In a significant advancement for forest management, researchers at Kyoto University have harnessed drone technology to enhance the assessment of tree biomass across a range of forest types in Japan. This innovative approach addresses the challenges associated with traditional ground-based tree surveys, which are often labor-intensive and less effective in remote or rugged areas.
Forests have long played a crucial role in supporting human health and well-being, serving as major carbon sinks while providing essential ecosystem services such as timber, recreational opportunities, and climate regulation. Accurately measuring forest biomass is vital for understanding carbon storage and promoting sustainable management practices. However, studying these vast three-dimensional structures has proven difficult, particularly when it comes to measuring the height and canopy size of trees.
To overcome these obstacles, the research team employed LiDAR, or Light Detection and Ranging, a technology that emits millions of laser beams per second to capture three-dimensional data of scanned objects. This enabled a large-scale survey of 4,326 canopy trees from 149 different species across 23 forest census plots, ranging from the sub-boreal forests of Hokkaido to the subtropical woodlands of Okinawa.
The researchers combined drone-derived data with meticulous ground-based measurements, creating species-specific equations for estimating tree biomass based on crown structural traits. “To our knowledge, this represents the most comprehensive study to date estimating biomass for such a large number of tree species using drone-based data,” stated first author Kyaw Kyaw Htoo.
Findings indicated that a model utilizing only tree height and crown area could explain 72% of the variability in biomass, while factoring in functional types such as conifers and broadleaf trees improved this to 79%. The accuracy further increased to 83% when species-specific information was included. Team leader Yusuke Onoda noted, “Though drones cannot directly capture understory trees, our study found that canopy trees account for about 75% on average of total forest biomass across diverse forest types.”
This research lays the groundwork for better estimating total forest biomass, including understory components. The methodology not only enables more precise biomass assessments in species-rich natural forests but also offers a scalable, data-driven tool for ongoing forest monitoring. The potential implications extend to enhancing the accuracy of carbon credits and biodiversity assessments. Htoo emphasized, “By making good use of these tools, we aim to enhance the efficiency of forest resource assessment and hope to contribute not only to scientific progress but also to biodiversity conservation and to promoting sustainable forestry.”
