Remote Sensing of Fire Severity: Assessing the Performance of the Normalized Burn Ratio

TLDR

Satellite data are used to map fire severity, often via the normalized burn ratio (NBR), which theory suggests would optimally quantify severity if spectral trajectories were perpendicular to its isolines. This letter evaluates whether NBR meets the ideal requirements for measuring fire severity. The authors test NBR’s performance using pre‑ and post‑fire reflectance data from South African savanna, Australian savanna, Russian boreal forest, and South American tropical forest. Results show that NBR does not consistently align with fire severity, as spectral shifts occur in many directions relative to its isolines, indicating that future remote‑sensing methods should incorporate knowledge of how different severities displace prefire vegetation in multispectral space.

Abstract

Several studies have used satellite data to map different levels of fire severity present within burned areas. Increasingly, fire severity has been estimated using a spectral index called the normalized burn ratio (NBR). This letter assesses the performance of the NBR against ideal requirements of a spectral index designed to measure fire severity. According to index theory, the NBR would be optimal for quantifying fire severity if the trajectory in spectral feature space caused by different levels of severity occurred perpendicular to the NBR isolines. We assess how well NBR meets this condition using reflectance data sensed before and shortly after fires in the South African savanna, Australian savanna, Russian Federation boreal forest, and South American tropical forest. Although previous studies report high correlation between fire severity measured in the field- and satellite-derived NBR, our results do not provide evidence that the performance of the NBR is optimal in describing fire severity shortly after fire occurrence. Spectral displacements due to burning occur in numerous directions relative to the NBR index isolines, suggesting that the NBR may not be primarily and consistently sensitive to fire severity. Findings suggest that the development of the next generation of methods to estimate fire severity remotely should incorporate knowledge of how fires of different severity displace the position of prefire vegetation in multispectral space.