Thematic Accuracy Assessment of the NLCD 2016 Land Cover for the Conterminous United States

The National Land Cover Database (NLCD) is an operational land cover monitoring program providing updated land cover and related information for the United States at five-year intervals. NLCD2016 extends temporal coverage to 15 years (2001 - 2016). We collected land cover reference data for the 2011 and 2016 nominal dates to report land cover accuracy for the NLCD2016 database 2011 and 2016 land cover components at Level II and Level I and for Level I 2011 - 2016 land cover change using two definitions of agreement. For both the 2011 and 2016 land cover components, single-date Level II overall accuracies (OA) were 72% (standard error of ± 0.9%) when agreement was defined as match between the map label and primary reference label only and 86% (± 0.7%) when agreement also included the alternate reference label. The corresponding level I OA for both dates were 79% (± 0.9%) and 91% (± 1.0%). The 2011 - 2016 user's and producer's accuracies (UA and PA) were ~75% for forest loss and PA for water loss, grassland loss, and grass gain were > 70% when agreement included a match between the map label and either the primary or alternate reference label. Depending on agreement definition and level of the classification hierarchy, OA for the 2011 land cover component of the NLCD2016 database was about 4% to 7% higher than OA for the 2011 land cover component of the NLCD2011 database, suggesting that the changes in mapping methodologies initiated for production of the NLCD2016 database have led to improved product quality. Additionally, we used the reference dataset collected for assessment of the NLCD2011 database to assess the 2001 and 2006 land cover components of the NLCD2016 database. OA for the 2001 and 2006 land cover components was 1% - 5% lower than OA for the 2011 and 2016 land cover components of the NLCD2016 database. Higher OA for 2011 and 2016 land cover components of the NLCD2016 database relative to OA for its 2001 and 2006 components may be attributable to differences in reference data quality.