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Normalized Burn Ratio

Contributors: Jason Karl

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The Normalized Burn Ratio (NBR) was defined to highlight areas that have burned and to index the severity of a burn using Landsat TM imagery. The formula for the NBR is very similar to that of NDVI except that it uses near-infrared band 4 and the short-wave infrared band 7:

The NBR equation was designed to be calcualted from reflectance, but it can be calculated from radiance and digital_number_(dn) with changes to the burn severity table below.

For a given area, NBR is calculated from an image just prior to the burn and a second NBR is calculated for an image immediately following the burn. Burn extent and severity is judged by taking the difference between these two index layers:

The meaning of the ∆NBR values can vary by scene, and interpretation in specific instances should always be based on some field assessment. However, the following table from the USGS FireMon program can be useful as a first approximation for interpreting the NBR difference:

ΔNBR Burn Severity Categories

ΔNBR Burn Severity
< -0.25 High post-fire regrowth
-0.25 to -0.1 Low post-fire regrowth
-0.1 to +0.1 Unburned
0.1 to 0.27 Low-severity burn
0.27 to 0.44 Moderate-low severity burn
0.44 to 0.66 Moderate-high severity burn
> 0.66 High-severity burn

Typically, NBR and ΔNBR images are generated shortly after a fire burns to get an initial assessment of burn severity and to support field work. During the next growing season, NBR datasets are calculated again (called “extended assessments”) to assess vegetation survival and delayed mortality.

Similar Methods

The normalized burn ratio is a vegetation index and in form is a modification of the Normalized Difference Vegetation Index. The ΔNBR technique is a form of Change Detection. Other fire-related methods include fire anomaly mapping/detection and surface temperature mapping.


Applying the NBR algorithm to an image will yield an output image containing index values centered around zero. Because of the form of the NBR equation, output values are constrained to +/- 1. For ΔNBR, most output values will be between -1 and +1, but ΔNBR is not constrained to these values.

Successful Rangeland Uses

  • The Normalized Burn Ratio has been adopted as part of the FireMon program and is routinely used by Burned Area Emergency Response (BAER) teams for post-fire assessments by many US land management agencies.

Application References

Technical References

  • Cocke, A. E., Fulé, P. Z. and Crouse, J. E. (2005) Comparison of burn severity assessments using Differenced Normalized Burn Ratio and ground data. International Journal of Wildland Fire, 14, pp. 189-198.
  • Escuin, S., R. Navarro, P. Fern\, \#225, and ndez. 2008. Fire severity assessment by using NBR (Normalized Burn Ratio) and NDVI (Normalized Difference Vegetation Index) derived from LANDSAT TM/ETM images. Int. J. Remote Sens. 29:1053-1073.
  • Epting, J., Verbyl, D. and Sorbel, B. (2005) Evaluation of remotely sensed indices for assessing burn severity in interior Alaska using Landsat TM and ETM+. Remote Sensing of Environment, 96, pp. 228-239.
  • Loboda, T. K.J. O'Neal, and I. Csiszar. 2007. Regionally adaptable dNBR-based algorithm for burned area mapping from MODIS data. Remote Sensing of the Environment 109(4):429-442.
  • Miller, J.D. and A.E. Thode. 2007. Quantifying burn severity in a heterogeneous landscape with a relative version of the delta normalized burn ratio (dNBR). Remote Sensing of the Environment 109(1):66-80
  • Roy, D. P., Boschetti, L. and Trigg, S. N. (2006) Remote sensing of fire severity: assessing the performance of the Normalized Burn Ratio. IEEE Geoscience and Remote Sensing Letters, 1, pp. 112-116.
  • Walz, Y., S.W. Maier, S.W. Dech, C. Conrad, and R.R. Colditz. 2007. Classification of burn severity using Moderate Resolution Imaging Spectroradiometer (MODIS): A case study in the jarrah-marri forest of southwest Western Australia, Journal of Geophysical Research 112, G02002.
  • Weber, K.T. S. Seefeldt, C. Moffet, and J. Norton. 2008. Comparing fire severity models from post-fire and pre/post-fire differenced imagery. GIScience and Remote Sensing 45(4):392-405.


The NBR algorithm requires a short-wave infrared band, so its implementation is limited to those imaging platforms that have a short-wave band (e.g., Landsat, MODIS). Also, the ΔNBR technique is sensitive to phenological or vegetation/soil moisture conditions before and after the fire.

Data Inputs

The Normalized Burn Ratio was designed to work with the short-wave and near infrared bands of the Landsat TM satellites. NBR can be calculated on any single image, but the ΔNBR will require two or more images. NBR can be calculated from DNs (i.e., 8-bit digital numbers [0 to 255]), radiance, or reflectance. The output values may be different for each input data types, and the burn severity values may need to be adjusted.

Software/Hardware Requirements

The Normalized Burn Ratio can be calculated in almost any image processing or GIS package that can process raster data. No specialized software or hardware is needed.

Sample Graphic

Example of normalized burn ratio from a fire at Camp Gurnsey, Wyoming in 2006. Note that this example is for illustration purposes only. The ΔNBR burn severity categories were taken directly from the FireMon cheatsheet and were not adjusted for the area. Additionally, the date difference between the two images is larger than is desirable for burn severity analysis and may be contributing the the over-prediction of low severity burn.

Additional Information

Who Is Using This Method?

Existing datasets

  • An archive of NBR and ΔNBR images for past fires on National Park Service, Bureau of Land Management, or Forest Service lands can be found at the NPS/USGS Burn Severity Mapping Project website:

Implementation help

  • Contact information for groups/people who can help implement this method either for free or for a fee.

Web Search Results



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remote_sensing_methods/normalized_burn_ratio.txt · Last modified: 2012/05/01 09:00 by jgillan