Forest fires are considered to be an important part in numerous terrestrial ecosystems and veg-etation types, being also a significant factor of ecosystem disruption, thus playing an important role in the structure and function of the ecosystems. Biomes are characterized by a specific type of fire regime which is a synergy of the climate conditions and the characteristics of the vegetation types dominating each biome. At global level, based on MODIS fire perimeters, we found that fires are occurring at 70% in the Tropical and Subtropical Grasslands, Savannas and Shrublands, fol-lowed by fires at Tropical and Subtropical Moist Broadleaf Forests by 7% and by fires at Deserts and Xeric Shrublands by 6.5%. The assessment of burned areas and the definition of the fire regimes can be implemented with freely available low-to-high resolution satellite data as those of Landsat and Sentinel-2. Moreover, the biomes are characterized by the phenology of the consisting vegetation types, a characteristic that can be useful in the monitoring of the vegetation, especially with remote sensing methods. Both the definition of the fire regime by reconstructing the fire history as well as the monitoring of the post-fire evolution of burned areas, are studied in our work with remote sensing methods. Specifically, the present paper is a pilot study implemented in a Mediterranean biome, aiming at the establishment of the methodological framework to (i) define fire regimes, (ii) characterize the phenological pattern of the vegetation (pre-fire situation) of the fire-affected areas and finally (iii) compare the phenology of the recovered fire-affected areas with the corresponding one of the pre-fire situation. We show that burned land mapping with a rule-based approach can be successfully applied to both Landsat and Sentinel-2 images, for delineating fire perimeters without however avoiding the final cleaning of the data because of some errors. Phenology on the other side can be useful in characterizing the phenological cycle of the type of vegetation that is affected by the fires and in assessing and quantifying the post-fire vegetation recovery and dynamics by the phenological assessment of the fire-affected areas and their comparison to the pre-fire situation by the dynamic time warping method. This method depicts a more elastic non-linear alignment al-lowing similar shapes to match even if they are out of phase in the time scale.