Date of Award


Degree Name

Master of Science


Geography and Environmental Resources

First Advisor

Lant, Christopher


The purpose of this research is to generate the most accurate model possible for predicting locations most suitable for new wind energy development using a case study of Iowa. With the United States poised for significant growth in electricity generation from wind and other renewable resources, this research can help developers, transmission planners, landowners, as well as academics in predicting optimal locations for development. Iowa currently has the second greatest installed wind energy capacity and highest percentage of energy generated from wind of all the states, and has excellent resources and central location for a high level of continued development. This research employs a variety of methods including traditional constraint mapping techniques, logistic regression, and a hybrid of both approaches in attempting to produce the best predictive model possible. The best performing logistic regression model with 11 variables correctly predicts 90.1% of overall observations. A variety of output maps are produced and analyzed, and many suggestions for future research in this area are presented.




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