A new burn severity index based on land surface temperature and enhanced vegetation index

• We proposed a new index for burn severity estimation by combining two surface biophysical parameters: land surface temperature and enhanced vegetation index.
• We examined performance of this new index using 264 composite burn index (CBI) field data collected in five past fire sites with different eco-type areas.
• Results show that the proposed index performed equally well in different post-fire areas with sparse or dense vegetation cover and relatively better than some commonly-used burn severity indices, such as: deltaNBR, RdNBR, RNBR.

Remotely sensed data have already become one of the major resources for estimating the burn severity of forest fires. Recently, Land Surface Temperature (LST) calculated from remote sensing data has been considered as a potential indicator for estimating burn severity. However, using the LST-based index alone may not be sufficient for estimating burn severity in the areas that has unburned trees and vegetation. In this paper, a new index is proposed by considering LST and enhanced vegetation index (EVI) together. The accuracy of the proposed index was evaluated by using 264 composite burn index (CBI) field sample data of the five fires across different regional eco-type areas in the Western United States. Results show that the proposed index performed equally well for post-fire areas covered with both sparse vegetation and dense vegetation and relatively better than some commonly-used burn severity indices. This index also has high potential of estimating burn severity if more accurate surface temperatures can be obtained in the future.