LiDAR insights on stand structure and topography in mountain forest wind extreme events: the Vaia case study

With climate change intensifying, forests globally are becoming more susceptible to extreme weather events, such as windstorms, which account for a significant share of Europe’s economic losses. The Vaia windstorm of late autumn 2018, striking Italy’s northeast alpine ecosystem, highlighted this vulnerability, toppling over 8.5 million cubic meters of timber and sparking debates on forest management’s role in mitigating such disasters. This study aims to evaluate the impact of structural and topographical characteristics on the damage caused by Vaia, using Airborne Light Detection And Ranging (LiDAR) data col- lected before the storm, in four heavily affected forest areas in the Italian Alps (Carezza in the Province of Bolzano-Bozen, Predazzo, Manghen, and Primiero in the Province of Trento). We analyzed structural metrics like forest height heterogeneity (HH), forest mean height, and density, alongside topographical features such as aspect, slope, and altitude, to discern their influence on the storm’s severity. Our results revealed that factors such as forest mean height (which vary significantly between affected and unaffected areas)is the major contributors to storm damage. Forest density played a lesser but important role, with denser areas experiencing more severe damage, though this was only significant in certain areas. Contrary to common assumptions, our analysis revealed that height heterogeneity (HH) did not have a significant effect on damage levels. The results, supported by previous studies, found a notable association between certain aspects (in particular South-East) and increased damage likelihood. In general the results suggest that both structural and topographical factors interact in complex ways to influence the outcome of such extreme events. The study emphasizes the dominant impact of the Vaia windstorm, noting that while managing forest height and density may help, the diverse topography complicates these efforts. Our study explicitly tested the effectiveness of using Airborne LiDAR data to explore forest structural and topographical factors that influenced Vaia storm damage. The results demonstrate that LiDAR serves as a complementary tool to field data, offering valuable insights for broader applications in this area.