By Dan McFarlane, Graduate Research Assistant and
Anna Haines, Ph.D., Associate Professor and Land Use Specialist

If you are a resident or visitor to Wisconsin, you may have noticed changes on the land in the past few decades, mostly in the form of new homes where farmland or forests previously existed. Some call these new land uses sprawl, others call it market demand; but whatever it is, change is occurring. In addition to changes in land use, changes in land ownership and parcel size are also taking place. The growing demand for rural residential and recreational land can break up large tracts of productive lands. Many communities in Wisconsin are concerned about the loss of farmland and forests and have started to manage that change through various means. Studies have shown that viable farming and forestry operations are more efficient when located in large contiguous blocks of land. Improved land management techniques can contribute to the preservation of these areas.

New mapping tools can help to identify areas of concern and target regions for either land preservation or potential future development. Advances in digital mapping technology, such as Geographic Information Systems (GIS), have allowed counties to modernize their tax parcel information from a paper format into an integrated spatial database. Similar advances in spatial analysis have allowed researchers to display the geographic distribution of landscape features, distinguish patterns, and measure relationships, thereby improving the ability of planners and citizens to understand potential factors driving land ownership patterns. The ability to present results in colorful maps makes interpretation straightforward and much easier to communicate. This project demonstrates how a person does not need to be a statistical genius to utilize and understand landscape patterns.

Methods

Spatial tools¹ such as Hot Spot Analysis and Cluster Analysis were used to identify concentrations or clusters of various parcel attributes such as size, land use, or zip codes. The statistics indicate the extent to which each parcel is surrounded by similar values. Using parcel acreages we mapped and color-coded parcels based on clusters of large and small parcels. Because landowners sometimes retain ownership of new lots after subdividing their property, this analysis was performed on tax parcel boundaries rather than ownership boundaries. Using the tax parcels, we show where potential new ownership may occur.

Patterns of Land Ownership in Columbia County

  Click on maps to open and/or download the pdf version. The Columbia County map describes factors which may influence parcelization trends.

Interpreting the Results

If one were to look at a published plat book, identifying parcel patterns can be difficult. With this analysis (see maps above and in left panel), we are able to show the spatial pattern of parcels on a county-wide scale, with red "hot spots" indicating concentrations of small parcels and blue "hot spots" indicating concentrations of large parcels. Naturally, cities and villages show up as red hot spots indicating clustered small parcels. With this method, we are also able to pick out other hot spots in more distant rural areas. For example, shorelines along rivers and lakes are heavily clustered with small parcels. Access ramps to interstate highways, ridge tops and areas adjacent to public lands also appear to influence the clustering of small parcels. Features such as lack of water bodies, exclusive agriculture zoning, industrial forests, and public lands appear to influence the grouping of large parcels.

Conclusion

With easy-to-use tools included with most GIS software packages, it is possible to measure and display land ownership patterns using tax parcel data. Whether a community's goal is to protect farmlands, forests, or habitat corridors, understanding the patterns and spatial relationships of land ownership can help make better decisions regarding land use planning. The maps can help both planners and policy-makers visualize the parcel landscape and communicate important patterns back to the public. This analysis can also help improve decision-making regarding the location of future growth, land acquisition, farmland protection, and other policies.

References

Clark, C. D., Park, W., & Howell, J. (2006). Tracking farmland conversion and fragmentation using tax parcel data. Journal of Soil and Water Conservation, 61(5), 243-249.

Mitchell, A. (2005). The ESRI Guide to GIS Analysis (Volume 2: Spatial Measurements and Statistics). Redlands, CA: ESRI Press.

For More Information

The Center for Land Use Education would be pleased to perform the land ownership analysis highlighted in this article for interested counties. All we need is your county�s current digital tax parcel information in shapefile, coverage, or feature class format. Please contact our office at (715) 346-3783 for more information.