Filters: Tags: shrublands (X)
38 results (111ms)|
Filters
Date Range
Extensions Types
Contacts
Categories Tag Types
|
Predictions of raven occurrence intersected with high impact areas for sage-grouse populations. The index highlights regions where elevated raven occurrence is likely to impact breeding sage-grouse.
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: Great Basin,
biota,
geographic information systems (GIS),
geospatial analysis,
habitat alteration,
Minimum convex polygons created from survey locations at associated study sites.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Great Basin,
boundaries,
geographic information systems (GIS),
geospatial analysis,
habitat alteration,
The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified...
Predictions of raven occurrence in the absence of anthropogenic environmental effects. Raven point counts were related to landscape covariates using Bayesian hierarchical occupancy models and the means of the posterior distributions for relevant effects were used to generate the predictions.
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: Great Basin,
biota,
geographic information systems (GIS),
geospatial analysis,
habitat alteration,
This dataset provides spatial predictions of habitat suitability for current (1950 – 2000 yr) and mid-Holocene (8.3 ka – 4.2 ka) intervals using hindcasting, and three separate paleo-distributions calibrated on the packrat midden archive: those without bias correction (naïve), those created with a standard method (standard), and those created with a novel alternative (modeled) incorporating a three-stage model of bias. The raster layers contained here accompany the manuscript Inman et al. 2018 and were used to evaluate utility of a novel bias correction method (modeled) over classic methods. Spatial predictions of habitat suitability were created using MaxEnt version 3.4.0 (Phillips et al., 2006), a widely-used...
The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified...
The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified...
Predictions of raven occurrence in the absence of natural environmental effects. Raven point counts were related to landscape covariates using Bayesian hierarchical occupancy models and the means of the posterior distributions for relevant effects were used to generate the predictions.
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: Great Basin,
biota,
geographic information systems (GIS),
geospatial analysis,
habitat alteration,
As part of a 2018 Northwest Climate Adaptation and Science Center project, USGS researchers are releasing a series of spatially-explicit land-cover projections for the period 2018-2050 covering part of the northern Great Basin (Beaty Butte Herd Management Area, Hart Mountain National Antelope Refuge, and Sheldon National Refuge). The dataset contains an empirically-based business-as-usual (BAU) and an RCP8.5 climate change scenario executed for shrub, herbaceous, and bare cover types. Each scenario is executed 30 times (i.e. Monte Carlo simulations) to account for variability across historical change estimates derived from annual fractional cover maps generated by the National Land Cover Database. The map dates...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Geography,
Great Basin,
Land Use Change,
Nevada,
Oregon,
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2020. The RCMAP product suite consists of eight fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub and rule-based error maps including the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. We used an updated version of the 2016 base training data, with a more aggressive forest mask and reduced shrub and sagebrush cover bias in pinyon-juniper woodlands. We pooled training data in areas...
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2020. The RCMAP product suite consists of eight fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub and rule-based error maps including the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. We used an updated version of the 2016 base training data, with a more aggressive forest mask and reduced shrub and sagebrush cover bias in pinyon-juniper woodlands. We pooled training data in areas...
Western U.S. rangelands have been quantified as six fractional cover (0-100%) components over the Landsat archive (1985-2018) at 30-m resolution, termed the “Back-in-Time” (BIT) dataset. Robust validation through space and time is needed to quantify product accuracy. We leverage field data observed concurrently with HRS imagery over multiple years and locations in the Western U.S. to dramatically expand the spatial extent and sample size of validation analysis relative to a direct comparison to field observations and to previous work. We compare HRS and BIT data in the corresponding space and time. Our objectives were to evaluate the temporal and spatio-temporal relationships between HRS and BIT data, and to compare...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Central Basin and Range,
Land Use Change,
MT,
Montana,
NV,
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2020. The RCMAP product suite consists of eight fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub and rule-based error maps including the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. We used an updated version of the 2016 base training data, with a more aggressive forest mask and reduced shrub and sagebrush cover bias in pinyon-juniper woodlands. We pooled training data in areas...
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2020. The RCMAP product suite consists of eight fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub and rule-based error maps including the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. We used an updated version of the 2016 base training data, with a more aggressive forest mask and reduced shrub and sagebrush cover bias in pinyon-juniper woodlands. We pooled training data in areas...
This presentation aired as part of the Great Basin LCC webinar series on November 29, 2017. The presentation was given by Bruce Roundy of Brigham Young University.In this webinar, Dr. Bruce Roundy of Brigham Young University discusses climatic conditions that favor cheatgrass and those that favor desirable perennial herbs. He explains why conditions that favor cheatgrass are associated with less resistance and those that favor perennial herbs are associated with more resilience. The presentation suggests ways to increase resistance to weeds and system resilience when planning fuel control treatments in sagebrush steppe.
Categories: Data;
Tags: Cheatgrass,
EARTH SCIENCE > LAND SURFACE > LANDSCAPE,
Great Basin,
Great Basin,
Idaho,
The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified...
To map the baseline distribution of riparian forest and shrublands, we all included LANDFIRE Existing Vegetation Types (EVT) where the type contained the word "riparian", "woodland", "ravine" and "swamp". We also included aspen woodlands at elevations below 1524 m using ReGAP values, as these areas, upon inspection were found to be introduced vegetation and not aspen. These data are provided by Bureau of Land Management (BLM) "as is" and may contain errors or omissions. The User assumes the entire risk associated with its use of these data and bears all responsibility in determining whether these data are fit for the User's intended use. These data may not have the accuracy, resolution, completeness, timeliness,...
Types: Live Data;
Tags: Aquatic Development Index,
BLM,
Bureau of Land Management,
DOI,
Ecological Risk,
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2020. The RCMAP product suite consists of eight fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub and rule-based error maps including the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. We used an updated version of the 2016 base training data, with a more aggressive forest mask and reduced shrub and sagebrush cover bias in pinyon-juniper woodlands. We pooled training data in areas...
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2020. The RCMAP product suite consists of eight fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub and rule-based error maps including the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. We used an updated version of the 2016 base training data, with a more aggressive forest mask and reduced shrub and sagebrush cover bias in pinyon-juniper woodlands. We pooled training data in areas...
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2020. The RCMAP product suite consists of eight fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub and rule-based error maps including the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. We used an updated version of the 2016 base training data, with a more aggressive forest mask and reduced shrub and sagebrush cover bias in pinyon-juniper woodlands. We pooled training data in areas...
|
|
