Uppser Midwest RESAC Agriculture Forestry Land water Data
Change Classification Land Transformation Model Forecasting Urbanization

For more information on Change Classification research at UMN, please contact Marvin Bauer.

Change classification research at UMN is also supported by the Metropolitan Council of Minnesota.
Change Classification
Project Overview

Landsat classification can cost effectively produce landscape change maps and statistics. The Minneapolis-St.Paul metropolitan area has been used to evaluate the potential of satellite remote sensing for land cover classification and change analysis. The amount of land that was converted from agricultural, forest and wetland use to developed use between 1991 and 1998 was classified using Landsat imagery. The satellite change maps and statistics have accurately captured the patterns and trends of land use change and results have been compared to other traditional surveys. With these techniques we have the capacity to prepare such maps and accompanying data elements within two to three months of the satellite overpass, instead of the more common two to three years for conventional surveys.
Woodbury, MN: Land Change Classification
Landsat-derived maps of development between 1991 and 1998 (shown here in red), accurately reflect urban expansion in Woodbury, a suburban area east of Saint Paul, Minnesota.