AI for Climate Sensitive Tree Growth Modelling and Maximum Carbon Segregation
Changing climatic conditions pose significant challenges for forests, including rising temperatures, more frequent storms, and prolonged droughts. At the same time, European forests have served as a vital carbon sink, naturally removing CO₂ from the atmosphere and mitigating climate change. Tree growth is a key indicator of forest health and carbon sequestration, yet its complex dynamics make traditional statistical modelling inadequate, especially for capturing immediate responses to climate extremes and phenological changes.
With the increasing availability of high-resolution ecological and climatic data, AI technologies offer new opportunities for advanced tree growth modelling. The AI4Trees project leverages extensive forest monitoring networks across Austria and Europe, integrating multi-scale growth data—from hourly single-tree measurements to long-term stand development assessments. Additionally, airborne and terrestrial laser scanning, combined with satellite-derived parameters, will provide detailed spatial information to enhance model accuracy.
This integrated approach enables AI-driven models to capture both high- and low-frequency growth patterns while incorporating explainable AI for error analysis. The insights gained will support optimized carbon sequestration, biodiversity conservation, and climate adaptation in forest ecosystems, contributing to sustainable forest management in line with the UN Sustainable Development Goals.
Facts
- Project start: 1.4.2022
- Project duration (in months): 36
- Budget: 1,028 million EUR
- Funding: 775 kEUR
- Project partners: Umweltdata GmbH, GeoVille GmbH, Bundesforschungszentrum für Wald, E.C.O. Institut für Ökologie Jungmeier GmbH, Know-Center GmbH
- Project website: https://ai4trees-project.at/
