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Three views of a burned area: a satellite image, a burn classification map and a burn probability map

The Bootleg fire in Oregon on July 11, 2021: left, a Landsat 8 surface reflectance image (bands 6, 5 and 4); center, burn classification; right, burn probability. USGS images.

Why it's needed

Accurate, complete data on where fires burned are needed to track trends and patterns of fire, understand what drives it, project how fire will behave in the future, and assess its effects on natural and social systems.

The Landsat Collection 2 Level-3 Burned Area (BA) science product is designed to identify burned areas across all ecosystems — forests, shrublands and grasslands among them — in Landsat 4–9 data.

How it works

  • Inputs: it is generated from Landsat Collection 2 U.S. Analysis Ready Data surface reflectance and top-of-atmosphere brightness temperature data.
  • Burn probability: the maximum per-pixel probability of burning, found by comparing each new acquisition with composites made from the seasonal average and the previous year.
  • Burn classification: whether an area burned, found by applying a threshold to the burn probability.
  • Grid: 30-meter pixels in the Albers Equal-Area Conic projection on the WGS 84 datum, on fixed, non-overlapping tiles.

Map of the conterminous United States covered by a grid of tiles numbered horizontally and vertically

The Burned Area product's tiles over the conterminous United States, on a horizontal (h) and vertical (v) grid. USGS map.

Coverage

The conterminous United States:

SensorDates
Landsat 9 Operational Land ImagerOctober 2021 to present
Landsat 8 Operational Land ImagerApril 2013 to present
Landsat 7 Enhanced Thematic Mapper PlusJuly 1999 to April 2022
Landsat 5 Thematic MapperMarch 1984 to May 2012
Landsat 4 Thematic MapperMarch 1984 to September 1992

What changed in Collection 2

No major changes, but some updates:

  • A browse file was added.
  • A bug was fixed: in Collection 1, pixels in the top row (the northern edge) and left column (the western edge) of each tile were wrongly classed as unburned.
  • Diagonal growth: data can now grow diagonally, not only up, down and sideways.
  • Retraining: the model was retrained after an upgrade to Python 3, which caused minor differences in the output.

The files

FileContents
tileID_BP.TIFburn probability raster
tileID_BC.TIFburn classification raster
tileID.pngbrowse image: a false-color composite (shortwave infrared 2 / near infrared / green) with the probability and classification plots, for a quick visual check
tileID_BA.XMLmetadata (also provided as JSON)

Getting and citing it

Download from EarthExplorer — under Landsat › Landsat Collection 2 Level-3 Science Products or Landsat C2 U.S. Analysis Ready Data (ARD), listed as "Landsat 4-9 C2 Burned Area" — or through the commercial cloud.

The suggested credit is "Landsat Collection 2 Level-3 Burned Area Science Product courtesy of the U.S. Geological Survey," along with Hawbaker and others (2020), "The Landsat Burned Area algorithm and products for the United States," Remote Sensing of Environment 244: 111801.

Sources

Based on U.S. Geological Survey, "Landsat Collection 2 Level-3 Burned Area Science Product," Fact Sheet 2022–3083, USGS; a work of the United States government in the public domain. The figures are restored from the fact sheet's PDF. The source gives the tile size as 5,000 square meters in its text and 5,000 square miles in a caption; this page gives neither.

ভাষাEnglish

লাইসেন্স: CC0 1.0 (পাবলিক ডোমেইন) · গৃহীত হয়েছে pubs.usgs.gov

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