The goal of the work package 6 is to develop machine learning prediction model for tree growth using a data centric paradigm to achieve a high performance AI-model on high-frequency tree growth data. Furthremore, we aim to develop a framework focusing on data quality improvement by advantaging explainability and active learning techniques, explore latest data quality assessment techniques for machine learning models, and develop explainable error analysis method to automatically and iteratively improve the effectiveness and quality of data using AI-based architectures.

A WP6 meeting was held at the beginning of 2023 led by the data scientist Naghibzadeh-Jalali Anahid (AIT) and ecologist Anita Zolles (BFW). Among other things, the results of the exploratory analysis of the available dendrometer and environmental data was presented.