The Exotic Annual Grass (EAG) abundance dataset provides early season percent cover estimate of the exotic grass species in 30m spatial resolution for a mapped year in rangeland ecosystems of western United States. We plan to release these EAG estimates multiple times each year in early growing season. EAG is a continuous field consisting of abundance of non-native grass species whose life history is complete in one growing season. Cheatgrass (Bromus tectorum) is a dominant species, but this dataset also includes Bromus arvensis L., Bromus briziformis Fisch. & C.A. Mey. Bromus catharticus Vahl, Bromus commutatus Schrad, Bromus diandrus Roth, Bromus hordeaceus L., Bromus hordeaceus spp. Hordeaceus, Bromus japonicus Thunb, Bromus madritensis L., Bromus madritensis L. ssp. rubens (L.) Duvin, Bromus racemosus L., Bromus rubens L., Bromus secalinus L., Bromus texensis (Shear) Hitchc, and medusahead (Taeniatherum caput-medusae (L.) Nevski). The main objective of releasing these maps is to provide a tool for better monitoring EAG dynamics and informing conservation and management efforts at local to regional scales.
For additional information regarding creation of the EAG products:
Dahal, Devendra, Neal J. Pastick, Stephen P. Boyte, Sujan Parajuli, Michael J. Oimoen, and Logan J. Megard. "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 14, no. 4 (2022): 807. https://doi.org/10.3390/rs14040807
Pastick, Neal J., Bruce K. Wylie, Matthew B. Rigge, Devendra Dahal, Stephen P. Boyte, Matthew O. Jones, Brady W. Allred, Sujan Parajuli, and Zhuoting Wu. "Rapid Monitoring of the Abundance and Spread of Exotic Annual Grasses in the Western United States Using Remote Sensing and Machine Learning." AGU advances (2021). https://dx.doi.org/10.1029/2020AV000298.
Pastick, Neal J., Devendra Dahal, Bruce K. Wylie, Sujan Parajuli, Stephen P. Boyte, and Zhouting Wu. "Characterizing Land Surface Phenology and Exotic Annual Grasses in Dryland Ecosystems Using Landsat and Sentinel-2 Data in Harmony." Remote Sensing 12, no. 4 (2020): 725. https://dx.doi.org/10.3390/rs12040725.
Pastick, Neal J., Bruce K. Wylie, and Z. T. Wu. "Spatiotemporal Analysis of Landsat-8 and Sentinel-2 Data to Support Monitoring of Dryland Ecosystems." Remote Sensing 10, no. 5 (May 2018). https://dx.doi.org/doi:10.3390/rs10050791.