This product contains LCMAP CONUS 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. This LCMAP Reference Data Product includes the collection of an independent dataset of 25,000 randomly-distributed and 2,000 stratified random 30-meter by 30-meter samples across the conterminous United States (CONUS). The 2,000 samples were selected using a stratified random sampling process with 4 strata based off the LCMAP Collection 1.0 Science Products.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?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. 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. LCMAP Collection 1.0 annual land cover products covered years 1985?2017 and the validation of the Collection 1.0 products were reported in theLCMAP Version 1.0 Annual Land Cover and Land Cover Change Validation Tables.LCMAP Collection 1.1 products covered 1985-2018 and validation was reported in theLCMAP Collection 1.1 Annual Land Cover and Land Cover Change Validation Tables.LCMAP Collection 1.2 products covered 1985-2020 and validation was reported in the LCMAP Collection 1.2 Annual Land Cover and Land Cover Change Validation Tables.

A validation assessment of Land Cover Monitoring, Assessment, and Projection Collection 1.2 annual land cover products (1985-2018) 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 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 (1984-2018) (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, 1985-2018. A cluster sampling formulation was used to calculate standard sampling error for summary tables reporting results for multiple years of data comparison. LCMAP Collection 1.0 annual land cover products covered years 1985-2017 and the validation of the Collection 1.0 products were reported in the LCMAP Version 1.0 Annual Land Cover and Land Cover Change Validation Tables. LCMAP Collection 1.1 products covered 1985-2018 and validation was reported in the LCMAP Collection 1.1 Annual Land Cover and Land Cover Change Validation Tables.

A validation assessment of Land Cover Monitoring, Assessment, and Projection annual land cover products (2000-2019) for Hawaii 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 (2000-2019) to a reference sample of 600 Landsat resolution (30m x 30m) pixels. 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. Overall Hawaii land cover agreement across all years was found to be 83.4%. Annual accuracies are also reported.

The data are 475 thematic land cover raster?s at 2m resolution. Land cover classification was to the land cover classes: Tree (1), Water (2), Barren (3), Other Vegetation (4) and Ice & Snow (8). Cloud cover and Shadow were sometimes coded as Cloud (5) and Shadow (6), however for any land cover application would be considered NoData. Some raster?s may have Cloud and Shadow pixels coded or recoded to NoData already. Commercial high-resolution satellite data was used to create the classifications. Usable image data for the target year (2010) was acquired for 475 of the 500 primary sample locations, with 90% of images acquired within ?2 years of the 2010 target. The remaining 25 of the 500 sample blocks had no usable data so were not able to be mapped. Tabular data is included with the raster classifications indicating the specific high-resolution sensor and date of acquisition for source imagery as well as the stratum to which that sample block belonged. Methods for this classification are described in Pengra et al. (2015). A 1-stage cluster sampling design was used where 500 (475 usable), 5 km x 5 km sample blocks were the primary sampling units (note; the nominal size was 5km x 5km blocks, but some have deviations in dimensions due only partial coverage of the sample block with usable imagery). Sample blocks were selected using stratified random sampling within a sample frame stratified by a modification of the K?ppen Climate/Vegetation classification and population density (Olofsson et al., 2012). Secondary sampling units are each of the classified 2m pixels of the raster. This design satisfies the criteria that define a probability sampling design and thus serves as the basis to support rigorous design-based statistical inference (Stehman, 2000).

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 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 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. Overall CONUS land cover agreement across all years was found to be 82.6%. Annual and regional accuracies are also reported. LCMAP Version 1.0 annual land cover products covered years 1985-2017 and the validation of the Version 1.0 products were reported in the LCMAP Version 1.0 Annual Land Cover and Land Cover change Validation Tables.

Area estimates of land cover and land cover change are often based on reference class labels determined by analysts interpreting satellite imagery and aerial photography. Different interpreters may assign different reference class labels to the same sample unit. This dataset include land cover attributes for the year 2000 assigned by 7 image analysts, working independently of each other, to a set of 300 sample locations from a region of the Pacific Northwest of the United States. This data was used in an evaluation of the impact of interpreter variability on variance estimation.

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 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. Overall CONUS land cover agreement across all years was found to be 82.5%. Annual and regional accuracies are also reported.

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.