University of Wisconsin–Madison

Wisconsin Geospatial News

SCO conducting pilot project to develop a more accurate statewide Public Land Survey System dataset

In the early 1990’s, the Wisconsin Department of Natural Resources (DNR) had no automated methods of spatially-referencing the 48,000 land parcels they managed.  To better manage and administer their properties, they developed the 24K Landnet dataset of the Public Land Survey System (PLSS) in Wisconsin. Landnet debuted in 1996 and has maintained its status as the de facto standard for statewide PLSS data ever since. To create this dataset, the DNR digitized PLSS corners from USGS 7.5 minute, 1:24,000 scale, topographic maps along with data they received from other sources.  While robust at the time and still widely used, data with greater accuracy now exists at the local level in many areas in Wisconsin due to the remonumentation process which is underway. 

A primary role of a county surveyor is to restore and protect PLSS corner monuments as required by state legislation. These corner monuments are vital to property ownership rights and affect nearly every property description in Wisconsin. As counties complete remonumentation and record more accurate coordinates for corners, they become the custodians of the most accurate PLSS data in the state. 

The SCO is conducting a pilot study during 2011 – 2012 which will develop and test data integration methods for statewide production of contemporary PLSS data.  We are currently reviewing various data model standards and collaborating with local agencies to select and acquire data for inclusion in the pilot study.  We hope to publish a pilot study dataset using a subset of Wisconsin counties for user testing and comments in 2012.  The goal of this project is to consolidate more accurate local PLSS data into an integrated statewide format. 

Objectives of the pilot project include:

  • A data integration model that is capable of consolidating different datasets into one statewide data model which can be reproduced for use with other data types.
  • A more accurate PLSS dataset derived from local data wherever possible.
  • An authoritative PLSS dataset that provides comprehensive statewide coverage.
  • The development and testing of methodology to complete the first step in producing an updated and more accurate statewide PLSS database.

Anyone interested in learning more about this project please contact Timothy Kennedy or Brenda Hemstead