Su, YangSchwartz, MartinFayad, IbrahimGarcía, MarianoZavala, Miguel A.Tijerín-Triviño, JuliánAstigarraga, JulenCruz Alonso, VerónicaLiu, SiyuZhang, XianglinChen, SongchaoRitter, FrançoisBesic, Nikolad’Aspremont, AlexandreCiais, Philippe2025-05-292025-05-292025-04Su, Y., Schwartz, M., Fayad, I. et al. Canopy height and biomass distribution across the forests of Iberian Peninsula. Sci Data 12, 678 (2025). https://doi.org/10.1038/s41597-025-05021-910.1038/s41597-025-05021-9https://hdl.handle.net/20.500.14352/120649Acknowledgements: MAZ, JTT, JA and VCA acknowledge support from the Spanish Ministry of Science and Innovation (grant LARGE, Nº PID2021-123675OB-C41, Agencia Estatal de Investigación). MG acknowledges support from the Spanish Ministry of Science and Innovation (grant REMOTE, Nº PID2021-123675OB-C42). VCA was supported by the Ministry of Universities, Spain, and Next Generation-EU, with “Maria Zambrano” fellowship. PC acknowledges support from the European Space Agency Climate Space RECCAP2-CS project (ESA ESRIN/4000144908) and the CALIPSO project funded by the generosity of Schmidt Science. YS, PC, MS, IF and AD are supported by the French German project AI4FOREST (ANR-22-FAI1-0002-01) funded by ANR and DLR.Accurate mapping of vegetation canopy height and biomass distribution is essential for effective forest monitoring, climate change mitigation, and sustainable forestry. Here we present high-resolution remote sensing-based canopy height (10 m resolution) and above ground biomass (AGB, 50 m resolution) maps for the forests of the Iberian Peninsula from 2017 to 2021, using a deep learning framework that integrates Sentinel-1, Sentinel-2, and LiDAR data. Two UNET models were developed: one trained on Airborne Laser Scanning (ALS) data (MAE: 1.22 m), while another using Global Ecosystem Dynamics Investigation (GEDI) footprints (MAE: 3.24 m). External validation with 6,308 Spanish National Forest Inventory (NFI) plots (2017–2019) confirmed canopy height reliability, showing MAEs of 2–3 m in tree-covered areas. AGB estimates were obtained through Random Forest models that linked UNET derived height predictions to NFI AGB data, achieves an MAE of ~29 Mg/ha. The creation of high-resolution maps of canopy height and biomass across various forest landscapes in the Iberian Peninsula provides a valuable new tool for environmental researchers, policy makers, and forest management professionals, offering detailed insights that can inform conservation strategies, carbon sequestration efforts, and sustainable forest management practices.engAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/journal article2052-4463https://doi.org/10.1038/s41597-025-05021-9https://www.nature.com/articles/s41597-025-05021-9#article-infoopen access581.526.42(460)574.3(460)Ecología (Biología)2417.13 Ecología Vegetal3106 Ciencia Forestal2506.16 Teledetección (Geología)