The assessment of burn severity is highly important in order to describe and measure the effects of fire on vegetation, wildlife habitat and soils. The estimation of burn severity based on remote sensing is a powerful tool that, to be useful, needs to be related and validated with field data. The present paper explores the relationships between field accessible variables and Relative Differenced Normalized Burn Ratio (RdNBR) index by using linear mixed-effects models and boosted regression trees, based on data from 28 large fires and 668 field measurements across three countries in southern Europe. The RdNBR clearly reflected the mean height of charred stem and loss of ligneous, living shrub and tree cover during the fire. The paper confirms that remote sensing indices provide an acceptable assessment of fire induced impact on forest vegetation but also highlights there are important between-fire variations due to specific contexts that modify these relationships. These variations can be effectively assessed and should be taken into account in future predictive efforts.