modeling pulls together discussions of theory and methodology, scale, data, quantitative methods, and cultural resource management and uses location models and case studies to illustrate these concepts. This book, written by a distinguished group of international authors, reassesses the practice of predictive modeling as it now exists and examines how it has become useful in new ways. A guide to spatial procedures used in archaeology, the book provides a comprehensive treatment of predictive modeling. It draws together theoretical models and case studies and explains how modeling may be applied to future projects. The book illustrates the various aspects of academic and practical applications of predictive modeling. It also discusses the need to assess the reliability of the results and the implications of reliability assessment on the further development of predictive models. Of the books available on GIS, some touch on archaeological applications but few cover the topic in such depth. Both up to date and containing case studies from a wide range of geographical locations including Europe, the USA, and Australia, this book sets a baseline for future developments.

The Greater Yellowstone Region was a destination for nomadic hunter-gatherers for at least 12,000 years. Archaeological sites representing the whole spectrum of time, cultures, and activities, have been found throughout the region. Within Yellowstone National Park a number of Paleoindian projectile points and other related cultural materials have been recorded, however, only a handful of buried Paleoindian sites have been identified and excavated. Considering the nature of the archaeological record in the area, some interesting questions surface about the value of the information recorded on the Paleoindian sites. In terms of Yellowstone National Park (YNP) Paleoindian archaeology, is it possible to use the existing Paleoindian sites to make inferences about the landscape choices of Paleoindian cultures? Can the relationship between the location of known Paleoindian sites and the environment be modeled using quantitative methods? If so, is it possible to use the information about land use patterns derived from a known set of sites to find additional, currently unknown, Paleoindian sites? This paper attempts to answer those questions through the development of an archaeological predictive model, focused on Paleoindian sites, for Yellowstone National Park. Utilizing Geographic Information Systems (GIS) and statistical software, a probability model has been created that relates the existence or nonexistence of Paleoindian cultural materials with sixteen selected environmental features. The model output classifies areas within YNP through a set of environmental characteristics favorable for finding Paleoindian cultural material.

The search for archaeological materials dating to 15,000 yr BP along the southern Oregon coast is a formidable task. Using ethnographic, theoretical, and archaeological data, landscape resources which would have influenced land-use and occupation location decisions in the past are highlighted. Additionally, environmental data pertaining to the late Pleistocene is examined to determine what landscape features may have been used by human groups 15,000 years ago and to determine how these landscape features may have changed since that time. These landscape resource features are included in the modeling project as independent variables. The dependent variable in this modeling project is relative probability that an area will contain archaeological materials dating to the time period of interest. Two predictive locational models are created to facilitate the search process. These models mathematically combine the independent variables using two separate approaches. The hierarchical decision rule model approach assumes that decision makers in the past would have viewed landscape features sequentially rather than simultaneously. The additive, or weighted-value, approach assumes that a number of conditional preference aspects were evaluated simultaneously and that different environmental variables had varying amounts of influence on the locational choices of prehistoric peoples. Integration of the data and mathematical model structures into a Geographic Information System (GIS) allows for spatial analysis of the landscape and the prediction of locations most likely to contain evidence of human activity dating to 15,000 years ago. The process involved with variable integration into the GIS is delineated and results of the modeling procedures are presented in spatial, map-based formats.

Predictive modeling for archaeological sites uses known environmental and geophysical correlates of sites, direct historical information, theory of settlement and subsistence system, and archaeological data substantiating these to identify areas with varying degrees of archaeological potential.