Land use and land cover (LULC) change occurs at a local level within contiguous ownership and management units (parcels), yet LULC models primarily use pixel-based spatial frameworks. The few parcel-based models being used overwhelmingly focus on small geographic areas, limiting the ability to assess LULC change impacts at regional to national scales. We developed a modified version of the Forecasting Scenarios of land-use change (FORE-SCE) model to project parcel-based agricultural change across the Northern Great Plains ecoregion of the Great Plains of the United States. A scenario representing an agricultural biofuel scenario was modeled from 2012 to 2030, using parcel data to represent real, contiguous ownership and land management units. The resulting LULC projection provides a vastly improved representation of landscape pattern over existing pixel-based models, while simultaneously providing an unprecedented combination of thematic detail and broad geographic extent.
These data represent 50 individual Monte Carlo runs for the 2012 to 2030 biofuel scenario in the Northern Glaciated Plains ecoregion. Each of the 50 individual runs represents one model realization of the scenario, with uncertainty parameters factored in. Each individual run is thus unique. A combination of the 50 individual runs can be used to assess relative probability of land-use class membership for each pixel in the modeled ecoregion.