Timely, accurate, and spatial explicit information on forest structure, such as canopy height, is important to understand and respond to ongoing changes in forests and to support the mapping of habitat structure. The availability of spaceborne LiDAR data, such as those from GEDI, has stimulated the development of continental to global canopy height maps. Yet, while GEDI data are often used to train canopy height models, these data are lacking in northern areas. In this study, we mapped canopy height over Europe at 10 m resolution by combining Sentinel-1 and Sentinel-2 data and integrating training data from GEDI and ICESat-2. The integration of ICESat-2 and GEDI data mostly enhanced the model performance in the north of Europe, where GEDI data are lacking. The model reached a RMSE of 5.77 m and a MAE of 4.09 m based on an independent validation with ALS data over about 3,700 patches across Europe. The resulting canopy height map and validation dataset have been made publicly available at <a href="https://doi.org/10.5281/zenodo.13324731" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13324731</a> and <a href="https://doi.org/10.5281/zenodo.18471620" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.18471620</a>, respectively.