Presentation

The aim of Cross-Forest is to combine Forest Inventory Datasets, Forestry maps and observational Big Data to create and integrate models supporting forest management and forest protection. 

Fires propagation and their effects together with fire suppression techniques will be addressed in one of the pilots (FRAME – Forest fiRes Advanced ModElization). The aim of FRAME (Forest fiRes Advanced ModElization) is to improve forest fires prevention and control, as well as to train personnel in strategic operations. It focuses on using a HPC-adapted propagation model for predicting forest fires behavior and spreading according to high spatial and time resolution data related to weather (wind, temperature and humidity), vegetation and terrain, available or enhanced from public open data infrastructures from Portugal and Spain for a cross-border approach. FRAME will consider both fire spread parameters and performance of fire-fighting actions. The end users will be Public Administrations, Policy Makers and Emergency Professionals.

In another pilot, Cross-Forest will create models to forecast wood quality in mixed forests on higher surfaces than the municipality level by using the National Forest Inventory. This pilot will be fully oriented towards end users interests (i.e., wood for wine barrels, biomass production, raw material for Composite Laminated Timber) which will be completely integrated in the final models development. The final aim of this pilot is to facilitate the creation of a dynamic information platform – that could potentially be integrated in the JRC bio economy portal, section SIMWOOD2 information system – to improve commercial promotion of wood to fit end users interests.