Modeling the interaction between wildfire behaviour and bark beetle outbreak from LiDAR data: new perspective for Italian forests

Among the main issues affecting European forests, forest fires, windstorm and bark beetles outbreaks nowadays represent the most relevant one. In this regard, local stakeholders are  actually facing with critical circumstances both concerning the implementation of efficient silvicultural management of forest stands affected by such problematics. The storm Vaia occurred in 2018 in northeastern Italy created an unexpected scenario for Italian Alps. Following the windthrow produced by the storm, bark beetles proliferated from the downed logs, therefore moving to the neighbour standing forest and modifying the characteristics and the availability of forest fuel. In this context, the development of remote sensing techniques such as Light Detection and Ranging  (LiDAR) and Unmanned Aerial Vehicle (UAV)-based data acquisition, together with wildfire behaviour models, allow researchers to perform detailed estimation of forest fuels, necessary to simulate fire behaviour over disturbed forested areas over time. The prediction of key factors related to wildfire risk (e.g., fire type, rate of spread, flames lengths) is useful in estimating fire behaviour also in those areas affected by bark beetles proliferation. In this connection, new methods able to overcome notable limitations in forest fire simulations is nowadays needed. In particular, the interaction between bark beetles outbreaks and wildland fire dynamics were investigated focusing on a forested catchment (Veneto region, Italy) recently affected by the VAIA storm and hence involved in a widespread outbreak of bark beetle (Ips typographus). Extensive field data collection and the FlamMap fire behaviour model were coupled with high-resolution LiDAR and UAV-based analysis, to compare wildfire behaviour before and after beetle outbreak. Results could enrich the amount of information available for local administration of the Alpine region, in order to find effective interventions and management options for the areas affected by similar natural disturbances over time.