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Landsat Collection 1 Level-3 Burned Area Science Product

NOTE: Landsat Collection 1 Level-3 science products are no longer available to download from the USGS as of December 30, 2022.

Landsat Collection 2 remains available. Please use the links below to return to Landsat Collection 2 information. 

Return to Landsat Burned Area Products Overview

 

NOTE: Landsat Collection 1 Level-3 science products are no longer available to download from the USGS as of December 30, 2022. The information on this webpage is for reference only. 

 

Accurate and complete data on fire locations and burned areas are needed to quantify trends and patterns of fire occurrence, characterize drivers of fire occurrence, projections of future fire pattern behavior, and help with assessments of fire impacts on both natural and social systems.

Landsat Burned Area Example
Left: Landsat Surface Reflectance image (Landsat 7 bands 5,4,3) and Right: Derived Burned Area product for an area within Landsat CONUS ARD tile h006v010 acquired on July 7, 2003. 

Accurate and complete data on fire locations and burned areas (e.g. fire occurrence) are needed to quantify trends and patterns of fire occurrence, characterize drivers of fire occurrence, projections of future fire pattern behavior, and help with assessments of fire impacts on both natural and social systems.

The Landsat Collection 1 (C1) Burned Area (BA) product is designed to identify burned areas across all ecosystems (e.g. forests, shrublands, and grasslands) for Landsat 4-8 data.

Landsat C1 BA products contain two acquisition-based raster data products that represent burn classification and burn probability. Landsat Burned Area is generated from Landsat Collection 1 U.S. Analysis Ready Data (ARD) Surface Reflectance and Top of Atmosphere Brightness Temperature data.

Landsat C1 BA products are processed to 30-meter spatial resolution in Albers Equal Area (AEA) projection using the World Geodetic System 1984 (WGS84) datum and gridded to a common tiling scheme.

Product Availability

Landsat C1 BA products are available for the conterminous U.S for the following date ranges:

  • Landsat 8 OLI: April 2013 to December 31, 2021*
  • Landsat 7 ETM+: July 1999 to December 31, 2021*
  • Landsat 5 TM: March 1984 to May 2012
  • Landsat 4 TM: March 1984 to July 1993

*As of January 1, 2022, newly-acquired Landsat data are processed into Landsat Collection 2 only. 

Package Content

C1 BA products include two acquisition-based raster data products that represent burn classification and burn probability.  Additional product specifications can be found in the Landsat Collection 1 Burned Area Product Guide. The C1 BA package includes a metadata file in Extensible Markup Language (.xml) format.

The list below describes the products and filenames that are delivered with the Landsat C1 BA package. 

Burn Probability (BP): Provides the maximum per-pixel BP; generated by comparing the current individual acquisition against composites created from seasonal average and the previous year of acquisition.

Delivered file name: *_BP.tif

Approximate file size: 8.3 MB

Burned Classification (BC): Indicates if an area was burned by applying a threshold to the BP product.

Delivered file name: *_BC.tif

Approximate file size: 200 KB

 

Caveats and Constraints

  • Only images with a RMSE less than 10 m and cloud cover less than 80 percent are processed to a BA product.
  • A Quality Assessment process is applied to the BA products prior to public release, which includes visually assessing each scene-level BA product for excessive commission errors caused by factors such as incorrect cloud masks or poor georeferencing. Therefore, while the majority of Landsat scenes were used to generate Burned Area products, certain scenes may not be able to be processed to produce a scientifically viable Burned Area product.
  • Due to a bug in the Collection 1 BA code, pixels in the top row (northern edge) and left column (western edge) of the Landsat C1 ARD tile may be incorrectly classified as not-burned in the BC layer, while the BP layer indicates a burn probability greater than 71% and the burn region is larger than the threshold seed size. Users can still refer to the BP layer to obtain the correct burn probability. This issue has been fixed in Collection 2 BA products.
  • Occasionally some burned areas are incorrectly classified as being water in the BA  product. This occurs if the input ARD Pixel QA (PIXELQA) band includes pixels that are flagged as “water, terrain, low-confidence cloud”.
  • The product metadata file (.xml) lists the band information for both the burn classification and burn probability.  The units for the pixel size is “m” and should be “meters” to be compliant with the schema.

 

Documentation

Landsat Collection 1 Burned Area Product Guide

Landsat Collection 1 Burned Area Algorithm Description Document (ADD)

Landsat Collection 1 Burned Area Digital Object Identifier (DOI): doi.org/10.5066/F77W6BDJ

 

Citation Information

There are no restrictions on the use of Landsat Level-3 Science Products. It is not a requirement of data use, but the following citations may be used in publication or presentation materials to acknowledge the USGS as a data source and to credit the original research.

Landsat Collection 1 Level 3 Burned Area  Science Product courtesy of the U.S. Geological Survey.

Hawbaker, T.J., Vanderhoof, M.K., Schmidt, G.L., Beal, Y.-J., Picotte, J.J., Takacs, J.D., Falgout, J.T., Dwyer, J.L., 2020. The Landsat Burned Area algorithm and products for the United States. Remote Sensing of the Environment 244. https://doi.org/10.1016/j.rse.2020.111801

Hawbaker, T.J., Vanderhoof, M.K., Beal, Y.-J., Takacs, J.D., Schmidt, G.L., Falgout, J.T., Williams, B., Brunner, N.M., Caldwell, M.K., Picotte, J.J., Howard, S.M., Stitt, S., Dwyer, J.L., 2017a. Landsat Burned Area Essential Climate Variable products for the conterminous United States (1984 -2015). U.S. Geological Survey Data Release. https://doi.org/10.5066/F73B5X76

Hawbaker, T.J., Vanderhoof, M.K., Beal, Y.-J., Takacs, J.D., Schmidt, G.L., Falgout, J.T., Williams, B., Fairaux, N.M., Caldwell, M.K., Picotte, J.J., Howard, S.M., Stitt, S., Dwyer, J.L., 2017b. Mapping burned areas using dense time-series of Landsat data. Remote Sensing of Environment 198, 504–522. https://doi.org/10.1016/j.rse.2017.06.027

 

References

Hawbaker, T.J., Vanderhoof, M.K., Schmidt, G.L., Beal, Y.-J., Picotte, J.J., Takacs, J.D., Falgout, J.T., Dwyer, J.L., 2020. The Landsat Burned Area algorithm and products for the United States. Remote Sensing of the Environment 244. https://doi.org/10.1016/j.rse.2020.111801

Hawbaker, T.J., Vanderhoof, M.K., Beal, Y.-J., Takacs, J.D., Schmidt, G.L., Falgout, J.T., Williams, B., Brunner, N.M., Caldwell, M.K., Picotte, J.J., Howard, S.M., Stitt, S., Dwyer, J.L., 2017a. Landsat Burned Area Essential Climate Variable products for the conterminous United States (1984 -2015). U.S. Geological Survey Data Release. https://doi.org/10.5066/F73B5X76

Hawbaker, T.J., Vanderhoof, M.K., Beal, Y.-J., Takacs, J.D., Schmidt, G.L., Falgout, J.T., Williams, B., Fairaux, N.M., Caldwell, M.K., Picotte, J.J., Howard, S.M., Stitt, S., Dwyer, J.L., 2017b. Mapping burned areas using dense time-series of Landsat data. Remote Sensing of Environment 198, 504–522. https://doi.org/10.1016/j.rse.2017.06.027

Vanderhoof, K.M., Brunner, N., Beal, G.Y.-J., Hawbaker, J.T., 2017. Evaluation of the U.S. Geological Survey Landsat Burned Area Essential Climate Variable across the Conterminous U.S. Using Commercial High-Resolution Imagery. Remote Sensing 9. https://doi.org/10.3390/rs9070743

Vanderhoof, M.K., Fairaux, N., Beal, Y.-J.G., Hawbaker, T.J., 2017a. Validation of the USGS Landsat Burned Area Essential Climate Variable (BAECV) across the conterminous United States. Remote Sensing of Environment 198, 393–406. https://doi.org/10.1016/j.rse.2017.06.025

Vanderhoof, M.K., Fairaux, N.M., Beal, Y.-J., Hawbaker, T.J., 2017b. Data Release for the Validation of the USGS Landsat Burned Area Essential Climate Variable (BAECV) across the conterminous U.S. U.S. Geological Survey Data Release. https://doi.org/10.5066/F7T151VX