Our research focuses on the use of remote sensing in ecology, with an emphasis on vegetation characteristics and dynamics in both forest ecosystems and urban trees. A major challenge in this field lies in upscaling—translating insights from small-scale ecological processes to broader, landscape-level analyses. We address this gap by leveraging proximal sensing, which enables detailed observation at the level of individual trees. This approach helps bridge the scale gap, offering new opportunities to identify ecological patterns, assess the potential for upscaling, and better understand the limitations of current large-scale monitoring methods.

To analyze and integrate data across scales, we combine established with modern approaches including time series analysis, image classification, segmentation, photogrammetry, point cloud processing, and deep learning.

Individual Tree

At the tree level, we operate local sensor fields to capture real-time environmental data such as tree growth, soil moisture, and light intensity. We utilize state of the art technology to transmit information from each sensor to an interactive dashboard, enabling 24/7 live monitoring of individual trees. This system supports research, teaching, and public outreach.

Forest Stand

To study vegetation structure at the stand level, we use various LiDAR systems (TLS, MLS, ULS), UAV-based RGB and Multispectral, as well as experimental imagery using GoPros, Mobile Phones and Wildlife Cameras. These tools allow us to generate detailed 2D and 3D digital replicates of forest stands with high spatial precision and resolution.

Landscape

At the landscape scale, we integrate satellite imagery to observe large-scale vegetation dynamics. This enables us to connect local ecological processes with regional and global patterns, supporting broader-scale analysis and long-term environmental monitoring.

 

We are currently specifically working on the topics:

• Urban trees in the context of tree detection, mapping, and classication, vitality, allergenicity
• Wild fires, Forest fires
• Forest Ecology
• Land degradation

Have a look at some recent papers published from researchers in our group:

Fassnacht, F.E., Mager, C., Waser, L.T., Kanjir, U., Schäfer, J., Potočnik Buhvald, A., Shafeian, E., Schiefer, F., Stančič, L., Immitzer, M., Dalponte, M., Stereńczak, K., Skudnik, M., 2025. Forest practitioners’ requirements for remote sensing-based canopy height, wood-volume, tree species, and disturbance products. Forestry: An International Journal of Forest Research 98, 233–252. https://doi.org/10.1093/forestry/cpae021

Schiller, C., Költzow, J., Schwarz, S., Schiefer, F., Fassnacht, F.E., 2024. Forest disturbance detection in Central Europe using transformers and Sentinel‑2 time series. Remote Sensing of Environment 315, 114475. https://doi.org/10.1016/j.rse.2024.114475

Stellmes, M., Sonnenschein, R., Röder, A., Udelhoven, T., del Barrio, G., Hill, J., Sommer, S., 2024. Land degradation assessment and monitoring of drylands. In: Remote Sensing Handbook, Volume VI, CRC Press/Taylor & Francis, Boca Raton, FL, USA, pp. 109–150. https://doi.org/10.1201/9781003541417‑6