News Release

AI meets Forestry: EU Project SWIFTT webinar explores insect damage detection in European forests

The webinar will explore the practical and technical challenges of using artificial intelligence (AI) and satellite data to monitor bark beetle outbreaks

Meeting Announcement

Da Vinci Labs

Leveraging AI Models for Insect Damage Detection in European Forests

image: 

AI Meets Forestry: EU Project SWIFTT Webinar Explores Insect Damage Detection in European Forests 

view more 

Credit: SWIFTT Project

The SWIFTT project invites forest professionals, researchers, and remote sensing experts to its upcoming webinar, “Leveraging AI Models for Insect Damage Detection in European Forests,” taking place online on 11 July 2025, from 14:00 to 15:00 CEST (Paris Time). 

Register here to secure your spot. 

The webinar will explore the practical and technical challenges of using Artificial Intelligence (AI) and satellite data to monitor bark beetle outbreaks—one of the most pressing threats to forest health in Europe.  

In the first session, led by project partner Juris Zariņš (Rīgas Meži, LV), participants will gain insight into the real-world challenges of detecting insect damage early, a task made more difficult by the speed and subtlety of pest spread.  

This sets the stage for Prof. Annalisa Appice (UNIBA, IT), who will delve into how AI models can support large-scale monitoring—but only when anchored in accurate, high-quality field data.  

Together, these sessions highlight the critical interplay between remote sensing, machine learning, and traditional forestry knowledge, reinforcing SWIFTT’s mission to create practical tools that forest managers can trust and apply. 

About SWIFTT 

SWIFTT will provide forest managers with affordable, simple and effective remote sensing tools backed up by powerful machine learning models. Our solution will offer a holistic health monitoring service using Copernicus satellite imagery to detect and map the various risks to which forests and their managers are exposed. 

Learn more: https://swiftt.eu/  

SWIFTT is funded by the European Union under Grant Agreement 101082732. Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or European Union Agency for the Space Programme (EUSPA). Neither the European Union nor the granting authority can be held responsible for them. 


Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.