Strengthening weaknesses is one of the starting points in any management or developing plan, but what to do when even identifying them is tricky? Such is the problem forest managers often face while trying to predict and prevent storm damages to forests. The current models to predict storm damages suffer from lack of data, and the expected increase of severe storms caused by climate change adds its own spice to the mix.
However, there is hope in the future . Researchers from Edinburgh Napier University, INRA and Shinsu University have collaborated to combine computer sciences and forest management to create a novel way to predict storm damages to individual trees. By using artificial intelligence (AI), more precisely: machine-learning, they have created a model that has dramatically better accuracy rates than any other models currently have. According to the researchers, “the model relies on a type of artificial evolution called genetic programming (GP), which mimics evolution in the natural world to come up with completely new features that can be fed into a classification system to make it easier to discriminate between different trees”.
The model shows that artificial intelligence can exceedingly improve forest risk management. You can read the entire article (published in the academical journal The Conservation by Emma Hart, Chair in Natural Computation, Edinburgh Napier University and Barry Gardiner, Senior Scientist INRA/EFI Planted Forest Facility) here.