For years, the question of how many trees exist in China remained unanswered. That changed with the release of the country’s first national tree-density map earlier this year, revealing that as of 2020, China had approximately 142.6 billion trees, equivalent to about 100 trees for every person in the country. This figure is the result of a decade-long effort by my team to "count" them.
The urgency of this endeavor stemmed from a fundamental gap in our understanding. Although China hosts the world’s largest area of planted forests, traditional forestry statistics have long focused on general metrics such as timber volume. As the principles of green development gained traction and China announced its dual-carbon goals, it became clear that a more granular, data-driven understanding …
For years, the question of how many trees exist in China remained unanswered. That changed with the release of the country’s first national tree-density map earlier this year, revealing that as of 2020, China had approximately 142.6 billion trees, equivalent to about 100 trees for every person in the country. This figure is the result of a decade-long effort by my team to "count" them.
The urgency of this endeavor stemmed from a fundamental gap in our understanding. Although China hosts the world’s largest area of planted forests, traditional forestry statistics have long focused on general metrics such as timber volume. As the principles of green development gained traction and China announced its dual-carbon goals, it became clear that a more granular, data-driven understanding of forest ecosystems was needed.
To calculate carbon storage at the tree level and assess forest contributions to biodiversity, we required a precise ecological accounting system – a "green ledger." Science-based ecological restoration, including decisions on whether to plant trees, shrubs, or grasses in a given location, depends on access to high-quality, spatially explicit data.
A secondary motivation was a deep dissatisfaction with outdated or incomplete data. Years ago, Nature published a global estimate of 3.04 trillion trees, but China’s forests were represented by sparse data. By then, my team had already spent more than three years collecting extensive information deep within China’s forests. I was convinced that China should not remain a blind spot in global forest research. If others could map trees at scale, so could we.
Yet China spans over 9.6 million square kilometers. How could we count trees across such a vast territory? The solution lay in methodological innovation and technological advancement.
Two decades ago, I watched foreign researchers climb into forest canopies to manually measure tree height – an admirable feat, but one that underscored the limitations of traditional methods. Progress in environmental surveying, I realized, depends not only on dedication but also on the continuous adoption of advanced tools. Technology is the handrail that enables us to reach new heights.
Our breakthrough came with the application of LiDAR (Light Detection and Ranging). This technology uses laser pulses to capture tree height, form, and location with exceptional accuracy. A single scan can map an entire forest stand in minutes.
We developed an integrated "sky-and-ground" observation system, similar to performing a CT scan of a forest. From above, drones equipped with LiDAR sensors emit over a million laser pulses per second. From below, team members navigate the terrain with portable scanners.
Together, these perspectives – top-down, side-view, and upward-looking – enabled us to construct high-resolution, measurable digital models of forest ecosystems. Today, the LiDAR hardware and software we developed have been adopted in more than 130 countries and regions.
Over the past 10 years, we surveyed more than 76,000 sample plots and collected over 400 terabytes of data – the equivalent of over 80 million high-resolution photographs. This unprecedented scale required constant innovation. To address challenges like uneven terrain, we created a terrain-following flight algorithm for drones. To process massive datasets, we developed an intelligent tree-segmentation algorithm capable of automatically extracting individual trees from complex forest canopies and generating the tree-density map. Step by step, we built unprecedented solutions. Scientific research rarely begins with perfect conditions. It advances when researchers create new conditions through persistent effort.
Among the many unforgettable moments was the discovery of Asia’s tallest known tree – a 102.3-meter cypress in Xizang autonomous region. After crossing the rushing Yiong Tsangpo River, we finally stood in awe beneath this towering presence. More than a tree, it felt like a living monument – a testament to nature’s resilience, wisdom, and quiet power.
Our work to refine China’s digital ecological ledger continues. By deepening our understanding of this green foundation, we aim to support more effective environmental stewardship at home and contribute valuable knowledge to the international community.
(Guo Qinghua is a Boya distinguished professor at Peking University and director of the Institute of Remote Sensing and Geographic Information Systems, Peking University School of Earth and Space Sciences. This article was compiled by People’s Daily journalist Liu Fa.)