Preprints
https://doi.org/10.5194/essd-2026-813
https://doi.org/10.5194/essd-2026-813
13 Oct 2026
 | 13 Oct 2026
Status: this preprint is currently under review for the journal ESSD.

ChinaTD30: An annual 30 m tree density dataset for China (1985–2022)

Ziyi Xian, Zhen Yu, Jinge Yu, and Shirong Liu

Abstract. Accurate information on tree density and its long-term dynamics is essential for understanding forest demography, ecosystem restoration, and terrestrial carbon cycling. However, existing tree-density products for China are generally limited by coarse spatial resolution, restricted temporal coverage, or a focus only on forested areas. Here, we developed a 30 m tree density dataset for China (ChinaTD30) spanning 1985–2022 by integrating four cycles of the National Forest Inventory (NFI), each comprising 670,279 plot observations, with long-term satellite observations, forest attributes, land-cover information, and environmental variables. Three modelling strategies were evaluated to balance prediction accuracy and temporal consistency, and a temporally unified model was adopted for the reconstruction of the released product. The resulting dataset characterizes tree density in both forest and non-forest ecosystems and resolves substantial spatial heterogeneity across China. Comparison with existing tree-density products showed large discrepancies in densely forested regions, partly reflecting differences in training data, spatial resolution, and model structure. The reconstructed time series reveals a pronounced long-term increase in China’s tree population. Forest trees increased from approximately 106 billion in 1985 to about 182 billion in 2022, an increase of approximately 72 %, while trees outside forests increased from about 2.3 billion to 5.1 billion. Tree number increases were evident not only across northern restoration regions but also in densely forested southeastern China. Tree density exhibited distinct age-related patterns between natural and planted forests, with densities generally peaking in youngto-middle-aged stands before declining in older stands. This dataset provides a spatially detailed and temporally consistent basis for investigating forest dynamics, ecological restoration, tree mortality, carbon cycling, and the contribution of trees outside forests across China. The dataset is available at https://doi.org/10.5281/zenodo.23100944 (Xian et al., 2026a), with the nine associated part records detailed in the Data availability section.

Competing interests: At least one of the (co-)authors is a member of the editorial board of Earth System Science Data.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
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Ziyi Xian, Zhen Yu, Jinge Yu, and Shirong Liu

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Ziyi Xian, Zhen Yu, Jinge Yu, and Shirong Liu

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ChinaTD30: An annual 30 m tree density dataset for China (1985–2022) Z. Xian et al. https://doi.org/10.5281/zenodo.23100943

Ziyi Xian, Zhen Yu, Jinge Yu, and Shirong Liu
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Short summary
We developed an annual 30 m tree-density dataset for China from 1985 to 2022 using national forest inventory observations and multi-source remote sensing data. The dataset captures long-term changes in tree density across forest and non-forest areas and provides uncertainty estimates, supporting studies of forest dynamics, ecosystem change, and land management.
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