Lucas, Moritz

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.

Project team: Moritz Lucas (Ph.D. Student), Prof. Dr. Björn Waske (UOS), Dr.-Ing. Ralf Pecenka (ATB)

Living Planet Symposium

 Poster

Publications

2024

• M. Lucas, M. Pukrop, P. Beckschäfer, and B. Waske,  Individual tree detection and crown delineation in the Harz National Park from 2009 to 2022 using mask R–CNN and aerial imagery, in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol. 13, pp. 100071, 2024. doi:10.1016/j.ophoto.2024.100071
• M. Lucas, V. Barkov, R. Pecenka, M. Atzmueller, and B. Waske,  Mapping trees outside forests using semantic segmentation, in IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, pp. 4435–4438, 2024. doi:10.1109/IGARSS53475.2024.10641035

2023

• M. Lucas, A. Dasgupta and B. Waske,  Analyzing Gradual Vegetation Changes in the Athabasca Oil Sands Region Using Landsat Data, in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 1365-1377, 2023, doi:10.1109/JSTARS.2023.3234090