The development of methods for identifying long-term land cover changes is important for many research domains that focus on environmental changes. Analyses of changes in forest vegetation cover are of particular relevance. The interpretation potential of results increases when, in addition to changes in an area occupied by forest cover, we are also able to identify the variability of the area’s height over time. The paper presents a method for precise assessment of changes in forest cover and height over several decades in forests and areas affected by agricultural land abandonment. The data was sourced from two point clouds: one set was collected using airborne laser scanning and represents the current state; the other was obtained from processed monochromatic stereometric aerial images and represents the historical state.The study involved a dataset made up of nine test fields of 1.3 km2 each. The data processing which was used to obtain a family of universal curves that represents certain aspects of forest cover and height changes during the time interval is described. The proposed approach could standardize the presentation and interpretation of long-term changes caused by agricultural land abandonment, deforestation, regular forestry operations, fires, outbreaks of forest pests, and extreme events like heat waves or droughts. This method can also be used to estimate the approximate point in time when events took place that led to a loss of forest cover. This can improve the accuracy of long-term analyses of the dynamics of the extent of forest cover changes and land abandonment.