Earth Resources Observation and Science (EROS) Center
Email:
ddahal@contractor.usgs.gov
Office Phone:
605-594-2716
ORCID:
0000-0001-9594-1249
Location
EROS - Mundt Federal Building
47914 252nd Street
Sioux Falls
, SD
57198-9801
US
Supervisor:
Frederick M Badke
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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...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel, All tags...
Idaho,
Kansas,
Land Use Change,
Montana,
NDVI,
Nebraska,
Nevada,
New Mexico,
North Dakota,
Oklahoma,
Oregon,
South Dakota,
Texas,
Texas brome,
USGS Science Data Catalog (SDC),
United States,
Utah,
Washington,
Wyoming,
annual grass,
annual herbaceous,
cheatgrass,
exotic,
invasive species,
medusahead,
nonindigenous species,
noxious,
red brome,
remote sensing,
rye brome,
sagebrush,
soft brome,
western United States, Fewer tags
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These datasets provide early estimates of 2022 fractional cover for exotic annual grass (EAG) species and one native perennial grass species on a bi-weekly basis from May to early July. The EAG estimates are developed within one week of the latest satellite observation used for that version. Each bi-weekly release contains four fractional cover maps along with their corresponding confidence maps for: 1) a group of 16 species of EAGs, 2) cheatgrass (Bromus tectorum); 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 (AIM) data plots; Harmonized Landsat...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel, All tags...
Idaho,
Kansas,
Montana,
NDVI,
Nebraska,
Nevada,
New Mexico,
North Dakota,
Oklahoma,
Oregon,
Poa secunda,
South Dakota,
Texas,
Texas brome,
United States,
Utah,
Washington,
Wyoming,
annual grass,
annual herbaceous,
cheatgrass,
exotic,
invasive species,
medusahead,
nonindigenous species,
noxious,
perennial grass,
red brome,
remote sensing,
rye brome,
sagebrush,
soft brome,
western United States, Fewer tags
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Exotic annual grasses [EAG] are one of the most damaging biological stressors in western North America. Despite numerous environmental and societal impacts associated with EAG there remains a need to enhance regional monitoring capabilities to better guide management and conservation efforts. Here we provide estimates of historic and potential future trends in EAG abundance that were developed using linear trend analysis and machine learning techniques at a 30-m spatial resolution. Specifically, these data represent historic (1985 to 2019) and potential future (2025-2040) rates of exotic annual grass change as estimated using Theil-Sen regression and a process-constrained, random forest model assuming only changes...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Ecology,
Exotic annual grasses, cheatgrass, remote sensing,
Exotic annual grasses, cheatgrass, remote sensing,
Land Use Change,
Remote Sensing, All tags...
USGS Science Data Catalog (SDC),
biota, Fewer tags
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Exotic annual grasses are one of the most damaging biological stressors in western North America and increase the susceptibility of landscapes to wildfire occurrence. Here we couple estimates of long-term rangeland component fractions (e.g. exotic annual grasses) with remote sensing, climate data, and machine learning techniques to estimate the long-term (1985 to 2019) probability of wildfire occurrence (30-m spatial resolution) in sagebrush-dominated landscapes of the western United States.
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Ecology,
Exotic annual grasses, cheatgrass, remote sensing, wildfire,
Land Use Change,
Remote Sensing,
Remote sensing, wildfire occurrence, wildfire risk, All tags...
USGS Science Data Catalog (SDC),
biota, Fewer tags
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Spatially accurate annual crop cover maps are an important component to various planning and research applications; however, the importance of these maps varies significantly with the timing of their availability. Utilizing a previously developed crop classification model (CCM), which was used to generate historical annual crop cover maps (classifying nine major crops: corn, cotton, sorghum, soybeans, spring wheat, winter wheat, alfalfa, other hay/non alfalfa, fallow/idle cropland, and ‘other’ as one class for remaining crops), we hypothesized that such crop cover maps could be generated in near real time (NRT). The CCM was trained on 14 temporal and 15 static geospatial datasets, known as predictor variables, and...
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