Title
Remote sensing of fire severity: assessing the performance of the normalized burn ratio
Abstract
Several studies have used satellite data to map different levels of fire severity present within burned areas. In- creasingly, 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 spec- tral 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.
Year
DOI
Venue
2006
10.1109/LGRS.2005.858485
Geoscience and Remote Sensing Letters, IEEE
Keywords
Field
DocType
fires,forestry,geophysical techniques,remote sensing,vegetation,Australian savanna,NBR index isolines,Russian Federation boreal forest,South African savanna,South American tropical forest,fire severity,index theory,normalized burn ratio,reflectance data,remote sensing,spectral displacements,spectral index,Fire severity,remote sensing,spectral index
Vegetation,Normalization (statistics),Multispectral image,Remote sensing,Taiga,Tropical forest,Reflectivity,Mathematics,Satellite data
Journal
Volume
Issue
ISSN
3
1
1545-598X
Citations 
PageRank 
References 
23
4.58
1
Authors
3
Name
Order
Citations
PageRank
David P. Roy130164.93
Luigi Boschetti212021.77
Simon N. Trigg3234.58