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Map of Survey Probability Model
 

Mn/Model

Minnesota Statewide Archaeological Predictive Model

Contact Us   Mn/Model Home | Archaeology | Geomorphology | Geographic Information Systems (GIS) | Implementation

 

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Model is the first archaeological predictive model to make survey bias explicit in the final results so that the model's value for any given place can be assessed.

Map of negative survey points and archaeological sites

As we evaluated the Site Probability Models, it became apparent that they predicted surveyed places almost as well as they predicted site locations. This implied a high degree of survey bias and reduced our confidence in the interpretation of the predictive models, posing the question of whether areas were categorized as low probabity because no sites were there or because there had been no surveys there. This led to the development of the Survey Probability Model, which might be thought of as a model of survey bias. This model has no precedent.

 

Reasons for Survey Bias

Archaeological field survey is very labor intensive, time-consuming, and, ultimately, expensive. Naturally, archaeologists are more interested in finding archaeological features and artifacts than in spending many hours surveying and finding nothing at all. Consequently, they tend to focus their survey efforst on places where they expect sites to be - usually places near water. Even so-called 'probabilistic' surveys usually are stratified so that more locations are surveyed near water than away from water. Although the goal of the 1995 and 1996 Mn/Model field surveys was to 'provide data on site location and non-site locations based on random sampling,' the archaeologists' stratified survey design gave 'rarer landforms... priority over more common ones to insure they be represented in the sample strategy.' A truly random survey, such as the 1997 Mn/Model field survey, would result in a sample representing each landform in proportion to its occurrence in the landscape.

 

Detecting Survey Bias

In Phases 1 and 2 of Mn/Model, we used 'negative survey points' as non-site locations. These were points mapped in sections that were surveyed, at least in part, but where no sites were found. By comparing the distribution of surveyed locations within the early models' high, medium, and low probability areas, it became apparent that survey distributions reflected archaeologists' notions of where sites were most likely to be found. Consequently, Mn/Model's predictive models are biased by the archaeologists' own intuitive models of probable site location. The map (above right) shows negative survey points in red and archaeological sites in black. The relationship of both to water features is apparent.

 

Modeling Survey Bias

To account for this bias, survey locations were modeled uisng the same methods and environmental variables that were used to model site locations. The resulting Survey Probability Model indicates which parts of the landscape have been adequately surveyed (darker purple in the map in the banner above).

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Incorporating Our Understanding of Bias into the Predictive Models
Finally, the Site Probability and Survey Probability models were combined to create the Survey Implementation Model. This model qualifies the values of site probability by reference to the values from the survey probability model.

 

 

 

 

 

 

 

MnModel Orange Bar Logo

Acknowledgements

Mn/Model was financed by the Minnesota Department of Transportation using funds set aside by the Federal Highway Administration's Intermodal Surface Transportation Efficiency Act.

 

Copyright Notice

The Mn/Model process and the predictive models it produced are copyrighted by the Minnesota Department of Transportation (MnDOT), 2000. They may not be used without MnDOT's Consent.