Sagebrush Distribution within the Biome Range Extent, as Derived from Classified Landsat Imagery
This raster portrays the distribution of sagebrush within the geographic extent of the sagebrush biome in the United States. It was created for the Western Association of Fish and Wildlife Agency’s (WAFWA) Sagebrush Conservation Strategy publication as a visual for the schematic figures and to calculate summary statistics. This distribution incorporates the most recently available sagebrush cover mapping (Xian et al. 2015, Rigge et al. 2019) and classified LANDFIRE EVT (Department of Ecosystem Science, University of Wyoming 2016). Both datasets were rigorously evaluated and extensive ground measurements taken to evaluate accuracy by the respective authors. We created a combined binary sagebrush distribution by classifying the Rigge et al. (2019) product to a binary form where sagebrush cover was greater than 5%, which is equal to the root mean squared error of the analysis (RMSE = 5.09). The Rigge et al. (2019) raster is not complete across the sagebrush biome, so we filled in the areas of NoData with the 'Sagebrush-dominated Ecological Systems' pixels from binary sagebrush raster (Department of Ecosystem Science, University of Wyoming 2016) to create a continuous raster across the sagebrush biome. The input layers are informative to conditions circa the beginning of 2015.
Complete Metadata
| accessLevel | public |
|---|---|
| bureauCode |
[
"010:12"
]
|
| contactPoint |
{
"fn": "FRESC Science Data Coordinator",
"@type": "vcard:Contact",
"hasEmail": "mailto:fresc_outreach@usgs.gov"
}
|
| description | This raster portrays the distribution of sagebrush within the geographic extent of the sagebrush biome in the United States. It was created for the Western Association of Fish and Wildlife Agency’s (WAFWA) Sagebrush Conservation Strategy publication as a visual for the schematic figures and to calculate summary statistics. This distribution incorporates the most recently available sagebrush cover mapping (Xian et al. 2015, Rigge et al. 2019) and classified LANDFIRE EVT (Department of Ecosystem Science, University of Wyoming 2016). Both datasets were rigorously evaluated and extensive ground measurements taken to evaluate accuracy by the respective authors. We created a combined binary sagebrush distribution by classifying the Rigge et al. (2019) product to a binary form where sagebrush cover was greater than 5%, which is equal to the root mean squared error of the analysis (RMSE = 5.09). The Rigge et al. (2019) raster is not complete across the sagebrush biome, so we filled in the areas of NoData with the 'Sagebrush-dominated Ecological Systems' pixels from binary sagebrush raster (Department of Ecosystem Science, University of Wyoming 2016) to create a continuous raster across the sagebrush biome. The input layers are informative to conditions circa the beginning of 2015. |
| distribution |
[
{
"@type": "dcat:Distribution",
"title": "Digital Data",
"format": "XML",
"accessURL": "https://doi.org/10.5066/P9QSQPUU",
"mediaType": "application/http",
"description": "Landing page for access to the data"
},
{
"@type": "dcat:Distribution",
"title": "Original Metadata",
"format": "XML",
"mediaType": "text/xml",
"description": "The metadata original format",
"downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.5d1cfecae4b0941bde64ce9f.xml"
}
]
|
| identifier | http://datainventory.doi.gov/id/dataset/USGS_5d1cfecae4b0941bde64ce9f |
| keyword |
[
"Arizona",
"California",
"Colorado",
"Great Basin",
"Idaho",
"Montana",
"Nevada",
"New Mexico",
"North America",
"North Dakota",
"Oregon",
"South Dakota",
"USGS:5d1cfecae4b0941bde64ce9f",
"United States",
"Utah",
"Washington",
"Western United States",
"Wyoming",
"biogeography",
"biota",
"sage",
"sagebrush"
]
|
| modified | 2020-08-19T00:00:00Z |
| publisher |
{
"name": "U.S. Geological Survey",
"@type": "org:Organization"
}
|
| spatial | -124.7875, 32.5295, -101.2154, 50.8434 |
| theme |
[
"Geospatial"
]
|
| title | Sagebrush Distribution within the Biome Range Extent, as Derived from Classified Landsat Imagery |
