Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
