Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, May 2021, v1

This dataset provides early estimates of 2021 exotic annual grasses (EAG) fractional cover predicted on May 3rd. We develop and release EAG fractional cover map with an emphasis on cheatgrass (Bromus tectrorum) but it also includes number of other species, i.e., Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L., Bromus japonicus, Bromus madritensis L., Bromus racemosus, Bromus rubens L., Bromus secalinus L., Bromus texensis (Shear) Hitchc., and medusahead (Taeniatherum caput-medusae. The dataset was generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring data (AIM) plots; Harmonized Landsat and Sentinel-2 (HLS) based 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. A total 17,536 AIM plots from years 2016 - 2019 were used to train an ensemble of five-fold regression models using a cross-validation approach (each observation was used as test data once) that developed EAG fractional cover maps. The geographic coverage includes arid and semi-arid rangelands in the western U.S.

Data and Resources

Field Value
accessLevel public
bureauCode {010:12}
catalog_@context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
catalog_conformsTo https://project-open-data.cio.gov/v1.1/schema
catalog_describedBy https://project-open-data.cio.gov/v1.1/schema/catalog.json
identifier USGS:6091af4bd34e791692e16886
metadata_type geospatial
modified 20220210
old-spatial -124.9400, 31.1700, -109.0000, 49.0000
publisher U.S. Geological Survey
publisher_hierarchy Department of the Interior > U.S. Geological Survey
resource-type Dataset
source_datajson_identifier true
source_hash c51e752a855caabd49c65bd8e05a11480f535d92
source_schema_version 1.1
spatial {"type": "Polygon", "coordinates": [[[-124.9400, 31.1700], [-124.9400, 49.0000], [ -109.0000, 49.0000], [ -109.0000, 31.1700], [-124.9400, 31.1700]]]}
theme {geospatial}
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • amerigeo
  • amerigeoss
  • annual-grass
  • annual-herbaceous
  • arizona
  • california
  • cheatgrass
  • ckan
  • colorado
  • exotic
  • geo
  • geoss
  • great-basin
  • harmonized-landsat-sentinel
  • idaho
  • invasive-species
  • kansas
  • medusahead
  • montana
  • national
  • ndvi
  • nebraska
  • nevada
  • new-mexico
  • nonindigenous-species
  • north-america
  • north-dakota
  • noxious
  • oklahoma
  • oregon
  • red-brome
  • remote-sensing
  • rye-brome
  • sagebrush
  • soft-brome
  • south-dakota
  • texas
  • texas-brome
  • united-states
  • usgs-6091af4bd34e791692e16886
  • utah
  • washington
  • western-united-states
  • wyoming
isopen False
license_id notspecified
license_title License not specified
maintainer Devendra Dahal (CTR)
maintainer_email ddahal@contractor.usgs.gov
metadata_created 2025-11-22T16:48:21.759981
metadata_modified 2025-11-22T16:48:21.759985
notes This dataset provides early estimates of 2021 exotic annual grasses (EAG) fractional cover predicted on May 3rd. We develop and release EAG fractional cover map with an emphasis on cheatgrass (Bromus tectrorum) but it also includes number of other species, i.e., Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L., Bromus japonicus, Bromus madritensis L., Bromus racemosus, Bromus rubens L., Bromus secalinus L., Bromus texensis (Shear) Hitchc., and medusahead (Taeniatherum caput-medusae. The dataset was generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring data (AIM) plots; Harmonized Landsat and Sentinel-2 (HLS) based 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. A total 17,536 AIM plots from years 2016 - 2019 were used to train an ensemble of five-fold regression models using a cross-validation approach (each observation was used as test data once) that developed EAG fractional cover maps. The geographic coverage includes arid and semi-arid rangelands in the western U.S.
num_resources 2
num_tags 44
title Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, May 2021, v1