Predicting Opposition to Windfarms Using Census Data

Authors: Sarah Mills*, University of Michigan, Jane Wentrack, University of Michigan
Topics: Energy, Rural Geography, Land Use
Keywords: wind energy; rural land-use; community acceptance
Session Type: Paper
Day: 4/11/2018
Start / End Time: 1:20 PM / 3:00 PM
Room: Galerie 5, Marriott, 2nd Floor
Presentation File: No File Uploaded

Previous research has found that place attachment and relationship with the landscape are important determinants for an individual’s support or opposition to a windfarm. This research has largely suggested that those residents who value the landscape more for its utility (e.g., as a working landscape) and less for its scenic value are more supportive of wind energy (Hall et al., 2013; van der Horst, 2007; Veelen and Haggett, 2016). Thus, understanding the proportion of each of these types of residents in a community may help to predict community acceptance. Indeed, the extremely high support for wind energy in some communities--even among those who are not directly compensated--has been attributed to high proportions of residents who have a connection to agriculture or “the farmer community” (Sowers, 2006). Gathering individual-level survey data, however, to predict attitudes can be both time-consuming and expensive. This paper considers the extent to which census data measuring community-level land-use characteristics such as population density, percentage of land in agricultural production, and percentage of seasonal (vacation) homes can be used to predict community acceptance of wind. This exploratory study focuses on four Midwestern states (IL, IN, MI, MN) where rural communities run the spectrum from agriculture-centric to heterogeneous interests including rural-to-urban commuters and amenity-based landowners. We employ a survey of wind energy experts in each state to rank the relative level of contention associated with siting of each of the state’s utility-scale windfarms, and then assess whether there is any correlation with the census-derived land-use characteristics.

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