This dataset is intended to assist department staff in post-fire analysis efforts.

This dataset is intended to assist department staff in post-fire analysis efforts.

The U. S. Fish and Wildlife Service (FWS) requests burn severity assessments through an agreement with the U.S. Geological Survey (USGS) to be completed by analysts with the Monitoring Trends in Burn Severity (MTBS) Program. These data products are burned area boundary shapefiles derived from post-fire sensor data (including Landsat TM, Landsat ETM+, Landsat OLI). The pre-fire and post-fire subsets included were used to create Normalized Burn Ratio (NBR) and then a differenced Normalized Burn Ratio (dNBR) image. The objective of this assessment was to generate burned area boundaries for each fire. Data bundles also include post fire subset, pre-fire subset, NBR, and dNBR images. This map layer is a vector Fire Occurrence dataset which contains point locations of all currently inventoried fires occurring between calendar year 1983 and 2014. Fires omitted from this mapped inventory are those where suitable satellite imagery was not available, or fires which were not discernable from available imagery.

The U. S. Fish and Wildlife Service (FWS) requests burn severity assessments through an agreement with the U.S. Geological Survey (USGS) to be completed by analysts with the Monitoring Trends in Burn Severity (MTBS) Program. These data products are burned area boundary shapefiles derived from post-fire sensor data (including Landsat TM, Landsat ETM+, Landsat OLI). The pre-fire and post-fire subsets included were used to create Normalized Burn Ratio (NBR) and then a differenced Normalized Burn Ratio (dNBR) image. The objective of this assessment was to generate burned area boundaries for each fire. Data bundles also include post fire subset, pre-fire subset, NBR, and dNBR images. This map layer is a vector Fire Occurrence dataset which contains point locations of all currently inventoried fires occurring between calendar year 1983 and 2014. Fires omitted from this mapped inventory are those where suitable satellite imagery was not available, or fires which were not discernable from available imagery.

The U. S. Fish and Wildlife Service (FWS) requests burn severity assessments through an agreement with the U.S. Geological Survey (USGS) to be completed by analysts with the Monitoring Trends in Burn Severity (MTBS) Program. These data products are burned area boundary shapefiles derived from post-fire sensor data (including Landsat TM, Landsat ETM+, Landsat OLI). The pre-fire and post-fire subsets included were used to create Normalized Burn Ratio (NBR) and then a differenced Normalized Burn Ratio (dNBR) image. The objective of this assessment was to generate burned area boundaries for each fire. Data bundles also include post fire subset, pre-fire subset, NBR, and dNBR images. This map layer is a vector Fire Occurrence dataset which contains point locations of all currently inventoried fires occurring between calendar year 1983 and 2014. Fires omitted from this mapped inventory are those where suitable satellite imagery was not available, or fires which were not discernable from available imagery.

The U. S. Fish and Wildlife Service (FWS) requests burn severity assessments through an agreement with the U.S. Geological Survey (USGS) to be completed by analysts with the Monitoring Trends in Burn Severity (MTBS) Program. These data products are burned area boundary shapefiles derived from post-fire sensor data (including Landsat TM, Landsat ETM+, Landsat OLI). The pre-fire and post-fire subsets included were used to create Normalized Burn Ratio (NBR) and then a differenced Normalized Burn Ratio (dNBR) image. The objective of this assessment was to generate burned area boundaries for each fire. Data bundles also include post-fire subset, pre-fire subset, NBR, and dNBR images. This map layer contains burned areas boundaries of the location of all currently inventoried fires occurring between calendar year 1983 and 2014. Fires omitted from this mapped inventory are those where suitable satellite imagery was not available, or fires which were not discernable from available imagery.

The U. S. Fish and Wildlife Service (FWS) requests burn severity assessments through an agreement with the U.S. Geological Survey (USGS) to be completed by analysts with the Monitoring Trends in Burn Severity (MTBS) Program. These data products are burned area boundary shapefiles derived from post-fire sensor data (including Landsat TM, Landsat ETM+, Landsat OLI). The pre-fire and post-fire subsets included were used to create Normalized Burn Ratio (NBR) and then a differenced Normalized Burn Ratio (dNBR) image. The objective of this assessment was to generate burned area boundaries for each fire. Data bundles also include post-fire subset, pre-fire subset, NBR, and dNBR images. This map layer contains burned areas boundaries of the location of all currently inventoried fires occurring between calendar year 1983 and 2014. Fires omitted from this mapped inventory are those where suitable satellite imagery was not available, or fires which were not discernable from available imagery.

The U. S. Fish and Wildlife Service (FWS) requests burn severity assessments through an agreement with the U.S. Geological Survey (USGS) to be completed by analysts with the Monitoring Trends in Burn Severity (MTBS) Program. These data products are burned area boundary shapefiles derived from post-fire sensor data (including Landsat TM, Landsat ETM+, Landsat OLI). The pre-fire and post-fire subsets included were used to create Normalized Burn Ratio (NBR) and then a differenced Normalized Burn Ratio (dNBR) image. The objective of this assessment was to generate burned area boundaries for each fire. Data bundles also include post-fire subset, pre-fire subset, NBR, and dNBR images. This map layer contains burned areas boundaries of the location of all currently inventoried fires occurring between calendar year 1983 and 2014. Fires omitted from this mapped inventory are those where suitable satellite imagery was not available, or fires which were not discernable from available imagery.

The increase in wildfires, particularly in the western U.S., represents one of the greatest threats to multiple native ecosystems. Despite this threat, there is currently no central repository to store both past and current wildfire perimeter data. Currently, wildfire boundaries can only be found in disparate local or national datasets. These datasets are generally restricted to specific locations, fire sizes, or time periods. Our objective was to create a comprehensive national wildfire perimeter dataset by combining all freely available wildfire datasets that we could download. We combined and dissolved individual wildfire polygons from multiple datasets if they were in the same year and overlapped each other or were within 1km of the fire boundary. This combined dataset includes spatial summary statistics such as number of times burned, earliest fire of record, and most recent fire of record.

Post-fire vegetation status and condition have multiple implications. They are indicative of burn severity and the lasting impacts of fire the land; they also help inform post-fire debris flow modeling and related risk analyses, hydrology and water quality assessments, and vulnerability to invasive species. Monitoring vegetation recovery over time enables continuous re-evaluation of various post-fire hazards, thereby facilitating informed and timely responses to post-fire risks by land managers at the local level. Structure metrics were derived from spaceborne Global Ecosystem Dynamics Investigation (GEDI) lidar data and used to map pre- and post-fire structure. Pre- and post-fire Landsat or Sentinel satellite data were obtained from the Monitoring Trends in Burn Severity (MTBS; https://www.mtbs.gov/) program. GEDI data were intersected with each satellite band and XGBoost models were built using band values as independent variables and GEDI vegetation structure values as dependent values. The models were used to generate spatially continuous maps of structure, providing vegetation structural estimates throughout the fire perimeter and beyond.