Early estimates of Annual Exotic Herbaceous Fractional Cover in the Sagebrush Ecosystem, USA, May 2020

Dates

Publication Date: 2020-05-27
Time Period: 2020-05-01

Citation

Dahal, D., Pastick, N.J., Parajuli, S., and Wylie, B.K., 2020, Early estimates of Annual Exotic Herbaceous Fractional Cover in the Sagebrush Ecosystem, USA, May 2020: U.S. Geological Survey data release, https://doi.org/10.5066/P9ZZSX5Q.

Summary

The dataset provides an estimate of 2020 herbaceous mostly annual fractional cover predicted on May 1st with an emphasis on annual exotic grasses Historically, similar maps were produced at a spatial resolution of 250m (Boyte et al. 2019 https://doi.org/10.5066/P9ZEK5M1., Boyte et al. 2018 https://doi.org/10.5066/P9KSR9Z4.), but we are now mapping at a 30m resolution (Pastick et al. 2020 doi:10.3390/rs12040725). This dataset was generated using in situ observations from Bureau of Land Management’s (BLM) Assessment, Inventory, and Monitoring data (AIM) plots; weekly composites of harmonized Landsat and Sentinel-2 (HLS) data (https://hls.gsfc.nasa.gov/); relevant environmental, vegetation, remotely sensed, and geophysical drivers. These [...]

Summary

The dataset provides an estimate of 2020 herbaceous mostly annual fractional cover predicted on May 1st with an emphasis on annual exotic grasses Historically, similar maps were produced at a spatial resolution of 250m (Boyte et al. 2019 https://doi.org/10.5066/P9ZEK5M1., Boyte et al. 2018 https://doi.org/10.5066/P9KSR9Z4.), but we are now mapping at a 30m resolution (Pastick et al. 2020 doi:10.3390/rs12040725). This dataset was generated using in situ observations from Bureau of Land Management’s (BLM) Assessment, Inventory, and Monitoring data (AIM) plots; weekly composites of harmonized Landsat and Sentinel-2 (HLS) data (https://hls.gsfc.nasa.gov/); relevant environmental, vegetation, remotely sensed, and geophysical drivers. These data were integrating into regression tree (RT) models for prediction of weekly cloud free Normalized Difference Vegetation Index (NDVI). A total 11,002 AIM plots from years 2016 - 2019 were used to train an ensemble of five-fold RT models using a cross-validation approach (each observation was used as test data once). Cheatgrass (Bromus tectrorum) is the most common species, however, number of other species were included in this study: 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 Taeniatherum caput-medusae. The geographic coverage includes rangelands in the Great Basin, the Snake River Plain, the state of Wyoming, and contiguous areas. We applied a mask to areas above 2700-m elevation to target areas of unlikely substantial annual grass cover. To target likely sagebrush ecosystems, the mask also removed pixels classified as something other than shrub or grassland/herbaceous by the 2016 National Land Cover Dataset (NLCD).

Contacts

Point of Contact :: Devendra Dahal (CTR), Land Resources
Originator :: Devendra Dahal (CTR), Neal J Pastick (CTR), Sujan Parajuli, Bruce K Wylie
Metadata Contact :: Devendra Dahal (CTR), Land Resources
Distributor :: U.S. Geological Survey - ScienceBase
SDC Data Owner :: Earth Resources Observation and Science (EROS) Center
USGS Mission Area :: Land Resources
Publisher :: U.S. Geological Survey

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AnnHerb_nrtMay2020.xml Original FGDC Metadata	View	19.8 KB	application/fgdc+xml
AnnHerb_nrtMay2020.zip		651.24 MB	application/zip
May2020..png		618.72 KB	image/png

Related External Resources

Type: Related Primary Publication

Pastick, N.J.; Dahal, D.; Wylie, B.K.; Parajuli, S.; Boyte, S.P.; Wu, Z. Characterizing Land Surface Phenology and Exotic Annual Grasses in Dryland Ecosystems Using Landsat and Sentinel-2 Data in Harmony. Remote Sens. 2020, 12, 725, https://doi.org/10.3390/rs12040725.	https://doi.org/10.3390/rs12040725

Purpose

The overall goal to develop these data is to provide land managers and researchers with early season, near-real-time estimates of spatially explicit percent cover predictions of exotic herbaceous annual vegetation 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 datasets.

Early estimates of Annual Exotic Herbaceous Fractional Cover in the Sagebrush Ecosystem, USA, May 2020

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