Deriving crop specific covariate data sets from multi-year NASS geospatial cropland data layers

The National Agricultural Statistics Service (NASS) Area Sampling Frames (ASFs) are based on the stratification of US land cover by percent cultivation. Recently, an automated stratification method based on the NASS Cropland Data Layer (CDL) was developed to efficiently and objectively stratify US land cover. This method achieved higher accuracies in all cultivated strata with statistical significance at a 95% confidence level. This paper proposed to develop crop specific covariate data based on 2007 - 2010 CDLs. Crop (corn, soybeans, wheat and cotton) and non crop (forest, urban and water) covariate data were derived and validated for six states. Producer and user accuracies for the covariate data sets were based on independent 2011 Farm Service Agency Common Land Unit data and 2011 CDLs. Non crop covariate data were validated using the National Land Cover Data 2006. Covariate data were used within NASS to conduct substratification of the 2013 Oklahoma ASF.