Spatially Projecting Local Population Change Using Planning Support Software

Shaun Golding, University of Wisconsin at Madison

This paper is born from an effort to project the spatial distribution of population growth expected in Vilas County, Wisconsin using, GIS-based planning support software. In the course of developing growth scenarios to reflect the impacts of migration, several barriers to producing reliable models have been encountered. These barriers are specific to rural locales in the midst of amenity growth, and include the difficulty in tracking seasonal resident flows, and the limited availability of spatial data in rural municipalities. This research suggests that accurate and locally applicable projections will require greater access to spatial data and a more nuanced understanding of the rate at which second-home owners become permanent residents. Furthermore, in order for local landuse projections to be fully utilized in the policy making process, applied demographers must assuage a political resistance to both landuse models and population projections harbored where population growth remains a contentious political issue.