P. 1-24Forest managers demand reliable tools to evaluate post-fire vegetation and soil damage. In
this study, we quantify wildfire damage to vegetation and soil based on the analysis of burn severity,
using multitemporal and multispectral satellite data and species distribution models, particularly
maximum entropy (MaxEnt). We studied a mega-wildfire (9000 ha burned) in North-Western Spain,
which occurred from 21 to 27 August 2017. Burn severity was measured in the field using the
composite burn index (CBI). Burn severity of vegetation and soil layers (CBIveg and CBIsoil) was also
di erentiated. MaxEnt provided the relative contribution of each pre-fire and post-fire input variable
on low, moderate and high burn severity levels, as well as on all severity levels combined (burned
area). In addition, it built continuous suitability surfaces from which the burned surface area and
burn severity maps were built. The burned area map achieved a high accuracy level ( = 0.85), but
slightly lower accuracy when di erentiating the three burn severity classes ( = 0.81). When the burn
severity map was validated using field CBIveg and CBIsoil values we reached lower statistic values
(0.76 and 0.63, respectively). This study revealed the e ectiveness of the proposed multi-temporal
MaxEnt based method to map fire damage accurately in Mediterranean ecosystems, providing key
information to forest managersS
