China’s annual forest age dataset at 30-m spatial resolution from 1986 to 2022
This dataset presents China’s annual 30-m forest age from 1986 to 2022 (Version 2.0). It was derived by merging forest disturbance detection using Landsat data and age mapping of undisturbed forests in 2019 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). Currently, the forest age before the first forest disturbance was set as -99 due to the lack of forest height data, and we are working to update these pixels shortly. We welcome any feedback on our data for future updates!
Update History
- 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 2.0: Expansion to include annual forest age covering the period from 1986 to 2022 based on enhanced forest disturbance detection.
Notice
- 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.
Emails: Rong Shang (rongshang90@gmail.com, https://www.researchgate.net/profile/Rong-Shang), Jing M. Chen (jing.chen@utoronto.ca).
Citations
- Shang R., Lin, X. Chen J.M., et al.,(2024), China’s annual forest age mapping at 30m spatial resolution from 1986 to 2022. In preparation. https://doi.org/10.6084/m9.figshare.24464170.
- 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. The Innovation 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. Agricultural and Forest Meteorology 339, 109592. [Link]
