This master’s thesis presents the applicability of remote sensing images in monitoring forest regeneration at the former mining site in the Upper Meža Valley. The analysis is based on a time series of Landsat dataset taken between June 1984 and January 2016. Changes were detected using normalized difference vegetation index (NDVI) as an input for BFAST Monitor algorithm, which divides time series into a stable history period and a detection period. The robust method BFAST Monitor offers a simple way of detecting changes occurring at different time intervals. The changes can be detected in specific selected raster cells, which enable generation of time profiles that show a dynamic multi-year forest regeneration, or can be mapped showing the trends in revegetation in an arbitrarily selected area.
The time profiles in this master’s thesis were generated for four specific locations in the immediate vicinity of the source of pollution in the town of Žerjav that have also been monitored by experts of the Biotechnical Faculty of the University of Ljubljana for many years. Both studies show the same trends: the state of the forests in the analysed areas has improved during the period of observation; or rather, the forests are regenerating. The final maps show the changes determined in three different time intervals: a 21-year time interval (1995–2016), a 16-year time interval (2000–2016) and an 11-year time interval (2005–2016). The number of positive changes predominates in all three time intervals, which further corroborates the fact that the forests in the Upper Meža Valley and its surroundings have been regenerating for the past 30 years. The results confirm all working hypotheses set in this paper and show that remote sensing technology can be used as an affordable, fast and effective means of assistance in further monitoring of forest health in Slovenia.