Articles | Volume 17, issue 12
https://doi.org/10.5194/essd-17-6993-2025
https://doi.org/10.5194/essd-17-6993-2025
Data description paper
 | 
10 Dec 2025
Data description paper |  | 10 Dec 2025

Dynamics of China's forest carbon storage: the first 30 m annual aboveground biomass mapping from 1985 to 2023

Yaotong Cai, Peng Zhu, Xing Li, Xiaoping Liu, Yuhe Chen, Qianhui Shen, Xiaocong Xu, Honghui Zhang, Sheng Nie, Cheng Wang, Jia Wang, Bingjie Li, Changjiang Wu, and Haoming Zhuang

Related authors

An improved global land cover mapping in 2015 with 30 m resolution (GLC-2015) based on a multisource product-fusion approach
Bingjie Li, Xiaocong Xu, Xiaoping Liu, Qian Shi, Haoming Zhuang, Yaotong Cai, and Da He
Earth Syst. Sci. Data, 15, 2347–2373, https://doi.org/10.5194/essd-15-2347-2023,https://doi.org/10.5194/essd-15-2347-2023, 2023
Short summary
MAPPING FOREST DISTURBANCE USING PURE FOREST INDEX TIME SERIES AND CCDC ALGORITHM
Y. Cai, Q. Shi, and X. Liu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-3-W1-2022, 1–6, https://doi.org/10.5194/isprs-archives-XLVIII-3-W1-2022-1-2022,https://doi.org/10.5194/isprs-archives-XLVIII-3-W1-2022-1-2022, 2022

Cited articles

Adler, P. B., Smull, D., Beard, K. H., Choi, R. T., Furniss, T., Kulmatiski, A., Meiners, J. M., Tredennick, A. T., and Veblen, K. E.: Competition and coexistence in plant communities: intraspecific competition is stronger than interspecific competition, Ecology Letters, 21, 1319–1329, https://doi.org/10.1111/ele.13098, 2018. 
Babcock, C., Finley, A. O., Cook, B. D., Weiskittel, A., and Woodall, C. W.: Modeling forest biomass and growth: Coupling long-term inventory and LiDAR data, Remote Sensing of Environment, 182, 1–12, https://doi.org/10.1016/j.rse.2016.04.014, 2016. 
Baccini, A., Goetz, S. J., Walker, W. S., Laporte, N. T., Sun, M., Sulla-Menashe, D., Hackler, J., Beck, P. S. A., Dubayah, R., Friedl, M. A., Samanta, S., and Houghton, R. A.: Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps, Nature Clim. Change, 2, 182–185, https://doi.org/10.1038/nclimate1354, 2012. 
Download
Short summary
China’s forests play a crucial role in storing carbon and mitigating climate change, yet long-term high-resolution data on their biomass have been limited. We developed a 30 m annual forest aboveground biomass dataset from 1985 to 2023 using satellite data and deep learning. Our results reveal significant biomass gains, regional variations, and the impact of forest policies. This dataset provides valuable insights for climate research, conservation planning, and sustainable forest management.
Share
Altmetrics
Final-revised paper
Preprint