Project Description

FIMS is a digital predictive tool for forestry management that helps forecast the evolution of forests under a series of key environmental parameter changes. It uses Lidendenmayer computational algorithms to model changes in the parameters of trees. Aerial imagery and field data source the algorithm to model branches development and species spatial distribution changes, which in turn help to plan urban tree plantation, reforestation, pruning and wildfire prevention strategies. FIMS is coupled with a novel agent-based approach to include the effects of external factors such as topography, sunlight intensity, wind trends, climate change, pests and disease, wildlife and infrastructures.

FIMS is a digital prediction tool designed to help managing forests by city councils, government and the wood industry. It will help forecast the spatial evolution of a forest or green area throughout time. Its spatial data in 2D and 3D formats serve for implementing strategies for wildfire prevention (e.g., prescribed burning and pruning), disease control and other needs associated with maintaining healthy forests.