FORSAID has released its third practice abstract, “Neural Network for Remote Sensing”, on EU CAP Network, spotlighting the project’s use of artificial intelligence to transform forest pest monitoring.

This abstract introduces FORSAID’s application of deep learning-powered computer vision to quickly analyse the vast amounts of data collected through satellite, drone and aerial imagery. By training neural networks with field-verified images of pest-affected trees, the system can automatically detect signs of damage across large, even remote, forested regions.

The approach targets key questions for forest health: identifying where vulnerable tree species like oaks, pines and spruces are located, pinpointing pest outbreaks and predicting areas at future risk. This technology promises faster, more accurate and large-scale pest detection, enabling earlier interventions to safeguard Europe’s forests.

By combining remote sensing with AI, FORSAID is creating an efficient, scalable monitoring toolkit that will complement other innovative methods like automated traps and environmental DNA analysis, offering a smarter way to protect forest ecosystems.

Read the full abstract here.