The U.S. Geological Survey (USGS) has developed and implemented an automated algorithm that identifies burned areas in temporally-dense time series of Landsat image stacks to produce the Landsat Burned Area Essential Climate Variable (BAECV) products. The algorithm makes use of predictors derived from individual Landsat scenes, lagged reference conditions, and change metrics between the scene and reference predictors. Outputs of the BAECV algorithm consist of burn probabilities for each Landsat scene, and annual composites of: burn probability, and burn classification. These products were generated for the conterminous United States for 1984 through 2015. These data are also available for download at https://rmgsc.cr.usgs.gov/outgoing/baecv/BAECV_CONUS_v1_2017/
Citation Information
| Publication Year | 2018 |
|---|---|
| Title | Landsat Burned Area Essential Climate Variable products for the conterminous United States (1984 -2015) |
| DOI | 10.5066/F73B5X76 |
| Authors | Todd J. Hawbaker, Melanie K. Vanderhoof, Yen-Ju G. Beal, Joshua Takacs, Gail L. Schmidt, Jeff T. Falgout, Brad Williams, Nicole M. Brunner, Megan K. Caldwell, Joshua J. Picotte, Stephen M. Howard, Susan Stitt, John L. Dwyer |
| Product Type | Data Release |
| Record Source | USGS Digital Object Identifier Catalog |
| USGS Organization | Geosciences and Environmental Change Science Center |
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