Fractional Estimates of Multiple Exotic Annual Grass (EAG) Species and Sandberg bluegrass in the Sagebrush Biome, USA, 2016 - 2022 (ver. 3.0, July 2023)

These datasets provide historical (2016 - 2021) estimates of fractional cover for exotic annual grass (EAG) species and a native perennial bunch grass. The study area covers arid and semi-arid rangelands of the western U.S. Four fractional cover maps per year comprise this release, along with the corresponding confidence maps, for: 1) a group of 17 species of EAGs; 2) cheatgrass (Bromus tectorum); 3) medusahead (Taeniatherum caput-medusae); and 4) Sandberg bluegrass (Poa secunda). These datasets were generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring (AIM) plots; remotely sensed data from the Harmonized Landsat and Sentinel-2 (HLS) product, i.e., Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI); other relevant environmental, vegetation, remotely sensed, and geophysical drivers; and artificial intelligence/machine learning techniques.

Note that a total of 17,536 AIM plots from years 2016 – 2019 were used to train an ensemble of regression-tree models and to develop 2016 - 2020 historical maps whereas a total of 19,415 AIM plots from years 2016 - 2021 were used to train the models and to develop 2021 maps. For the 2016 – 2020 maps, we applied a mask to areas above 2250-m elevation and pixels classified other than grassland/herbaceous or shrub (likely rangelands) by the 2016 National Land Cover Dataset (NLCD). For the 2021 maps, we masked areas above 2350-m elevation and pixels classified as other than grassland/herbaceous by the 2019 NLCD. The seed source variable (from Rangeland Analysis Platform (RAP) [Jones et al., 2018]) was used as one of the drivers for modeling of 2016 – 2020 maps but it was not used for modeling of 2021 maps. Besides these, all other predictor variables are identical for all sets of maps. For details, please check data quality information section.