The latest project meeting of the AI-Recover (german: KI-Recover) project took the team to the wintry Bavarian Forest, where despite snow and icy temperatures, several reference and test areas were visited. The focus was on the forest stands shaped by storm events and other disturbances, which illustrate how complex and dynamic forest ecosystems react to external influences. The exchange on-site provided valuable insights into the data situation, monitoring methods, and the joint research goals of the project.
Particularly noteworthy is the close collaboration between science, practical partners, and technology development, which is crucial to the success of KI-Recover. Special thanks go to the Bavarian Forest National Park for hosting the meeting, as well as to all project partners for the productive exchange and inspiring conversations – and, of course, for their willingness to venture onto the sites even in the snow!
The KI-Recover project aims to develop an AI-based analysis and modeling of succession and reforestation measures after large-scale disturbances. It aims to support reforestation in forest ecosystems by monitoring carbon sequestration and the effectiveness of reforestation measures. Luftbild Umwelt Planung GmbH plays a central role in the analysis and evaluation of reforestation measures on disturbed areas using deep learning algorithms, particularly through the application of drone and aerial imagery to assess the growth success of seedlings.
Project start: May 2025
Duration: 3.5 years
FKZ: 67KIA4059C
Project Partners:
- Technical University (Department of AI and Land Use Change) – Project Management
- University of Freiburg (Group of Wildlife Ecology and Conservation Biology)
- Georg-August University Göttingen (Department of Silviculture and Forest Ecology of Temperate Zones)
