Moritz Lukas

Mapping Trees outside Forest, using multisensor Earth-Observation Data and Deep Learning

Trees outside of forests (TOF) play a critical role in biodiversity, cultural heritage, and landscape connectivity, especially in intensive agricultural areas and agroforestry systems. However, these trees are often neglected in conventional monitoring approaches, which tend to focus on forests or urban trees. This project aims to develop a robust methodology to map and classify TOFs, providing researchers, ecologists, and policymakers with better insight into their spatial distribution and structural characteristics. By integrating multisensor remote sensing data with state-of-the-art deep learning techniques, this project seeks to create a scalable tool for improving landscape-level assessments and supporting evidence-based decision-making.