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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...
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 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 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 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 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 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...
Burned Area Reflectance Classification Thematic Burn Severity Mosaic for 2024 (ver. 7.0, April 2024)
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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