This product contains plot location data in a .shp format as well as annual land cover, land use, and change process variables for each reference data plot in a separate .csv table. The same information available in the.csv file is also provided in a .xlsx format. The LCMAP Reference Data Product was utilized for evaluation and validation of the Land Change Monitoring, Assessment, and Projection (LCMAP) land cover and land cover change products. The LCMAP Reference Data Product includes the collection of an independent dataset of 25,000 randomly-distributed 30-meter by 30-meter plots across the conterminous United States (CONUS). This dataset was collected via manual image interpretation to aid in validation of the land cover and land cover change products as well as area estimates. The LCMAP Reference Data Product collected variables related to primary and secondary land use, primary and secondary land cover(s), change processes, and other ancillary variables annually across CONUS from 1984-2018. First posted - May 1, 2020 (available from author) Revised - September 21, 2021 (version 1.1) Revised - November 17, 2021 (version 1.2)

This product contains LCMAP CONUS Intensification Reference plot location data in a .shp format as well as annual land cover, land use, and change process variables for each reference data plot in a separate .csv table. The same information available in the.csv file is also provided in a .xlsx format. The LCMAP Reference Data Product was utilized for evaluation and validation of the Land Change Monitoring, Assessment, and Projection (LCMAP) land cover and land cover change products. The LCMAP Reference Data Product includes the collection of an independent dataset of 25,000 randomly-distributed 30-meter by 30-meter plots across the conterminous United States (CONUS). The LCMAP Reference Data Products collected variables related to primary and secondary land use, primary and secondary land cover(s), change processes, and other ancillary variables annually across CONUS from 1984–2018. This dataset includes 2,000 additional samples collected annually for 1984-2019 via manual image interpretation to increase the sample size of rare change classes at the CONUS level. This increased sample size will improve standard errors of the user's accuracy estimates for rare classes and improve estimates of area amounts of land cover change. These 2,000 samples were selected using a stratified random sampling process with 4 strata based off the LCMAP Collection 1.0 Science Products. These intensification samples were selected to assist in reducing the standard error focused on change classes.

This product contains LCMAP CONUS Intensification Reference plot location data in a .shp format as well as annual land cover, land use, and change process variables for each reference data plot in a separate .csv table. The same information available in the.csv file is also provided in a .xlsx format. The LCMAP Reference Data Product was utilized for evaluation and validation of the Land Change Monitoring, Assessment, and Projection (LCMAP) land cover and land cover change products. The LCMAP Reference Data Product includes the collection of an independent dataset of 25,000 randomly-distributed 30-meter by 30-meter plots across the conterminous United States (CONUS). The LCMAP Reference Data Products collected variables related to primary and secondary land use, primary and secondary land cover(s), change processes, and other ancillary variables annually across CONUS from 1984–2018. This dataset includes 2,000 additional samples collected annually for 1984-2019 via manual image interpretation to increase the sample size of rare change classes at the CONUS level. This increased sample size will improve standard errors of the user's accuracy estimates for rare classes and improve estimates of area amounts of land cover change. These 2,000 samples were selected using a stratified random sampling process with 4 strata based off the LCMAP Collection 1.0 Science Products. These intensification samples were selected to assist in reducing the standard error focused on change classes.

A validation assessment of Land Cover Monitoring, Assessment, and Projection Version 1 annual land cover products (1985–2017) for the Conterminous United States was conducted with an independently collected reference data set. Reference data land cover attributes were assigned by trained interpreters for each year of the time series (1984–2018) to a reference sample of 24,971 randomly-selected Landsat resolution (30m x 30m) pixels. The LCMAP and reference dataset labels for each pixel location are displayed here for each year, 1985–2017.

A validation assessment of Land Cover Monitoring, Assessment, and Projection Version 1 annual land cover products (1985–2017) for the Conterminous United States was conducted with an independently collected reference data set. Reference data land cover attributes were assigned by trained interpreters for each year of the time series (1984–2018) to a reference sample of 24,971 randomly-selected Landsat resolution (30m x 30m) pixels. The LCMAP and reference dataset labels for each pixel location are displayed here for each year, 1985–2017.

A validation assessment of Land Cover Monitoring, Assessment, and Projection Collection 1.1 annual land cover products (1985–2019) for the Conterminous United States was conducted with an independently collected reference dataset. Reference data land cover attributes were assigned by trained interpreters for each year of the time series (1984–2018) to a reference sample of 24,971 randomly-selected Landsat resolution (30m x 30m) pixels. The LCMAP and reference dataset labels for each pixel location are displayed here for each year, 1985–2018.

A validation assessment of Land Cover Monitoring, Assessment, and Projection Collection 1.1 annual land cover products (1985–2019) for the Conterminous United States was conducted with an independently collected reference dataset. Reference data land cover attributes were assigned by trained interpreters for each year of the time series (1984–2018) to a reference sample of 24,971 randomly-selected Landsat resolution (30m x 30m) pixels. The LCMAP and reference dataset labels for each pixel location are displayed here for each year, 1985–2018.

A validation assessment of Land Cover Monitoring, Assessment, and Projection Collection 1.3 annual land cover products (1985–2021) for the Conterminous United States was conducted with an independently collected reference dataset. Reference data land cover attributes were assigned by trained interpreters for each year of the time series (1984–2021) to a reference sample of 26,971 Landsat resolution (30m x 30m) pixels. The LCMAP and reference dataset labels for each pixel location are displayed here for each year, 1985–2021.

A validation assessment of Land Cover Monitoring, Assessment, and Projection Collection 1.3 annual land cover products (1985–2021) for the Conterminous United States was conducted with an independently collected reference dataset. Reference data land cover attributes were assigned by trained interpreters for each year of the time series (1984–2021) to a reference sample of 26,971 Landsat resolution (30m x 30m) pixels. The LCMAP and reference dataset labels for each pixel location are displayed here for each year, 1985–2021.

A validation assessment of Land Cover Monitoring, Assessment, and Projection Collection 1.3 annual land cover products (1985–2021) for the Conterminous United States was conducted with an independently collected reference dataset. Reference data land cover attributes were assigned by trained interpreters for each year of the time series (1984–2021) at a reference sample of 26,971 Landsat resolution (30m x 30m) pixels. These pixels were selected from a sample frame of all pixels in the ARD grid system which fell within the map area (Dwyer et al., 2018). Interpretation used the TimeSync reference data collection tool which visualizes Landsat images and Landsat data values for all usable images in the time series (1984–2021) (Cohen et al., 2010). Interpreters also referred to air photos and high-resolution images available in Google Earth as well as several ancillary data layers. The interpreted land cover attributes were crosswalked to the LCMAP annual land cover classes: Developed, Cropland, Grass/Shrub, Tree Cover, Wetland, Water, Snow/Ice and Barren. Validation analysis directly compared reference labels with annual LCMAP land cover map attributes by cross tabulation. The results of that assessment are reported here as confusion matrices for land cover agreement and land cover change agreement. Accuracy and standard errors have been calculated using stratified estimation (Stehman, 2014). Land cover class proportions were also estimated from the reference data for each year, 1985–2021. A cluster sampling formulation was used to calculate standard sampling error for summary tables reporting results for multiple years of data comparison.