The Great Plains Landscape Conservation Cooperative (GPLCC, http://www.greatplainslcc.org/) is a partnership that provides applied science and decision support tools to assist natural resource managers conserve plants, fish and wildlife in the mid- and short-grass prairie of the southern Great Plains. It is part of a national network of public-private partnerships—known as Landscape Conservation Cooperatives (LCCs, http://www.fws.gov/science/shc/lcc.html)—that work collaboratively across jurisdictions and political boundaries to leverage resources and share science capacity. The Great Plains LCC identifies science priorities for the region and helps foster science that addresses these priorities to support wildlife conservation throughout the Great Plains region. It also assists partners in building their own capacity to address scientific challenges associated with our rapidly changing environment.These data were compiled because the information did not previously exist as a single resource for the GPLCC area of interest, are intended to inform local and regional conservation and management strategies with a complete regional perspective. This dataset is a mosaic of two ReGAP landcover datasets: ReGAPSW and ReGAPNW. Refer to processing steps for the necessary attribute reclassification crosswalk.Data Originator:"Multi-season satellite imagery (Landsat ETM+) from 1999-2001 were used in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform, aspect, etc.) to model natural and semi-natural vegetation. The minimum mapping unit for this dataset is approximately 1 acre. Landcover classes are drawn from NatureServe's Ecological System concept, with 109 of the 125 total classes mapped at the system level. For the majority of classes, a decision tree classifier was used to discriminate landcover types, while a minority of classes (e.g. urban classes, sand dunes, burn scars, etc.) were mapped using other techniques."Data were the best available at the time of compilation (2011) with current information represented by a combination of national-scale datasets and state or other regional data (e.g. soils) that could be reasonably aggregated.