Geoinformatik

In our new project, funded by FAWF, we will integrate Sentinel-2 remote sensing, deep learning and site-factor analysis to produce high-resolution digital maps of coniferous forest disturbances and their succession trajectories. 

The project aims to qualitatively assess the influence of local management practices and environmental drivers, refine predictive models for post-disturbance growth, and compile comprehensive information layers on disturbance type, timing and recovery potential.