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These data products are preliminary burn severity assessments derived from data obtained from suitable imagery (including Landsat TM, Landsat ETM+, Landsat OLI, Sentinel 2A, and Sentinel 2B). The pre-fire and post-fire subsets included were used to create a differenced Normalized Burn Ratio (dNBR) image. The dNBR image attempts to portray the variation of burn severity within a fire. The severity ratings are influenced by the effects to the canopy. The severity rating is based upon a composite of the severity to the understory (grass, shrub layers), midstory trees and overstory trees. Because there is often a strong correlation between canopy consumption and soil effects, this algorithm works in many cases for Burned...
The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. 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 thematic raster image...
The Rapid Assessment of Vegetation Condition after Wildfire (RAVG) program provides assessments of vegetation conditions following large fires on forested lands. Fire effects are represented by three metrics: percent change in live basal area (BA), percent change in canopy cover (CC), and the standardized Composite Burn Index (CBI). These data are derived from moderate resolution multi-spectral imagery (e.g., Landsat 8 Operational Land Imager or Sentinel-2 Multispectral Instrument). The Relative Differenced Normalized Burn Ratio (RdNBR), which is correlated to the variation of burn severity within a fire, is calculated from a pair of images (pre- and postfire), judiciously selected to capture fire effects. The three-severity...
The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (including wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period of 1984 and beyond. 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...
These data products are preliminary burn severity assessments derived from data obtained from suitable imagery (including Landsat TM, Landsat ETM+, Landsat OLI, Sentinel 2A, and Sentinel 2B). The pre-fire and post-fire subsets included were used to create a differenced Normalized Burn Ratio (dNBR) image. The dNBR image attempts to portray the variation of burn severity within a fire. The severity ratings are influenced by the effects to the canopy. The severity rating is based upon a composite of the severity to the understory (grass, shrub layers), midstory trees and overstory trees. Because there is often a strong correlation between canopy consumption and soil effects, this algorithm works in many cases for Burned...
The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. 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 thematic raster image...
Categories: Data Release - Revised;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: AK,
Alaska,
Burn severity,
Burned area,
CONUS,
The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. 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 thematic raster image...
The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (including wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period of 1984 and beyond. 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...
These data products are preliminary burn severity assessments derived from post sensor data (including Landsat TM, Landsat ETM+, Landsat OLI, Sentinel 2A, and Sentinel 2B). The pre-fire and post-fire subsets included were used to create a differenced Normalized Burn Ratio (dNBR) image. The dNBR image attempts to portray the variation of burn severity within a fire. The severity ratings are influenced by the effects to the canopy. The severity rating is based upon a composite of the severity to the understory (grass, shrub layers), midstory trees and overstory trees. Because there is often a strong correlation between canopy consumption and soil effects, this algorithm works in many cases for Burned Area Emergency...
These data products are preliminary burn severity assessments derived from data obtained from suitable imagery (including Landsat TM, Landsat ETM+, Landsat OLI, Sentinel 2A, and Sentinel 2B). The pre-fire and post-fire subsets included were used to create a differenced Normalized Burn Ratio (dNBR) image. The dNBR image attempts to portray the variation of burn severity within a fire. The severity ratings are influenced by the effects to the canopy. The severity rating is based upon a composite of the severity to the understory (grass, shrub layers), midstory trees and overstory trees. Because there is often a strong correlation between canopy consumption and soil effects, this algorithm works in many cases for Burned...
The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (including wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period of 1984 and beyond. 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 includes...
These data products are preliminary burn severity assessments derived from data obtained from suitable imagery (including Landsat TM, Landsat ETM+, Landsat OLI, Sentinel 2A, and Sentinel 2B). The pre-fire and post-fire subsets included were used to create a differenced Normalized Burn Ratio (dNBR) image. The dNBR image attempts to portray the variation of burn severity within a fire. The severity ratings are influenced by the effects to the canopy. The severity rating is based upon a composite of the severity to the understory (grass, shrub layers), midstory trees and overstory trees. Because there is often a strong correlation between canopy consumption and soil effects, this algorithm works in many cases for Burned...
The various post-fire data products available on the Burn Severity Portal are produced using satellite imagery. The timing of the satellite imagery used, relative to the fire event, typically depends on the vegetation type and structure where the fire occurred. Each mapping program produces a suite of data products based on user intended user needs. You can find additional details in each of the available areas. First posted - September 6, 2022 Revised - January 6, 2023 (version 2.0) Revised - March 31, 2023 (version 3.0) Revised - August 8, 2023 (version 4.0) Revised - October 26, 2023 (version 5.0) Revised - January 26, 2024 (version 6.0) Revised - April 29, 2024 (version 7.0)
These data products are preliminary burn severity assessments derived from data obtained from suitable imagery (including Landsat TM, Landsat ETM+, Landsat OLI, Sentinel 2A, and Sentinel 2B). The pre-fire and post-fire subsets included were used to create a differenced Normalized Burn Ratio (dNBR) image. The dNBR image attempts to portray the variation of burn severity within a fire. The severity ratings are influenced by the effects to the canopy. The severity rating is based upon a composite of the severity to the understory (grass, shrub layers), midstory trees and overstory trees. Because there is often a strong correlation between canopy consumption and soil effects, this algorithm works in many cases for Burned...
These data products are preliminary burn severity assessments derived from post sensor data (including Landsat TM, Landsat ETM+, Landsat OLI, Sentinel 2A, and Sentinel 2B). The pre-fire and post-fire subsets included were used to create a differenced Normalized Burn Ratio (dNBR) image. The dNBR image attempts to portray the variation of burn severity within a fire. The severity ratings are influenced by the effects to the canopy. The severity rating is based upon a composite of the severity to the understory (grass, shrub layers), midstory trees and overstory trees. Because there is often a strong correlation between canopy consumption and soil effects, this algorithm works in many cases for Burned Area Emergency...
The Rapid Assessment of Vegetation Condition after Wildfire (RAVG) program provides assessments of vegetation conditions following large fires on forested lands. Fire effects are represented by three metrics: percent change in live basal area (BA), percent change in canopy cover (CC), and the standardized Composite Burn Index (CBI). These data are derived from moderate resolution multi-spectral imagery (e.g., Landsat 8 Operational Land Imager or Sentinel-2 Multispectral Instrument). The Relative Differenced Normalized Burn Ratio (RdNBR), which is correlated to the variation of burn severity within a fire, is calculated from a pair of images (pre- and postfire), judiciously selected to capture fire effects. The three-severity...
These data products are preliminary burn severity assessments derived from data obtained from suitable imagery (including Landsat TM, Landsat ETM+, Landsat OLI, Sentinel 2A, and Sentinel 2B). The pre-fire and post-fire subsets included were used to create a differenced Normalized Burn Ratio (dNBR) image. The dNBR image attempts to portray the variation of burn severity within a fire. The severity ratings are influenced by the effects to the canopy. The severity rating is based upon a composite of the severity to the understory (grass, shrub layers), midstory trees and overstory trees. Because there is often a strong correlation between canopy consumption and soil effects, this algorithm works in many cases for Burned...
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