Vítězslav Moudrý, Ruben Remelgado, Matthias Forkel, Michele Torresani, Gaia Vaglio Laurin, Eliska Sarovcova, Virginia E. Garcia Millan, Fabian Jörg Fischer, Tommaso Jucker, Michal Gallay, Patrick Kacic, Christopher R. Hakkenberg, Žiga Kokalj, Krzysztof Stereńczak, Yousef Erfanifard, Duccio Rocchini, Jiří Prošek, Stephanie Roilo, Katerina Gdulova, Anna F. Cord, Michela Perrone, Juan Alberto Molina-Valero, Peter Surovy, Zlatica Melichová, Marco Malavasi, Rudolf Urban, Martin Štroner, Dominik Seidel, Szilárd Szabó, László Bertalan, Anette Etner, Roberto Cazzolla Gatti, Vojtech Barták

Vegetation structure data are essential for understanding the functioning of terrestrial ecosystems and for informing various science-policy interfaces. Recent years have seen a growing demand for high-resolution data on vegetation structure, driving the prediction of such metrics at fine resolutions (1 m - 30 m) at state, continental, and global scales by combining satellite data with machine learning. As these initiatives expand, it is crucial for the remote sensing and ecological communities to actively discuss the quality and usability of these products. Here, we (i) provide a brief overview of space-borne lidar missions measuring vegetation structure; (ii) using global canopy height models (CHMs) as an example, we demonstrate that predicted products exhibit significant errors exceeding natural changes in canopy height observed over a 10-year period, indicating that even a 10-year-old CHM derived from airborne laser scanning (ALS) is superior to currently available predicted CHMs; therefore, (iii) we recommend that regions with abundant ALS data prioritize harmonizing ALS-based vegetation metrics rather than relying solely on much less accurate predicted products derived from satellite data. We investigated the availability of ALS data in Europe and found that they are available for 26 countries, collected mostly between 2009 and 2024. We argue that, despite variations in data characteristics, including temporal inconsistencies and differences in point density and classification accuracy, the production of vegetation structure metrics, particularly CHMs, in raster format at fine resolution is both necessary and feasible. As new acquisitions are planned or underway, it is important to coordinate efforts to facilitate harmonization, develop continent-wide products, and ensure free access for research and policy communities. Beyond numerous ecological applications, such consistent benchmark datasets are crucial for calibrating future Earth Observation missions, making them essential for producing truly global, fine-resolution vegetation structure data.