Among the most common natural disturbances affecting Mediterranean mountain regions, forest fires, windstorms and bark beetle outbreaks jointly represent a relevant issue for European forests in geomorphological, ecological and social terms. In this regard, local stakeholders and authorities are nowadays facing critical circumstances, concerning the identification and implementation of efficient silvicultural management of forest stands affected by such issues. The storm Vaia occurred in 2018 in northeastern Italy, creating an unprecedented scenario for Italian Alps. Following the windthrow produced by the storm, bark beetles proliferated first on the downed logs, and later moved to the neighbour standing forest, modifying the quantity and availability of forest fuel. In this context, the development of remote sensing and photogrammetric techniques such as Light Detection and Ranging (LiDAR) and Unmanned Aerial Vehicle (UAV), as well as fire behaviour models, allow researchers to perform detailed terrain reconstruction and estimation of forest fuel, necessary to simulate fire behaviour over disturbed forested areas. Predicting key factors related to wildfire risk (e.g., fire type, rate of spread, flames length) is useful in estimating fire behaviour in windthrown areas affected by bark beetles outbreaks. At the same time models output reliability is principally limited by input data estimation, specifically concerning troubles in retrieving precise data such as fuel characteristics and fire behaviour fuel models in such disturbed areas. Therefore, new methods able to overcome these limitations in forest fire simulations are nowadays needed. The project RETURN aims to improve the implementation of fire behaviour modeling in forested areas affected by similar natural disturbances, enhancing spatial mapping of input layers for fire simulators in the Alpine region. In this research, the joint interaction between bark beetle outbreaks and wildland fire dynamics is investigated by coupling extensive field data collection and fire behaviour models with high-resolution LiDAR and UAV-based analysis. Results could enrich the information available for the local administration of the Alpine region to find effective interventions and management options for the areas affected by similar natural disturbances over time.
Modeling the interaction between bark beetle outbreaks and wildland fire behavior: new perspective for Italian forests affected by the storm Vaia
flavio taccaliti;emanuele lingua
2024
Abstract
Among the most common natural disturbances affecting Mediterranean mountain regions, forest fires, windstorms and bark beetle outbreaks jointly represent a relevant issue for European forests in geomorphological, ecological and social terms. In this regard, local stakeholders and authorities are nowadays facing critical circumstances, concerning the identification and implementation of efficient silvicultural management of forest stands affected by such issues. The storm Vaia occurred in 2018 in northeastern Italy, creating an unprecedented scenario for Italian Alps. Following the windthrow produced by the storm, bark beetles proliferated first on the downed logs, and later moved to the neighbour standing forest, modifying the quantity and availability of forest fuel. In this context, the development of remote sensing and photogrammetric techniques such as Light Detection and Ranging (LiDAR) and Unmanned Aerial Vehicle (UAV), as well as fire behaviour models, allow researchers to perform detailed terrain reconstruction and estimation of forest fuel, necessary to simulate fire behaviour over disturbed forested areas. Predicting key factors related to wildfire risk (e.g., fire type, rate of spread, flames length) is useful in estimating fire behaviour in windthrown areas affected by bark beetles outbreaks. At the same time models output reliability is principally limited by input data estimation, specifically concerning troubles in retrieving precise data such as fuel characteristics and fire behaviour fuel models in such disturbed areas. Therefore, new methods able to overcome these limitations in forest fire simulations are nowadays needed. The project RETURN aims to improve the implementation of fire behaviour modeling in forested areas affected by similar natural disturbances, enhancing spatial mapping of input layers for fire simulators in the Alpine region. In this research, the joint interaction between bark beetle outbreaks and wildland fire dynamics is investigated by coupling extensive field data collection and fire behaviour models with high-resolution LiDAR and UAV-based analysis. Results could enrich the information available for the local administration of the Alpine region to find effective interventions and management options for the areas affected by similar natural disturbances over time.Pubblicazioni consigliate
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