Evaluating Landsat ETM+ emissivity-enhanced spectral indices for burn severity discrimination in Mediterranean forest ecosystems.

A. Fernández-Manso, C. Quintano. (2015) - Evaluating Landsat ETM+ emissivity-enhanced spectral indices for burn severity discrimination in Mediterranean forest ecosystems. - Remote Sensing Letters

Fires are a yearly recurring phenomenon in Mediterranean forest ecosystems. Accurate
classification of burn severity is fundamental for the rehabilitation planning of affected
areas. This work shows how conventional remote sensing methods for burn severity
assessment may be improved by using land surface emissivity (LSE) to enhance
standard spectral indices. We considered a large wildfire in August 2012 in north
western Spain. The composite burn index (CBI) was measured in 111 field plots and
grouped into three burn severity levels. Evaluation of the relationship between Landsat
7 Enhanced Thematic Mapper LSE-enhanced spectral indices and CBI was performed
by correlation analysis, regression models, and one-way analysis of variance. The
result was a 16.22% overall improvement in adjusted coefficient of determination over
the standard spectral indices. Our results demonstrate the potential of LSE for improving
mapping of burn severity. Future research, however, is needed to evaluate the
performance of the proposed spectral indices in other fire regimes and ecosystems.

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