Monitoring US agriculture: the US Department of Agriculture, National Agricultural Statistics Service, Cropland Data Layer Program

TLDR

The National Agricultural Statistics Service (NASS) of the USDA produces the Cropland Data Layer (CDL), a raster‑formatted, geo‑referenced, crop‑specific land cover map derived from medium‑resolution satellite imagery, ground truth, and ancillary datasets such as the National Land Cover Data set. This paper provides an overview of the NASS CDL program. The program uses a decision‑tree supervised classification method, incorporating satellite imagery, ground truth, and ancillary data, and includes processing procedures, validation, accuracy assessment, product specifications, dissemination venues, and a crop acreage estimation methodology. CDL accuracy for 2009 ranged from 85 % to 95 % for major crop categories.

Abstract

The National Agricultural Statistics Service (NASS) of the US Department of Agriculture (USDA) produces the Cropland Data Layer (CDL) product, which is a raster-formatted, geo-referenced, crop-specific, land cover map. CDL program inputs include medium resolution satellite imagery, USDA collected ground truth and other ancillary data, such as the National Land Cover Data set. A decision tree-supervised classification method is used to generate the freely available state-level crop cover classifications and provide crop acreage estimates based upon the CDL and NASS June Agricultural Survey ground truth to the NASS Agricultural Statistics Board. This paper provides an overview of the NASS CDL program. It describes various input data, processing procedures, classification and validation, accuracy assessment, CDL product specifications, dissemination venues and the crop acreage estimation methodology. In general, total crop mapping accuracies for the 2009 CDLs ranged from 85% to 95% for the major crop categories.