Snow avalanches are natural hazards that occur in high mountain environments, where they frequently disturb forest ecosystems. There is a strong interdependence between avalanche frequency and forest vegetation structure. Avalanches influence the shape, size, and spatial distribution of trees within avalanche paths, creating specific morphologies of disturbed forests, while the presence or absence of forest cover can inhibit or promote the occurrence. A detailed understanding of forest and shrub characteristics within avalanche paths is therefore essential for determining the spatial and temporal distribution of snow avalanches, estimating return periods, and conducting geomorphological hazard zoning. Combining dendrochronology with remote sensing techniques provides a better temporal and spatial resolution for reconstructing snow avalanche activity. The project aimed to evaluate snow avalanche activity and forest vegetation dynamics in avalanche paths on the eastern slope of the Piatra Craiului Mountains.
A total of 178 trees were analyzed in the avalanche path (1) and 136 in path (2). Event years were determined based on the number, type, and intensity of growth anomalies identified in the tree rings of collected samples. In total, 987 growth anomalies were identified in path (1) and 814 in path (2); only anomalies of moderate and strong intensity were used for avalanche reconstruction. These anomalies enabled the reconstruction of snow avalanche chronologies for each of the two paths. A minimum of 18 events were reconstructed for path (1) and 19 events for path (2), covering the common period 1980–2025. The event years 2020, 2018, 1997, and 1985 showed the highest Avalanche Activity Index (AAI) values and were common to both paths. For these years, AAI values ranged between 41% and 63%. The results indicate that AAI values above 40% correspond to major events, characterized by both a large number of affected trees and the strong growth responses recorded in their tree rings.
The reconstructed event years were used to calculate mean return periods for each avalanche path, following the method of Meseșan et al. (2019). These return periods represent the average interval at which avalanches reach specific locations along the path. The return periods calculated for the release zone and the upper part of the transport zone are 3 years in path (1) and 4 years in path (2). In the middle and lower sectors of the transport zone, return period values range between 8–10 years in path (1) and 10–14 years in path (2). In the lower part of the transport zone, at the transition to the accumulation area, the calculated return period is 21 years for both analyzed paths.
UAV images were used to generate a Digital Surface Model (DSM) with a spatial resolution of 0.43 m, followed by a Digital Terrain Model (DTM). The DSM supported the creation of RGB orthomosaics at 0.21 m resolution. These products enabled the estimation of tree heights. A total of 1,894 trees were manually vectorized, and a Canopy Height Model (CHM) was produced by normalizing the point cloud and rasterizing it at 0.02 m using the lidR package. After artifact removal, tree heights were extracted using the segmentation algorithm of Dalponte and Coomes (2016), which identifies individual tree crowns based on peak detection and canopy structure parameters.
Tree heights derived from the CHM were compared with three return-period categories in avalanche path (2): 1–5 years, 5–10 years, and 10–15 years. The combined analysis of return periods and tree heights reveals a clear relationship between avalanche frequency and vegetation structure. In areas with frequent avalanche activity, short trees (under 5 m) dominate, and tall trees are scarce. As avalanche frequency decreases, vegetation gradually shifts from shrub associations and small trees to taller, more developed forest stands. This demonstrates the long-term role of avalanches in shaping forest structure and ecosystem diversity.
These results enhance understanding of snow avalanche activity and support geomorphological hazard zoning within the investigated paths. The results will assist the administration of Piatra Craiului National Park in planning tourism activities within the massif.