Identifying ecologically relevant reference sites is important for evaluating ecosystem recovery, but the relevance of references that are temporally static is unclear in the context of vast landscapes with varying disturbance and environmental contexts over space and time. This question is pertinent for landscapes dominated by sagebrush (Artemisia spp.) which face a suite of threats from disturbance and development but also have lengthy recovery times. Here, we applied a dynamic reference approach to studying and projecting recovery of sagebrush on former oil and gas well pads in southwestern Wyoming, USA, using over 3 decades of remote sensing data (1985–2018). We also used quantile regression to evaluate factors that may affect recovery including soils, weather, elevation, and well pad characteristics. Data formatting necessary for this analysis created two datasets, one with reference pixels identified after applying both local and general masks (data_local.csv) and the other with only general masks (data_general.csv).