Western U.S. rangelands have been quantified as six fractional cover (0-100%) components over the Landsat archive (1985-2018) at 30-m resolution, termed the “Back-in-Time” (BIT) dataset. Robust validation through space and time is needed to quantify product accuracy. We leverage field data observed concurrently with HRS imagery over multiple years and locations in the Western U.S. to dramatically expand the spatial extent and sample size of validation analysis relative to a direct comparison to field observations and to previous work. We compare HRS and BIT data in the corresponding space and time. Our objectives were to evaluate the temporal and spatio-temporal relationships between HRS and BIT data, and to compare their response to spatio-temporal variation in climate. We hypothesize that strong temporal and spatio-temporal relationships will exist between HRS and BIT data and that they will exhibit similar climate response. We evaluated a total of 42 HRS sites across the western U.S. with 32 sites in Wyoming, and 5 sites each in Nevada and Montana. HRS sites span a broad range of vegetation, biophysical, climatic, and disturbance regimes. Our HRS sites were strategically located to collectively capture the range of biophysical conditions within a region. Field data were used to train 2-m predictions of fractional component cover at each HRS site and year. The 2-m predictions were degraded to 30-m, and some were used to train regional Landsat-scale, 30-m, “base” maps of fractional component cover representing circa 2016 conditions. A Landsat-imagery time-series spanning 1985-2018, excluding 2012, was analyzed for change through time. Pixels and times identified as changed from the base were trained using the base fractional component cover from the pixels identified as unchanged. Changed pixels were labeled with the updated predictions, while the base was maintained in the unchanged pixels. The resulting BIT suite includes the fractional cover of the six components described above for 1985-2018. We compare the two datasets, HRS and BIT, in space and time. Two tabular data presented here correspond to a temporal and spatio-temporal validation of the BIT data. First, the temporal data are HRS and BIT component cover and climate variable means by site by year. Second, the spatio-temporal data are HRS and BIT component cover and associated climate variables at individual pixels in a site-year.

Quantifying Western U.S. shrublands as a series of fractional components with remote sensing provides a new way to understand these changing ecosystems. The USGS NLCD team in collaboration with the BLM has produced the most comprehensive remote sensing-based quantification of Western U.S. shrublands to date. Nine shrubland ecosystem components, including percent shrub, sagebrush (Artemisia spp.), big sagebrush, herbaceous, annual herbaceous, litter, and bare ground cover, along with sagebrush and shrub heights, were quantified at 30-m resolution by mapping region. Each region required extensive ground measurement for model training and validation, two scales of remote sensing data from commercial high-resolution satellites and Landsat 8, and regression tree modeling to create component predictions. In the mapped portion (1,946,100 km²) of the total study area (2,557,556 km²), bare ground averaged 46.8%, shrub 14.4%, sagebrush 4.4%, big sagebrush 3.1%, herbaceous 22.8%, annual herbaceous 4.3% and litter 15.6%. Shrub height averaged 39.8 cm and sagebrush height 10.5 cm. Component accuracies using independent validation averaged R² values of 0.46, RMSE of 10.37 and nRMSE of 0.12, and cross validation averaged R² values of 0.72, RMSE of 5.09 and nRMSE of 0.062. Component composition strongly diverges by level III ecoregions, where 13 of 22 ecoregions are bare ground dominant, 8 are herbaceous dominant, and one is shrub dominant. Sagebrush physically covers 86,219 km², or 4.4%, of our study area, but it is present in 835,507 km², or 42.9%, of the non-masked area of our study area, underscoring its widespread distribution. This version contains some confusion between pinyon-juniper tree cover and shrubs. In a subsequent version, we have applied a more aggressive masking of tree canopy cover to each rangeland component. Specifically, we lowered the tree canopy cover threshold for exclusion from 40 to 25%. For pixels with 1-25% tree canopy cover we ensured that our primary components (shrub, herbaceous, litter, and bare ground) cover summed to 100% when added with the tree canopy. And, for the secondary components (sagebrush, big sagebrush, sagebrush height and shrub height) we reconciled to the primary component (shrub), excluding any pinyon-juniper woodlands. For the updated version with these changes applied, see https://doi.org/10.5066/P9MJVQSQ. This version of data were used as training for the Back-in-Time (BIT) fractional cover time series available at https://doi.org/10.5066/P9C9O66W. Component products can also be downloaded from www.mrlc.gov.

Quantifying Western U.S. shrublands as a series of fractional components with remote sensing provides a new way to understand these changing ecosystems. The USGS NLCD team in collaboration with the BLM has produced the most comprehensive remote sensing-based quantification of Western U.S. shrublands to date. Nine shrubland ecosystem components, including percent shrub, sagebrush (Artemisia spp.), big sagebrush, herbaceous, annual herbaceous, litter, and bare ground cover, along with sagebrush and shrub heights, were quantified at 30-m resolution by mapping region. Each region required extensive ground measurement for model training and validation, two scales of remote sensing data from commercial high-resolution satellites and Landsat 8, and regression tree modeling to create component predictions. In the mapped portion (1,946,100 km²) of the total study area (2,557,556 km²), bare ground averaged 46.8%, shrub 14.4%, sagebrush 4.4%, big sagebrush 3.1%, herbaceous 22.8%, annual herbaceous 4.3% and litter 15.6%. Shrub height averaged 39.8 cm and sagebrush height 10.5 cm. Component accuracies using independent validation averaged R² values of 0.46, RMSE of 10.37 and nRMSE of 0.12, and cross validation averaged R² values of 0.72, RMSE of 5.09 and nRMSE of 0.062. Component composition strongly diverges by level III ecoregions, where 13 of 22 ecoregions are bare ground dominant, 8 are herbaceous dominant, and one is shrub dominant. Sagebrush physically covers 86,219 km², or 4.4%, of our study area, but it is present in 835,507 km², or 42.9%, of the non-masked area of our study area, underscoring its widespread distribution. This version contains some confusion between pinyon-juniper tree cover and shrubs. In a subsequent version, we have applied a more aggressive masking of tree canopy cover to each rangeland component. Specifically, we lowered the tree canopy cover threshold for exclusion from 40 to 25%. For pixels with 1-25% tree canopy cover we ensured that our primary components (shrub, herbaceous, litter, and bare ground) cover summed to 100% when added with the tree canopy. And, for the secondary components (sagebrush, big sagebrush, sagebrush height and shrub height) we reconciled to the primary component (shrub), excluding any pinyon-juniper woodlands. For the updated version with these changes applied, see https://doi.org/10.5066/P9MJVQSQ. This version of data were used as training for the Back-in-Time (BIT) fractional cover time series available at https://doi.org/10.5066/P9C9O66W. Component products can also be downloaded from www.mrlc.gov.

Quantifying Western U.S. shrublands as a series of fractional components with remote sensing provides a new way to understand these changing ecosystems. The USGS NLCD team in collaboration with the BLM has produced the most comprehensive remote sensing-based quantification of Western U.S. shrublands to date. Nine shrubland ecosystem components, including percent shrub, sagebrush (Artemisia spp.), big sagebrush, herbaceous, annual herbaceous, litter, and bare ground cover, along with sagebrush and shrub heights, were quantified at 30-m resolution by mapping region. Each region required extensive ground measurement for model training and validation, two scales of remote sensing data from commercial high-resolution satellites and Landsat 8, and regression tree modeling to create component predictions. In the mapped portion (1,946,100 km²) of the total study area (2,557,556 km²), bare ground averaged 46.8%, shrub 14.4%, sagebrush 4.4%, big sagebrush 3.1%, herbaceous 22.8%, annual herbaceous 4.3% and litter 15.6%. Shrub height averaged 39.8 cm and sagebrush height 10.5 cm. Component accuracies using independent validation averaged R² values of 0.46, RMSE of 10.37 and nRMSE of 0.12, and cross validation averaged R² values of 0.72, RMSE of 5.09 and nRMSE of 0.062. Component composition strongly diverges by level III ecoregions, where 13 of 22 ecoregions are bare ground dominant, 8 are herbaceous dominant, and one is shrub dominant. Sagebrush physically covers 86,219 km², or 4.4%, of our study area, but it is present in 835,507 km², or 42.9%, of the non-masked area of our study area, underscoring its widespread distribution. This version contains some confusion between pinyon-juniper tree cover and shrubs. In a subsequent version, we have applied a more aggressive masking of tree canopy cover to each rangeland component. Specifically, we lowered the tree canopy cover threshold for exclusion from 40 to 25%. For pixels with 1-25% tree canopy cover we ensured that our primary components (shrub, herbaceous, litter, and bare ground) cover summed to 100% when added with the tree canopy. And, for the secondary components (sagebrush, big sagebrush, sagebrush height and shrub height) we reconciled to the primary component (shrub), excluding any pinyon-juniper woodlands. For the updated version with these changes applied, see https://doi.org/10.5066/P9MJVQSQ. This version of data were used as training for the Back-in-Time (BIT) fractional cover time series available at https://doi.org/10.5066/P9C9O66W. Component products can also be downloaded from www.mrlc.gov.

Quantifying Western U.S. shrublands as a series of fractional components with remote sensing provides a new way to understand these changing ecosystems. The USGS NLCD team in collaboration with the BLM has produced the most comprehensive remote sensing-based quantification of Western U.S. shrublands to date. Nine shrubland ecosystem components, including percent shrub, sagebrush (Artemisia spp.), big sagebrush, herbaceous, annual herbaceous, litter, and bare ground cover, along with sagebrush and shrub heights, were quantified at 30-m resolution by mapping region. Each region required extensive ground measurement for model training and validation, two scales of remote sensing data from commercial high-resolution satellites and Landsat 8, and regression tree modeling to create component predictions. In the mapped portion (1,946,100 km²) of the total study area (2,557,556 km²), bare ground averaged 46.8%, shrub 14.4%, sagebrush 4.4%, big sagebrush 3.1%, herbaceous 22.8%, annual herbaceous 4.3% and litter 15.6%. Shrub height averaged 39.8 cm and sagebrush height 10.5 cm. Component accuracies using independent validation averaged R² values of 0.46, RMSE of 10.37 and nRMSE of 0.12, and cross validation averaged R² values of 0.72, RMSE of 5.09 and nRMSE of 0.062. Component composition strongly diverges by level III ecoregions, where 13 of 22 ecoregions are bare ground dominant, 8 are herbaceous dominant, and one is shrub dominant. Sagebrush physically covers 86,219 km², or 4.4%, of our study area, but it is present in 835,507 km², or 42.9%, of the non-masked area of our study area, underscoring its widespread distribution. In this version, we have applied a more aggressive masking of tree canopy cover was applied to each rangeland component. Specifically, we have lowered the tree canopy cover threshold for exclusion from 40 to 25%. For pixels with 1-25% tree canopy cover we ensured that our primary components (shrub, herbaceous, litter, and bare ground) cover summed to 100% when added with the tree canopy. And, for the secondary components (sagebrush, big sagebrush, sagebrush height and shrub height) we reconciled to the primary component (shrub), excluding any pinyon-juniper woodlands. For a previous version without these updates applied, see https://doi.org/10.5066/P9LTU2QM. Component products can also be downloaded from www.mrlc.gov.

Quantifying Western U.S. shrublands as a series of fractional components with remote sensing provides a new way to understand these changing ecosystems. The USGS NLCD team in collaboration with the BLM has produced the most comprehensive remote sensing-based quantification of Western U.S. shrublands to date. Nine shrubland ecosystem components, including percent shrub, sagebrush (Artemisia spp.), big sagebrush, herbaceous, annual herbaceous, litter, and bare ground cover, along with sagebrush and shrub heights, were quantified at 30-m resolution by mapping region. Each region required extensive ground measurement for model training and validation, two scales of remote sensing data from commercial high-resolution satellites and Landsat 8, and regression tree modeling to create component predictions. In the mapped portion (1,946,100 km²) of the total study area (2,557,556 km²), bare ground averaged 46.8%, shrub 14.4%, sagebrush 4.4%, big sagebrush 3.1%, herbaceous 22.8%, annual herbaceous 4.3% and litter 15.6%. Shrub height averaged 39.8 cm and sagebrush height 10.5 cm. Component accuracies using independent validation averaged R² values of 0.46, RMSE of 10.37 and nRMSE of 0.12, and cross validation averaged R² values of 0.72, RMSE of 5.09 and nRMSE of 0.062. Component composition strongly diverges by level III ecoregions, where 13 of 22 ecoregions are bare ground dominant, 8 are herbaceous dominant, and one is shrub dominant. Sagebrush physically covers 86,219 km², or 4.4%, of our study area, but it is present in 835,507 km², or 42.9%, of the non-masked area of our study area, underscoring its widespread distribution. In this version, we have applied a more aggressive masking of tree canopy cover was applied to each rangeland component. Specifically, we have lowered the tree canopy cover threshold for exclusion from 40 to 25%. For pixels with 1-25% tree canopy cover we ensured that our primary components (shrub, herbaceous, litter, and bare ground) cover summed to 100% when added with the tree canopy. And, for the secondary components (sagebrush, big sagebrush, sagebrush height and shrub height) we reconciled to the primary component (shrub), excluding any pinyon-juniper woodlands. For a previous version without these updates applied, see https://doi.org/10.5066/P9LTU2QM. Component products can also be downloaded from www.mrlc.gov.

The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified by climate bin and assess spatial and temporal relationships with climate variables. Finally, we statistically evaluate the minimum time density needed to accurately characterize temporal patterns and relationships with climate drivers. Over the 30-yr period, shrub cover declined and bare ground increased. While few pixels had >10% cover change, a large majority had at least some change. All fractional components had significant spatial relationships with water year precipitation (WYPRCP), maximum temperature (WYTMAX), and minimum temperature (WYTMIN) in all years. Shrub and sagebrush cover in particular respond positively to warming WYTMIN, resulting from the largest increases in WYTMIN being in the coolest and wettest areas, and respond negatively to warming WYTMAX because the largest increases in WYTMAX are in the warmest and driest areas. These data can be used to answer critical questions regarding the influence of climate change and the suitability of management practices. Component products can be downloaded from www.mrlc.gov.

The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified by climate bin and assess spatial and temporal relationships with climate variables. Finally, we statistically evaluate the minimum time density needed to accurately characterize temporal patterns and relationships with climate drivers. Over the 30-yr period, shrub cover declined and bare ground increased. While few pixels had >10% cover change, a large majority had at least some change. All fractional components had significant spatial relationships with water year precipitation (WYPRCP), maximum temperature (WYTMAX), and minimum temperature (WYTMIN) in all years. Shrub and sagebrush cover in particular respond positively to warming WYTMIN, resulting from the largest increases in WYTMIN being in the coolest and wettest areas, and respond negatively to warming WYTMAX because the largest increases in WYTMAX are in the warmest and driest areas. These data can be used to answer critical questions regarding the influence of climate change and the suitability of management practices. Component products can be downloaded from www.mrlc.gov.