Interpretations of post-fire condition and rates of vegetation recovery can influence management priorities, actions, and perception of latent risks from landslides and floods. In this study, we used the Waldo Canyon fire (2012, Colorado Springs, Colorado, USA) as a case study to explore how a time series (2011-2016) of high-resolution images can be used to delineate burn extent and severity, as well as quantify post-fire vegetation recovery. We applied an object-based approach to map burn severity and vegetation recovery using Worldview-2, 3, and QuickBird-2 imagery. The burned area was classified as 51% high, 20% moderate and 29% low burn-severity. Across the burn extent, the shrub cover class showed a rapid recovery, resprouting vigorously within one year, while four years post-fire, areas previously dominated by conifers were divided approximately equally between being classified as dominated by quaking aspen saplings with herbaceous species in the understory or minimally recovered. Relative to using a pixel-based Normalized Difference Vegetation Index (NDVI), our object-based approach showed higher rates of revegetation. High-resolution imagery can provide an effective means to monitor post-fire site conditions and complement more prevalent efforts with moderate- and coarse-resolution sensors.