Abstract
Wildland fires and windthrows represent relevant disturbances for forest ecosystems worldwide. In this context, especially for Italian catchments, the interaction between windthrows and changes in wildfire behaviour starting from ALS data processing is scarcely investigated. Therefore, this research aims to compute a multi-temporal analysis of the interaction between windthrows and wildfire behaviour in a forested area (Veneto region, northern Italy), recently affected by the renamed Vaia windstorm. The semi-empirical FlamMap model was applied, starting from ALS data processing implemented in R for mapping the spatial distribution of forest attributes and fuels within the catchment. The role of windthrows in altering wildfire behaviour was investigated considering ALS point clouds acquired before and after the occurrence of the storm Vaia. Digital Terrain Models (DTMs), Canopy Height Models (CHMs), topographic data and metrics describing forest structure were extracted from ALS data for both scenarios at 5 m resolution, to compare changes in wildfire behaviour over time. Differences in Rate of Spread (RoS), flame length (FL), midflame windspeed (WS) and arrival time (AT) were assessed, and their correlation with windstorm damages was investigated at the catchment detail. , An increase of RoS, FL, and WS greater than 30 m/min, 3 m and 1.1 m/s were respectively estimated in windthrown areas, as well as a decrease of AT greater than 30 min, attesting the key role of windthrows in altering wildfire behaviour over time. The correlation between windthrows and changes in wildfire attributes was finally modeled by computing regression analysis, with R2 of 0.86, 0.93, 0.62, and 0.91 resulted for RoS, FL, WS and AT. This research represents a pilot case study for better detecting changes in wildfires behaviour due to windthrows occurrence, therefore proposing and carrying out effective planning and management strategies for disturbed forest stands over time.
Published Version
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