Modelled long-term wildfire occurrence probabilities in sagebrush-dominated ecosystems in the western US (1985 to 2019)
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.
Complete Metadata
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"fn": "Neal J Pastick",
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|
| description | 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. |
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| identifier | http://datainventory.doi.gov/id/dataset/USGS_6023017dd34e31ed20c87329 |
| keyword |
[
"Exotic annual grasses, cheatgrass, remote sensing, wildfire",
"USGS:6023017dd34e31ed20c87329",
"biota"
]
|
| modified | 2022-04-21T00:00:00Z |
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{
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| spatial | -121.87704, 36.90701, -104.87570, 47.84742 |
| theme |
[
"Geospatial"
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|
| title | Modelled long-term wildfire occurrence probabilities in sagebrush-dominated ecosystems in the western US (1985 to 2019) |
