tForest fires are one of the most important causes of environmental alteration in Mediterranean countries.Discrimination of different degrees of burn severity is critical for improving management of fire-affectedareas. This paper aims to evaluate the usefulness of land surface temperature (LST) as potential indicatorof burn severity. We used a large convention-dominated wildfire, which occurred on 19–21 September,2012 in Northwestern Spain. From this area, a 1-year series of six LST images were generated from Landsat7 Enhanced Thematic Mapper (ETM+) data using a single channel algorithm. Further, the Composite BurnIndex (CBI) was measured in 111 field plots to identify the burn severity level (low, moderate, and high).Evaluation of the potential relationship between post-fire LST and ground measured CBI was performedby both correlation analysis and regression models. Correlation coefficients were higher in the immediatepost-fire LST images, but decreased during the fall of 2012 and increased again with a second maximumvalue in summer, 2013. A linear regression model between post-fire LST and CBI allowed us to representspatially predicted CBI (R-squaredadj> 85%). After performing an analysis of variance (ANOVA) betweenpost-fire LST and CBI, a Fisher’s least significant difference test determined that two burn severity levels(low-moderate and high) could be statistically distinguished. The identification of such burn severitylevels is sufficient and useful to forest managers. We conclude that summer post-fire LST from moderateresolution satellite data may be considered as a valuable indicator of burn severity for large fires inMediterranean forest ecosytems
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