image: a Spatial pattern of tree numbers within a 0.01° grid. b Latitudinal distribution of tree density and total tree numbers, with shaded areas indicating the standard deviation of the estimated tree numbers. c-f Distribution characteristics of tree density and numbers at different scales: c Vegetation zones, d Geographic regions, e Basin regions, f Provincial level. The error bar in c-f is the standard deviation of the estimated tree numbers.
Credit: ©Science China Press
A groundbreaking study, recently published in Science Bulletin, has generated the tree density map of China, provided the update estimate of tree numbers across China. This study is led by the research group of Professor Qinghua Guo (Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University). To create this comprehensive tree density map, the research team collected more than 400TB of UAV LiDAR data, which included over 76,000 forest plots, covering a wide range of forest ecosystems across China. By integrating high-resolution remote sensing data with geographic features such as climate, soil, and terrain, and utilizing machine learning algorithms, the team was able to estimate tree density distributions with remarkable accuracy.
The map revealed that, as of 2020, China's average tree density was ~689 trees per hectare, with a total of ~142.6 billion trees—equivalent to ~100 trees per person—with significant spatial variation. For example, at the vegetation zone scale, the cold temperate coniferous forest zone, with an average tree density of ~720 trees per hectare, contributes over 60% of China's total tree count (~ 87.9 billion trees). At the provincial level, Sichuan, Heilongjiang, Yunnan, and Guangxi each have more than 1 billion trees, accounting for 32% of the national total. Regarding per capita tree count, Tibet stands out with ~1,982 trees per person, far exceeding other regions. This comprehensive dataset offers a fresh, detailed look at the state of China’s forests, which is critical for guiding future conservation efforts.
The study’s findings also highlight the importance of precision in future forest management. By utilizing this dataset, scientists and policymakers can now more effectively plan afforestation efforts, optimize tree planting strategies, and ensure that future conservation initiatives are both effective and sustainable. This research directly supports China’s ongoing efforts to plant and restore 70 billion trees over the next decade, providing a scientific foundation for these ambitious environmental goals.
This innovative approach, combining cutting-edge UAV LiDAR technology with AI, represents a significant leap forward in forest monitoring and management. By moving beyond traditional ground-based sampling, which is time-consuming and limited in scale, the study opens up new possibilities for large-scale forest assessments, carbon sink evaluations, and ecosystem restoration projects globally.
See the article:
How many trees are there in China? Science Bulletin, 2025, 70, doi: 10.1016/j.scib.2025.02.001
Journal
Science Bulletin