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These data can be used in a geographic information system (GIS) for any number of purposes such as assessing wildlife habitat, water quality, pesticide runoff, land use change, etc. The State data sets are provided with a 300 meter buffer beyond the State border to faciliate combining the State files into larger regions. The user must have a firm understanding of how the datasets were compiled and the resulting limitations of these data. The National Land Cover Dataset was compiled from Landsat satellite TM imagery (circa 1992) with a spatial resolution of 30 meters and supplemented by various ancillary data (where available). The analysis and interpretation of the satellite imagery was conducted using very large,...
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The dataset provides a near real time estimation of 2020 herbaceous mostly annual fractional cover predicted on July 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/P96PVZIF., Boyte et al. 2018 https://doi.org/10.5066/P9RIV03D.), but starting this year we are 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,...
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The dataset provides a spatially explicit estimate of 2019 herbaceous annual percent cover predicted on May 1st with an emphasis on annual grasses. The estimate is based on the mean output of two regression-tree models. For one model, we include, as an independent variable amongst other independent variables, a dataset that is the mean of 17-years of annual herbaceous percent cover (https://doi.org/10.5066/F71J98QK). This model's test mean error rate (n = 1670), based on nine different randomizations, equals 4.9% with a standard deviation of +/- 0.15. A second model was developed that did not include the mean of 17-years of annual herbaceous percent cover, and this model's test mean error rate (n = 1670), based...
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This dataset provides a near-real-time estimate of 2019 herbaceous annual cover with an emphasis on annual grass (Boyte and Wylie. 2016. Near-real-time cheatgrass percent cover in the Northern Great Basin, USA, 2015. Rangelands 38:278-284.) This estimate was based on remotely sensed enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) data gathered through June 24, 2019. This is the second iteration of an early estimate of herbaceous annual cover for 2019 over the same geographic area. The previous dataset used eMODIS NDVI data gathered through April 28, 2019 (https://doi.org/10.5066/P9ZEK5M1). The pixel values for this most recent estimate ranged from 0 to100%...
    map background search result map search result map National Land Cover Data Set 1992 for Wyoming 30 meter Early Estimates of Herbaceous Annual Cover in the Sagebrush Ecosystem (May 1, 2019) Near-real-time Herbaceous Annual Cover in the Sagebrush Ecosystem, USA, July 2019 Near real time estimation of annual exotic herbaceous fractional cover in the sagebrush ecosystem 30m, USA, July 2020 National Land Cover Data Set 1992 for Wyoming 30 meter Early Estimates of Herbaceous Annual Cover in the Sagebrush Ecosystem (May 1, 2019) Near-real-time Herbaceous Annual Cover in the Sagebrush Ecosystem, USA, July 2019 Near real time estimation of annual exotic herbaceous fractional cover in the sagebrush ecosystem 30m, USA, July 2020