China’s annual forest age dataset at a 30-m spatial resolution from 1986 to 2022

This dataset presents China’s Annual Forest Age (CAFA) at 30-m resolution from 1986 to 2022 (Version 2.0). It was derived by merging forest disturbance detection using Landsat data and age mapping of undisturbed forests using machine learning methods based on forest height, climate, terrain, and Landsat data (Shang et al., 2024; Shang et al., 2023; Lin et al., 2023). The forest extent was determined by the CLCD forest cover dataset (Yang et al. 2021). Areas classified as non-forest are set to -1, and the forest age for the year in which a disturbance occurred is set to 0. We welcome any feedback on our data for future updates!<b>Update History</b>Version 1.0: Initial release of China's forest age in 2019, as reported by Shang et al., 2023.Version 1.1: Update the forest mask using the CLCD forest cover dataset.Version 1.2: Improved forest age retrieval of undisturbed forests using machine learning methods with optimized model inputs, especially for the northeast and southwest of China.Version 1.3: Improved forest disturbance detection by integrating spatial information.Version 1.4: Expansion to include annual forest age covering the period from 1986 to 2022 based on enhanced forest disturbance detection.Version 1.5: Improved forest disturbance detection by integrating bidirectional monitoring.Version 2.0: Update the forest ages before their first forest disturbance, as reported by Shang et al., 2025.<b>Notice</b>Due to storage limitations, only the forest age data in 2019 is uploaded here. For access to the data from other years, please click Google Drive for downloading.<b>Emails: </b>Rong Shang ([e-mail], https://www.researchgate.net/profile/Rong-Shang), Jing M. Chen ([e-mail]).<b>Citations</b>Shang R., Lin, X. Chen J.M., et al.,(2025), China's annual forest age dataset at a 30 m spatial resolution from 1986 to 2022. <i>Earth System Science Data</i> 17, 3219–3241. [Link]Shang R., Chen J.M., Xu M., et al.,(2023), China's current forest age structure will lead to weakened carbon sinks in the near future. <i>The Innovation</i> 4(6),100515. [Link]Lin, X., Shang, R., Chen, J.M., et al.,(2023), High-resolution forest age mapping based on forest height maps derived from GEDI and ICESat-2 space-borne lidar data. <i>Agricultural and Forest Meteorology</i> 339, 109592. [Link]<br>