1 km annual forest cover and plant functional types dataset for China from 1980 to 2023

Abstract. High–spatial–resolution and long-term data on forest cover and plant functional types (PFTs) are crucial for elucidating the impacts of forest cover change on the national terrestrial carbon balance. Since the 1980s, China has undergone a substantial expansion in its forest area, primarily driven by large-scale national afforestation programmes. However, existing land cover products have often failed to capture this long-term increasing trend, leading to an underestimation of forest cover change–related ecological processes. Here, we developed a high-resolution (1 km), annual forest cover dataset for China during 1980–2023. This dataset integrates spatial constraints from multi-source remote sensing data with provincial-level statistics from China’s national forest inventories (NFIs), providing a consistent and spatially explicit record of forest dynamics over four decades. Building on this primary dataset, we further produced an annual PFT dataset that disaggregates total forest cover into eight distinct functional types, tailored for use in dynamic global vegetation models (DGVMs). Validation against independent data confirms the dataset’s ability to accurately represent historical forest recovery, achieving an overall accuracy (OA) of 95.3 ± 0.5 %, with classification accuracies for needleleaf and broadleaf forests ranging from 84.4 % to 92.0 %. To evaluate its applicability, we implemented the dataset within the Lund–Potsdam–Jena General Ecosystem Simulator (LPJ–GUESS). Compared to the widely used PFT dataset from the European Space Agency’s Land Cover Climate Change Initiative (ESA CCI), our product yields a markedly improved simulation of key biophysical and biogeochemical processes in China, enhancing the accuracy of evapotranspiration, leaf area index (LAI), and vegetation carbon flux by 49.4 %–77 %. With its high spatial resolution, long–term temporal coverage, and detailed forest-type classification, our dataset offers a robust foundation for assessing the ecological impacts of forest restoration and for constraining estimates of China’s forest carbon sink since 1980. The dataset is freely available at 10.5281/zenodo.16208012 (Liu et al., 2025).