Forest digital twin: coupling field data, mathematical modelling and 3D representation of a Mediterranean forests

Knowledge of forest ecosystem pattern and process responses to climate change and anthropogenic pressure requires innovative tools that combine monitoring and modelling of tree growth dynamics to account for a more sustainable management of forest resources and ecosystem services. In this context, Digital Twins (DTs) emerge as powerful tool to allow a better interpretation of complex models, summarizing a large amount of data and knowledge into a comprehensive 3D visualization. A Digital Twin is an evolving and comprehensive representation of a physical object, in our case trees, which involves three key elements: a digital representation of the object, an evolving set of data and a dynamic adjustment of the object data. However, due to the structural complexity of the forest stand, and the lack of adequate growth historical data series useful to build and validate the simulations, the full potential of Digital Twin frameworks has yet to be realized in forest field. Our work aims to develop a system that simulate forest growth and spatial patterns through a process-based single tree model and represent the outputs into a 3D immersive and interactive environment, able to reproduce the stand structure of Mediterranean forests. An individual based spatially explicit model has been developed to simulate the biomass growth within a time step of one year and while an immersive 3D dynamic environment enables the user to interact with trees (e.g. tree marking, logging). Competition among trees has been modelled computing the tree influence on surroundings space using a distance-biomass dependent approach. We implemented a set of allometric equations to convert tree biomass into size attributes (e.g. stem diameter, total height) to appropriately represent the modelled forest stand in the 3D environment. The use of DTs can assist forest experts and policymakers in managing complex systems like Mediterranean forests, by simulating several management scenarios and analysing their long-term impacts on forest ecosystem dynamics. Furthermore, process-based models coupled with an immersive 3D representation could help to better understand the forest ecosystem functioning.