Building locations identified before and after the Camp, Tubbs, and Woolsey wildfires
Wildland-urban interface (WUI) maps identify areas with wildfire risk, but they are often outdated due to the lack of building data. Convolutional neural networks (CNNs) can extract building locations from remote sensing data, but their accuracy in WUI areas is unknown. Additionally, CNNs are computationally intensive and technically complex making it challenging for end-users, such as those who use or create WUI maps, to apply. We identified buildings pre- and post-wildfire and estimated building destruction for three California wildfires: Camp, Tubbs, and Woolsey. We used a CNN model from Esri to detect buildings from high-resolution imagery. This dataset represents the state-of-the-art of what is readily available for potential WUI mapping.
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Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[ "010:12" ] |
| contactPoint |
{ "fn": "Todd J Hawbaker", "@type": "vcard:Contact", "hasEmail": "mailto:tjhawbaker@usgs.gov" } |
| description | Wildland-urban interface (WUI) maps identify areas with wildfire risk, but they are often outdated due to the lack of building data. Convolutional neural networks (CNNs) can extract building locations from remote sensing data, but their accuracy in WUI areas is unknown. Additionally, CNNs are computationally intensive and technically complex making it challenging for end-users, such as those who use or create WUI maps, to apply. We identified buildings pre- and post-wildfire and estimated building destruction for three California wildfires: Camp, Tubbs, and Woolsey. We used a CNN model from Esri to detect buildings from high-resolution imagery. This dataset represents the state-of-the-art of what is readily available for potential WUI mapping. |
| distribution |
[ { "@type": "dcat:Distribution", "title": "Digital Data", "format": "XML", "accessURL": "https://doi.org/10.5066/P9VWV2IO", "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.63b5c2d2d34e92aad3caa32b.xml" } ] |
| identifier | http://datainventory.doi.gov/id/dataset/USGS_63b5c2d2d34e92aad3caa32b |
| keyword |
[ "Building footprint", "Convolutional neural network", "USGS:63b5c2d2d34e92aad3caa32b", "Wildland fire", "Wildland-urban interface", "biota" ] |
| modified | 2023-01-06T00:00:00Z |
| publisher |
{ "name": "U.S. Geological Survey", "@type": "org:Organization" } |
| spatial | -122.7733, 34.0005, -118.3181, 39.8775 |
| theme |
[ "geospatial" ] |
| title | Building locations identified before and after the Camp, Tubbs, and Woolsey wildfires |
