The discontinuous permafrost zone has been subject to increased air temperatures over recent decades. Permafrost thaw can cause changes to topography, hydrology, vegetation, and trace gas fluxes, and thus it is important to monitor changes in permafrost area through time. Optical imagery can be used to generate time-series databases of near-surface spectra that may be related to permafrost area. This provides a spatial perspective on area permafrost change that is not easily obtained from field data alone. This study examines the cumulative maximum and minimum errors of aerial and satellite imagery used for change detection within the Scotty Creek watershed, Fort Simpson, NWT, Canada. The results illustrate that, unless unchanging linear features are found throughout every image used (e.g., to be used as multitemporal tie points) and radiometric normalization can be applied (problematic for film images), direct image to image comparisons (e.g., subtraction) are not appropriate. Further, measureable cumulative errors are often produced by misclassification of edges, resolution limitations, and increased landscape fragmentation. At Scotty Creek, increased fragmentation of permafrost plateaus occurred from 1947 to 2008. Cumulative maximum and minimum errors result in an approximate 8%–26% error in permafrost area when compared with the total area of the site. Rates of permafrost area reduction within the study area were approximately 0.5% every year, determined from linear correlation (r2 = 0.91, n = 5). Therefore, based on the maximum cumulative error (a worst-case scenario), approximately 21–32 years (for resolutions of 0.18–1.10 m) is required between images to approximate change within this particular site. Increased (decreased) rates of change at other sites will decrease (increase) the timing required to identify change between images beyond error bounds.