Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, July 2021, (ver 2.0, January 2022)
Dates
Publication Date
2021-07-09
Time Period
2021-07-01
Revision
2022-01-06
Citation
Dahal, D., Pastick, N.J., Boyte, S.P, Parajuli, S., and Oimoen, M.J., 2021, Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, July 2021, (ver 2.0, January 2022): U.S. Geological Survey data release, https://doi.org/10.5066/P9FG6X9Q.
Summary
These datasets provide early estimates of 2021 fractional cover for exotic annual grass (EAG) species and a native perennial grass predicted on July 1 using satellite observation data available no later than June 28th. Four fractional cover maps comprise this release, along with the corresponding confidence maps, for: 1) a group of 17 species of EAGs (i.e., Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L., Bromus hordeaceus spp. hordeaceus, Bromus japonicus, Bromus madritensis L., Bromus madritensis L. ssp. rubens (L.) Duvin, Bromus L., Bromus racemosus, Bromus rubens L., Bromus secalinus L., Bromus tectorum L., Bromus texensis (Shear) Hitchc., and Taeniatherum [...]
Summary
These datasets provide early estimates of 2021 fractional cover for exotic annual grass (EAG) species and a native perennial grass predicted on July 1 using satellite observation data available no later than June 28th. Four fractional cover maps comprise this release, along with the corresponding confidence maps, for: 1) a group of 17 species of EAGs (i.e., Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L., Bromus hordeaceus spp. hordeaceus, Bromus japonicus, Bromus madritensis L., Bromus madritensis L. ssp. rubens (L.) Duvin, Bromus L., Bromus racemosus, Bromus rubens L., Bromus secalinus L., Bromus tectorum L., Bromus texensis (Shear) Hitchc., and Taeniatherum caput-medusae; 2) cheatgrass (Bromus tectrorum); 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 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 all the fractional cover maps. The geographic coverage includes arid and semi-arid rangelands in the western U.S.
First posted - July 9, 2021 (available from author)
Revised - Janaury 6, 2022 (version 2.0)
Dahal, D., Pastick, N.J., Boyte, S.P., Parajuli, S., Oimoen, M.J., and Megard, L.J., 2022, Multi-Species Inference of Exotic Annual and Native Perennial Grasses in Rangelands of the Western United States Using Harmonized Landsat and Sentinel-2 Data: Remote Sensing, v. 14, no. 4, p. 807.
The purpose for this release is to provide land managers and researchers with near real time estimates of spatially explicit exotic annual grasses percent cover in the study area. Appropriate use of the data should be defined by the user; however, this data comes with caveats. First, these estimates should be viewed as relative abundances. Second, comparing this dataset to similar datasets with different spatial resolutions or different dates can lead to substantial differences between dataset values.
Revision 2.0 by Devendra Dahal on Janaury 6, 2022. To review the changes that were made, see “RevisonHistory_Jan2022.txt” in the attached files section.