Unveiling spatiotemporal tree cover patterns in China: The first 30 m annual tree cover mapping from 1985 to 2023

China leads in the greening of the world, with a nearly doubled increase in its forest area since the 1980 s revealed by the National Forest Inventory (NFI). However, a significant challenge persists in the absence of consistent and reliable remote sensing data that align with the NFI, hindering a comprehensive understanding of the spatiotemporal patterns of terrestrial ecosystem changes driven by afforestation and reforestation efforts over recent decades in China. Moreover, conventional binary thematic maps and land use and land cover (LULC) maps encounter difficulties in providing a thorough assessment of canopy cover at the subpixel level and trees extending beyond officially designated forest boundaries. This limitation creates substantial gaps in our comprehension of their invaluable contributions to ecosystem services. To confront these challenges, this study presents a systematic framework integrating time-series Landsat satellite imagery and random forest-based ensemble learning techniques. This framework aims to generate China's inaugural annual tree cover dataset (CATCD) spanning from 1985 to 2023 at a 30 m spatial resolution. Evaluation against multisource reference data shown high correlations ranging from 0.70 to 0.96 and reasonable RMSE values ranging from 5.6 % to 25.2 %, highlighting the reliability and precision of our approach across different years and data collection methodologies. Our analysis reveals that China's forested area has doubled, expanding from 1.04 million km2 in 1985 to 2.10 million km2 in 2023. Notably, 33 % of this growth can be attributed to a shift from non-forest to forest land categories, primarily observed in the three-north and southwest regions. However, the majority, contributing 67 %, results primarily from crown closure in central and southern China. This realization underscores the limitations of conventional binary thematic maps and LULC maps in accurately quantifying forest gain in China. Furthermore, China's tree population structure has undergone a transformative shift from 83 % forest trees and 17 % non-forest trees in 1985 to 92 % forest trees and 8 % non-forest trees in 2023, signifying a transition from afforestation to established forests. Our study not only enhances the understanding of tree cover variations in China but also provides valuable data for ecological investigations, land management strategies, and assessments related to climate change.