It is possible to estimate vegetation biophysical properties (e.g., leaf and wood biomass) with a satellite sensor to approximate regenerative stages. We identify the origin years of historic boreal harvests and wildfires in Ontario’s managed boreal forest, for the period before the availability of consumer of satellite data or where data is missing. Landsat satellites 5 TM, 7 ETM+, 8 OLI, and 9 OLI that include SWIR and TIR bands can be tested with the normalized difference vegetation index (NDVI), normalized burn ratio (NBR), near-infrared vegetation index (VINIR), and infrared vegetation index (VIIR). Backward prediction describes a statistical method of identifying missing/occluded disturbance origins by tracing incomplete regeneration trajectories with existing data. Backwards prediction matches incomplete disturbance time-series of vegetation index data to known disturbance—recovery trajectories stored in a database and predicting the point where the index was at a minimum, identifying the disturbance year. Since Landsat 1 – 5 MSS featured only visible and near-infrared (NIR) bands, we ask if it possible to predict disturbance origins with data from sensors onboard Landsat satellites predating 1985 that do not include shortwave-infrared (SWIR) and thermal-infrared (TIR) bands, with specific emphasis on disturbances occurring before the 1972 introduction of Landsat 1, using an alternative VI. The potential accuracy of predicted trajectories is assessed by performing in-line improvisation with known trajectories. For a representative subset of known regeneration trajectories drawn from summary groups defined by ecoregion, the disturbance origin point is removed and traced with the summary trajectory to provide a clear view of the potential accuracy of tracing for each group. The ability to trace disturbance origins obfuscated from the Landsat archive well as a general assessment of the potential accuracy of such methods, are significant outcomes.