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The study's goal was to downscale 2013 250-m expedited Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) to 30 m (Gu, Y. and Wylie, B.K., 2015, Developing a 30-m grassland productivity estimation map for central Nebraska using 250-m MODIS and 30-m Landsat-8 observations, Remote Sensing of Environment, v. 171, p. 291-298)using 2013 Landsat 8 data. The eMODIS NDVI was downscaled for four periods: mid spring, early summer, late summer and mid fall. The objective was to capture phenologies during periods that correspond to 1) annual grass growth, 2) annual grass senescence, 3) the optimal NDVI profile separation between sagebrush and other shrubs in the region, and...
This dataset provides a near-real-time estimate of 2018 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 July 1, 2018. This is the second iteration of an early estimate of herbaceous annual cover for 2018 over the same geographic area. The previous dataset used eMODIS NDVI data gathered through May 1 (https://doi.org/10.5066/P9KSR9Z4). The pixel values for this most recent estimate ranged from 0 to100% with...
The introduction of exotic plant species into the western United States has caused substantial changes to rangeland disturbance regimes and ecosystem structure and function. For example, exotic annual grass (EAG) invasion in western rangelands has increased wildfire frequency, which greatly reduces rangeland ecosystem diversity and leads to single-species dominance in many areas. Rangeland monocultures do not provide optimal carbon sequestration and other environmental processes necessary to sustain historically normal ecosystem structure, including the ecological diversity needed to support sagebrush obligates like Greater Sagegrouse, pygmy rabbit, and pronghorn. These obligates, as well as others, require contiguous,...
Categories: Data;
Tags: Bromus japonicus,
Bromus tectorum,
California (CA),
Cheatgrass,
Colorado (CO),
This data release consists of a video and individual image frames extracted from the original high frame rate video and used to derive remotely sensed estimates of surface flow velocity via particle image velocimetry (PIV). These data were acquired from the Tanana River near Nenana, Alaska, on July 14, 2020. The video was obtained from a satellite operated by Planet Labs as part of the SkySat constellation. The original video was recorded at 30 frames per second and is provided in a compressed, lower-resolution .mp4 format video file for viewing. In addition, Planet Labs provided the individual frames comprising the video as full resolution TIFF images. This data release consists of individual frames extracted...
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,...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
Idaho,
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...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Bromus tectorum,
California,
Colorado,
Desert,
Ecology,
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...
The dataset provides an estimate of 2018 herbaceous annual percent cover predicted on May 1st with an emphasis on annual grasses. The pixel values range from 0 to100 with an overall mean value of 8.32 and a standard deviation of +/-11.93. The model's test mean error rate (n = 1670), based on nine different randomizations, equals 4.9% with a standard deviation of +/- 0.15. This dataset was generated by integrating ground-truth measurements of annual herbaceous percent cover with 250-m spatial resolution eMODIS NDVI satellite derived data and geophysical variables into regression-tree software. The geographic coverage includes the Great Basin, the Snake River Plain, the state of Wyoming, and contiguous areas. We applied...
This data release includes a video acquired from a satellite and field measurements of flow velocity from the Tanana River in Alaska that were used to derive remotely sensed estimates of surface flow velocities via particle image velocimetry (PIV). The field data were collected on July 24, 2019, in cooperation with the USGS Alaska Science Center, and the satellite video was obtained on July 14, 2020. The purpose of this study was to assess the feasibility of inferring flow velocities from video acquired from a satellite in orbit above the river by tracking water surface features via a Particle Image Velocimetry (PIV) algorithm. Remote sensing of flow velocity could provide a more efficient, cost-effective alternative...
We integrated 250-m enhanced Moderate Resolution Imaging Spectroradiometer (eMODIS) Normalized Difference Vegetation Index (NDVI) with land cover, biogeophysical (e.g., soils, topography) and climate data into regression-tree software (Cubist®). We integrated this data to create a time series of spatially explicit predictions of herbaceous annual vegetation cover in sagebrush ecosystems, with an emphasis on annual grasses. Annual grass cover in sagebrush ecosystems is highly variable year-to-year because it is strongly dependent on highly variable weather patterns, particularly precipitation timing and totals. Annual grass cover also reflects past disturbances and management decisions. We produced 17 consecutive...
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%...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Bromus rubens,
Bromus tectorum,
California,
Colorado,
Desert,
Uncertainty of satellite discharge estimates is affected by choice of satellite sensor, hydraulic variable for observation, and discharge estimation algorithm, as well as the availability of ground-calibration data. Site selection is very important for reducing error and uncertainty in both conventional and satellite-based discharge measurements because geomorphic river characteristics have strong control over the relationships between discharge and depth, width, slope, and velocity. A ground-truth data set of 8,445 conventional hydraulic measurements, collected by acoustic Doppler current profilers (ADCP) at 503 stations in the United States was developed to examine correlation between river discharge and river...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ADCP,
HYDRoSWOT,
Hydrology,
NASA,
Remote Sensing,
This dataset provides a near-real-time estimate of 2017 herbaceous annual cover with an emphasis on annual grass (Boyte and Wylie. 2016. Near-real-time cheatrass 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 19, 2017. This is the second iteration of an early estimate of herbaceous annual cover for 2017 over the same geographic area. The previous dataset used eMODIS NDVI data gathered through May 1 (https://doi.org/10.5066/F7445JZ9). The pixel values for this most recent estimate ranged from 0 to100% with...
The dataset provides an estimate of 2017 herbaceous annual percent cover predicted on May 1st with an emphasis on annual grasses. The pixel values range from 0 to100 with an overall mean value of 7.1 and a standard deviation of +/-10.5. The model's test mean error rate (n = 1670), based on nine different randomizations, equals 4.9% with a standard deviation of +/- 0.15. This dataset was generated by integrating ground-truth measurements of annual herbaceous percent cover with 250-m spatial resolution eMODIS NDVI satellite derived data and geophysical variables into regression-tree software. The geographic coverage includes the Great Basin, the Snake River Plain, the state of Wyoming, and contiguous areas. We applied...
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