Remote sensing offers reliable information on the rate and pattern of clear-cut logging and provides this information as relatively frequent updates, over large areas, and at relatively low cost. Temporal gaps in yearly images in a multiyear data set ranging from 1 year to multiple years can lead to inaccuracies in the determination of the area of clear-cuts and the estimation of clear-cut age. This study tested the dependence of reflectance in Landsat Thematic Mapper bands 1–5 and 7 and normalized difference vegetation index (NDVI) on forest age, gap size and forest type within the first 10 years following clear-cut logging in different seasons. The results of the study show that late winter images with snow-covered ground are phenologically the best timed images for detecting forest clear-cut area regionally. Spring and summer image are more useful for estimation of the successional age of clear-cut areas in various soil fertility and moisture conditions.