The Monitoring Trends in Burn Severity MTBS project assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period of 1984 through 2018. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a vector point of the location of all currently inventoried and mappable fires occurring between calendar year 1984 and 2018 for the continental United States, Alaska, Hawaii and Puerto Rico. The point location represents the geographic centroid for the _BURN_AREA_BOUNDARY polygon(s) associated with each fire. Map Service Feature Layer

The Monitoring Trends in Burn Severity MTBS project assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico from the beginning of the Landsat Thematic Mapper archive to the present. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a vector point of the location of all currently inventoried and mappable fires occurring between calendar year 1984 and the current MTBS release for CONUS, Alaska, Hawaii and Puerto Rico. Please visit https://mtbs.gov/announcements to determine the current release. Fires omitted from this mapped inventory are those where suitable satellite imagery was not available or fires were not discernable from available imagery. The point location represents the geographic centroid for the _BURN_AREA_BOUNDARY polygon(s) associated with each fire. Metadata

Monitoring Trends in Burn Severity of individual fires; Landsat remote sensing of land cover; Landscape Change Monitoring System maps of annual forest cover. This dataset is associated with the following publication: Zuspan, E.A., M. Reilly, and E. Lee. Long-Term Patterns of Post-Fire Harvest Diverge Among Ownerships in the Pacific West, U.S.A.. Environmental Research Letters. IOP Publishing LIMITED, Bristol, UK, 19(12): 124075, (2024).

Burn severity layers are thematic images depicting severity as unburned to low, low, moderate, high, and increased greenness (increased post-fire vegetation response). The layer may also have a sixth class representing a mask for clouds, shadows, large water bodies, or other features on the landscape that erroneously affect the severity classification. This data has been prepared as part of the Monitoring Trends in Burn Severity (MTBS) project. Due to the lack of comprehensive fire reporting information and quality Landsat imagery, burn severity for all targeted MTBS fires are not available. Additionally, the availability of burn severity data for fires occurring in the current and previous calendar year is variable since these data are currently in production and released on an intermittent basis by the MTBS project.

The LANDFIRE Percent Mixed-Severity Fire (PMS) raster dataset (LF US_120_PMS) was combined with the Monitoring Trends in Burn Severity (MTBS) data (1984-2017) to identify areas that have experienced unnaturally severe wildfires in the recent past (1984-2017). Areas mapped are greater than 50% Mixed-Severity Fire and a high severity fire MTBS mapped fire at the same location.

Burn severity layers are thematic images depicting severity as unburned to low, low, moderate, high, and increased greenness (increased post-fire vegetation response). The layer may also have a sixth class representing a mask for clouds, shadows, large water bodies, or other features on the landscape that erroneously affect the severity classification. This data has been prepared as part of the Monitoring Trends in Burn Severity (MTBS) project. Due to the lack of comprehensive fire reporting information and quality Landsat imagery, burn severity for all targeted MTBS fires are not available. Additionally, the availability of burn severity data for fires occurring in the current and previous calendar year is variable since these data are currently in production and released on an intermittent basis by the MTBS project.�Map Services

Wildland fire event polygons for 2004-2017 reconciled in SmartFire 2 for the EPA Air Quality Times Series (EQUATES) modeling project (https://doi.org/10.1016/j.dib.2023.109022). These event polygons represent a combination of properties from a collection of remotely sensed and ground-based fire activity datasets. The primary underlying fire activity datasets for the fire event polygons are the Hazard Mapping System (HMS) remote sense fire product (https://www.ospo.noaa.gov/Products/land/hms.html), SIT-ICS/209 Incident Reports (https://www.wildfire.gov/application/sit209), GeoMAC Fire Event polygons (https://data-nifc.opendata.arcgis.com/datasets/nifc::historic-perimeters-combined-2000-2018-geomac/about), and the Monitoring Trends in Burn Severity (MTBS) burn scar event perimeters (https://www.mtbs.gov/direct-download). This dataset includes events identified as over wildland and does not contain biomass burning events over agricultural areas, such as crop residue field burns. Additionally, certain grass fires, such as the annual prescribed fires in the Flint Hills region, have been removed for inclusion in a separate processing stream. Some minor updates have been made to the dataset since the publishing of the EQUATES emission inventories including removal of known errors related to issues in the underlying activity. This dataset is associated with the following publication: Beidler, J., G. Pouliot, and K. Foley. 2004-2017 Geospatial Dataset of Wild and Prescribed Fire Activity Over the Conterminous United States. Data in Brief. Elsevier B.V., Amsterdam, NETHERLANDS, 56: 110856, (2024).

Fire severity is a metric of the loss of biomass caused by fire. In collaboration with the NSW Rural Fire Service, DPE Remote Sensing & Regulatory Mapping team has developed a semi-automated approach to mapping fire extent and severity through a machine learning framework based on sentinel 2 and Landsat satellite imagery. Fire Extent and Severity Mapping for the 2016/17 fire year is based on Landsat 8 imagery. Fire Extent and Severity Mapping from the 2017/18 fire year onward is based on Sentinel 2 imagery. The statewide severity map has standardised classes to allow comparison of different fires across the landscape. The FESM severity classes include: unburnt, low severity (burnt understory, unburnt canopy), moderate severity (partial canopy scorch), high severity (complete canopy scorch, partial canopy consumption), extreme (full canopy consumption). This dataset represents the 2016/17 fire year, including wildfires >100ha with fire start date between July 2016 and June 2017.

Fire severity is a metric of the loss of biomass caused by fire. In collaboration with the NSW Rural Fire Service, DPE Remote Sensing & Regulatory Mapping team has developed a semi-automated approach to mapping fire extent and severity through a machine learning framework based on sentinel 2 satellite imagery. The statewide severity map has standardised classes to allow comparison of different fires across the landscape. The FESM severity classes include: unburnt, low severity (burnt understory, unburnt canopy), moderate severity (partial canopy scorch), high severity (complete canopy scorch, partial canopy consumption), extreme (full canopy consumption). This dataset represents the 2019/20 fire year including all wildfires >10ha with a fire start date between July 2019 and June 2020.

Fire severity is a metric of the loss of biomass caused by fire. In collaboration with the NSW Rural Fire Service, DPE Remote Sensing & Regulatory Mapping team has developed a semi-automated approach to mapping fire extent and severity through a machine learning framework based on sentinel 2 satellite imagery. The statewide severity map has standardised classes to allow comparison of different fires across the landscape. The FESM severity classes include: unburnt, low severity (burnt understory, unburnt canopy), moderate severity (partial canopy scorch), high severity (complete canopy scorch, partial canopy consumption), extreme (full canopy consumption). This dataset represents the 2021/22 fire year including all wildfires >10ha with a fire start date between July 2021 and June 2022.