The product shows forest structure information on canopy height, total canopy cover and Above-ground biomass density (AGBD) in Germany as annual products from 2017 to 2022 in 10 m spatial resolution. The products were generated using a machine learning modelling approach that combines complementary spaceborne remote sensing sensors, namely GEDI (Global Ecosystem Dynamics Investigation; NASA; full-waveform LiDAR), Sentinel-1 (Synthetic-Aperture-Radar; ESA, C-band) and Sentinel-2 (Multispectral Instrument; ESA; VIS-NIR-SWIR).

Sample estimates on forest structure from GEDI were modelled in 10 m spatial resolution as annual products based on spatio-temporal composites from Sentinel-1 and -2 for six years (2017 to 2022). The derived products are the first consistent data sets on canopy height, total canopy cover and AGBD for Germany which enable a quantitative assessment of recent forest structure dynamics, e.g. in the context of repeated drought events since 2018. The full description of the method and results can be found in the publication of Kacic et al. (2023).