Calculate the Normalised Burn Ratio (NBR) using Landsat 8 remote sensing data in Python
Calculate the Normalised Burn Ratio (NBR) using Landsat 8.
The Normalized Burn Ratio (NBR) is a remote sensing index specifically designed to identify burnt areas in large fire zones. Unlike NDVI, the NBR formula uses both near infrared (NIR) and shortwave infrared (SWIR) wavelengths to assess the severity of burn damage.
In healthy vegetation, the NIR portion of the spectrum shows a high reflectance, while the SWIR portion shows a low reflectance (as shown in Figure 1). In contrast, areas affected by fire exhibit a low reflectance in the NIR and a high reflectance in the SWIR. This difference in spectral response between healthy vegetation and burnt areas is most pronounced in the NIR and SWIR regions of the spectrum.
The NBR is calculated using the near-infrared (NIR) and shortwave-infrared (SWIR) bands of the Landsat imagery. The formula for calculating the NBR is:
NBR = (NIR — SWIR) / (NIR + SWIR)
The result of this calculation ranges from -1 to 1, with values closer to 1 indicating healthy vegetation and values closer to -1 indicating burnt areas.
To normalize the NBR and reduce variations caused by atmospheric conditions and sensor calibration, the difference Normalized Burn Ratio (dNBR) is used. It is calculated by subtracting the pre-fire NBR from the post-fire NBR.
The formula for calculating dNBR is:
dNBR = NBRpre — NBRpost
Where NBRpre is the NBR value for the pre-fire image, and NBRpost is the NBR value for the post-fire image.
The result of the dNBR calculation is a continuous variable that ranges from -2 to +2. Values greater than 0 indicate areas that have experienced higher severity of burn, while values less than 0 indicate areas that have experienced less severe burn.
Landsat 8 satellite imagery provides the necessary bands to calculate the NBR and dNBR, including the NIR and SWIR bands. The imagery can be processed using remote sensing…