Pennsylvania Predictive Model Set – Realigning Old Expectations with New Techniques in the Creation of a Statewide Archaeological Sensitivity Model
Sponsored by the Pennsylvania Department of Transportation (PennDOT), this project endeavored to create a statewide Archaeological Predictive Model (APM) based on the known locations of over 18,000 recorded pre-contact archaeological sites within the Commonwealth. The purpose of this project was to create a set of sensitivity maps to aide in transportation planning and assist in the cultural resources management process. The creation of an APM covering 46,000 square miles required the development of a new set of computational and statistical tools for the storage and management of massive datasets, the use of parallel and "cloud" computing to apply modern statistical methods, and the adaptation of data science techniques developed in fields such as biology, ecology, and medicine. While the resultant approach was grounded in the lessons of nearly 40 years of APM study, the project demanded a fundamental rethinking of our field’s approaches and expectations. This presentation will explore the project’s mission, outline the computational framework and statistical methods used, evaluate the findings, and discuss the benefits and challenges of such an approach.
SAA 2015 abstracts made available in tDAR courtesy of the Society for American Archaeology and Center for Digital Antiquity Collaborative Program to improve digital data in archaeology. If you are the author of this presentation you may upload your paper, poster, presentation, or associated data (up to 3 files/30MB) for free. Please visit http://www.tdar.org/SAA2015 for instructions and more information.
Cite this Record
Pennsylvania Predictive Model Set – Realigning Old Expectations with New Techniques in the Creation of a Statewide Archaeological Sensitivity Model. Matthew Harris, Grace Ziesing. Presented at The 80th Annual Meeting of the Society for American Archaeology, San Francisco, California. 2015 ( tDAR id: 397792)
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min long: -80.815; min lat: 39.3 ; max long: -66.753; max lat: 47.398 ;