Windstorms are natural disturbances predicted to increase in frequency in the future, with a consequent increased risk of damage to forests. Such damage severely affects the forest structure and, therefore, its protection capacity. Previous studies analyzed post event conditions and the recovery time of abated forest within study areas smaller than 10 ha, while not accounting for larger spatial scales. In this study, we propose a new methodology to provide tools for the spatial assessment and monitoring of protection forests against snow avalanches affected by large-scale windstorms. Four indices have been used: (i) vegetation height model, (ii) surface roughness, (iii) stored volume height and (iv) adapted tree parameters, of which the latter two have been specifically developed for this goal. We selected and periodically recorded two windthrow areas using photogrammetric surveys (deriving dense point clouds) to assess the performance of the proposed indices and to investigate the long-term changes in protective effects (Disentis, CH) and the influence of snow cover (Franza, IT). Stored volume height and the adapted tree parameters were the best indices to capture the forest conditions and standing trees, respectively. The stored volume height was further used to estimate forest protective capacity in relation to the snow cover height. Analyzing the Disentis (CH) area, we concluded that the minimum level of protective capacity occurs ten years after the storm event. After 29 years, the forest protective capacity against natural hazards increased again as forest recovery proceeded. However, special attention should be given to gaps between growing trees that may be critical for potential avalanche formation as wood decays. This study provided new insights into the long-term protective efficiency of windthrow forests, introducing two new indices to spatially assess and monitors their evolution.

Novel indices for snow avalanche protection assessment and monitoring of wind-disturbed forests

Baggio, T
;
D'Agostino, V
2022

Abstract

Windstorms are natural disturbances predicted to increase in frequency in the future, with a consequent increased risk of damage to forests. Such damage severely affects the forest structure and, therefore, its protection capacity. Previous studies analyzed post event conditions and the recovery time of abated forest within study areas smaller than 10 ha, while not accounting for larger spatial scales. In this study, we propose a new methodology to provide tools for the spatial assessment and monitoring of protection forests against snow avalanches affected by large-scale windstorms. Four indices have been used: (i) vegetation height model, (ii) surface roughness, (iii) stored volume height and (iv) adapted tree parameters, of which the latter two have been specifically developed for this goal. We selected and periodically recorded two windthrow areas using photogrammetric surveys (deriving dense point clouds) to assess the performance of the proposed indices and to investigate the long-term changes in protective effects (Disentis, CH) and the influence of snow cover (Franza, IT). Stored volume height and the adapted tree parameters were the best indices to capture the forest conditions and standing trees, respectively. The stored volume height was further used to estimate forest protective capacity in relation to the snow cover height. Analyzing the Disentis (CH) area, we concluded that the minimum level of protective capacity occurs ten years after the storm event. After 29 years, the forest protective capacity against natural hazards increased again as forest recovery proceeded. However, special attention should be given to gaps between growing trees that may be critical for potential avalanche formation as wood decays. This study provided new insights into the long-term protective efficiency of windthrow forests, introducing two new indices to spatially assess and monitors their evolution.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3455371
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