In this study, a methodology based on the analysis of MODIS (MODerate-resolution Imaging Spectrora-diometer) time series was developed to estimate post-fire resilience of Alpine vegetation. To this end,satellite images of two vegetation indices (VIs), the Normalized Difference Vegetation Index (NDVI) andthe Enhanced Vegetation Index (EVI) were used. The analysis was conducted on wildfire affected areasin the Lombardy region (Italy) between 2003 and 2007. Some land surface (LS) descriptors (i.e. meanand maximum VI, growing season start, end and length) were extracted to characterize the time evolu-tion of the vegetation. The descriptors from a burned area were compared to those from an undisturbedadjacent control site by means of analysis of variance (one-way ANOVA). Post-fire resilience was esti-mated on the basis of the number of subsequent years exhibiting a statistical difference between burnedarea and control site. The same methodologies were also applied to events aggregated by main landcover (broadleaf forest, prairies and mixed forest). The averaged resilience of broadleaf forest was 5-6years, whereas prairie ecosystems exhibited a faster response of 0-2 years. Phenological analysis revealedthat fire induces a shift of the start and end of growing season in forest ecosystems but has no effect onprairies. The method provides a useful and quantitative insight into complex post-fire vegetation dynam-ics in the Alps from a remote sensing perspective; results can apply to post-fire forest management andto multi-risk analysis. © 2014 Elsevier B.V.