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Ecological regions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components.
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This dataset contains the fire perimeters in the western United States since 1984. It was made by combining MTBS and GeoMAC data. Fires greater than 1000 acres came from MTBS, while fires less than 1000 acres came from GeoMAC. This data was published July 2016.
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This fire risk assessment was conducted to understand how resilience and resistance and sage-grouse breeding bird habitat may inform wildland fire management decisions including preparedness, suppression, fuels management and post-fire recovery for western sagebrush communities. The assessment is based on the premise that risk = probability of a threat and the consequences of that threat (negative or positive). Fire risk was determined by the probability of a large wildfire and the consequences of fire on greater sage-grouse breeding habitat. These consequences were modified by the capacity of sage-grouse habitat to be resilient and thus recover from fire processes, and be resistant to invasive annual grasses. The...
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More than 23,000 field measurements of cheatgrass cover were acquired from various agencies and research groups across the study area and reviewed for use in the mapping effort. A subset of 6650 field measurements were used to statistically evaluate relationships between cheatgrass and a suite of 50 biophysical and remotely sensed (NDVI) variables. Variables were examined for pairwise correlation and highly correlated variables were discarded from the analysis. Eighteen of the 50 variables were selected to construct a Generalized Linear Model to classify cheatgrass occurrence. A decision rule based on strength of class membership was used to classify the study area as containing either 0-2% or >2% cheatgrass cover....
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The 2015 CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season.
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The normals are baseline datasets describing average monthly and annual conditions over the most recent three full decades. The current PRISM normals cover the period 1981-2010.
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A raster dataset of the appropriate management levels of burros in BLM Herd Management Areas (HMAs) and USFS Wild Horse and Burro Territories (WHBT) within Reslience and Resistance classes within the GRSG management zones. This dataset was made by adding the Resilience and Resistance raster to a raster of horse AML levels.
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A raster dataset of the percent of sagebrush-dominated ecological systems within a 5km radius moving window. This dataset was made by reclassifying the Sagebrush Cover raster into values of only sagebrush-dominated ecological systems, and then running a moving window analysis on that raster.
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A raster dataset representing road density within the Western United States. This dataset was made combining the BLM GRSG Westwide Habitat Disturbance Threats of Surface Streets, Major Roads, and Highways. The density metric of the raster is kilometers of roads per square kilometer within a 5km radius multiplied by 10000. The purpose is to represent road density within the Western United States. It was created to be incorporated into a larger landscape scale geospatial data modeling effort, the Conservation and Restoration Strategy.


map background search result map search result map Western United States Fire Perimeters Since 1984 Western United States Road Density Raster Western United States Percent of Sagebrush-dominated Ecological Systems within a 5km Radius Raster Fire Risk Assessment for the Greater Sage-Grouse Raster Cheatgrass Across the Range of the Greater Sage-Grouse Precipitation (Mean: Annual) - 2070-2100 - RCP8.5 - Min Temperature (Mean: Annual) - 1980-2010 Precipitation (Proportion May - Oct) - 2070-2100 - RCP8.5 - Mean Precipitation (Mean: July - Sep) - 2070-2100 - RCP8.5 - Min Temperature (Mean: Apr - June) - 2070-2100 - RCP4.5 - Mean Temperature (Mean: Dec - Mar) - 2020-2050 - RCP4.5 - Max Temperature (Mean: Dec - Mar) - 2020-2050 - RCP8.5 - Max Burro AML Levels of BLM HMAs and USFS WHBTs within Resilience and Resistance Classes Raster USDA, National Agricultural Statistics Service, Cropland Data Layer Precipitation and Temperature Data: 30-Year Normals Burro AML Levels of BLM HMAs and USFS WHBTs within Resilience and Resistance Classes Raster Fire Risk Assessment for the Greater Sage-Grouse Raster Cheatgrass Across the Range of the Greater Sage-Grouse Western United States Road Density Raster Western United States Percent of Sagebrush-dominated Ecological Systems within a 5km Radius Raster Precipitation (Mean: Annual) - 2070-2100 - RCP8.5 - Min Temperature (Mean: Annual) - 1980-2010 Precipitation (Proportion May - Oct) - 2070-2100 - RCP8.5 - Mean Precipitation (Mean: July - Sep) - 2070-2100 - RCP8.5 - Min Temperature (Mean: Apr - June) - 2070-2100 - RCP4.5 - Mean Temperature (Mean: Dec - Mar) - 2020-2050 - RCP4.5 - Max Temperature (Mean: Dec - Mar) - 2020-2050 - RCP8.5 - Max Precipitation and Temperature Data: 30-Year Normals USDA, National Agricultural Statistics Service, Cropland Data Layer Western United States Fire Perimeters Since 1984