Error that is inherent to geospatial raster data can propagate through geospatial models that are used in geographic information systems (GIS) for many natural science and social science applications. The error propagation can result in substantial and spatially variable prediction uncertainty in model results. Consequently, prediction uncertainty has important implications for the use and interpretation of geospatial model results by scientists, environmental regulators, resource managers, elected officials, and the general public.
