In Japan, the forest covers 69% of the land; the trees have been planted all over the country after WWⅡ. About half of the trees are over 50 years old and now ready to get harvested. However, there is a severe shortage of laborers in the forestry industry due to hard-working conditions, aging population, and lower birthrate. The average age of workers reached 70 years old, and the forest industry's sustainability faces a big crisis. In recent years, therefore, smart forestry—IoT and ICT technology for forestry sector—is introduced to be a good alternative to human labor.

When the trees are harvested, and the logs are distributed for production, the amount of labor cost and income from timber sales need to be estimated beforehand. For the estimations, it is essential to measure the size of trees accurately, including the number, height, and diameter of the trees. However, lowering the cost of high accuracy of manual measurement is a big challenge. An inexpensive, simple, accurate, and efficient method is required to measure forest over a large area.

Here, the development of drone measurement technology becomes a crucial application for smart forestry. The introduction of drones saves over 80% of labor costs and doubles the timber sale. It makes a significant impact on the sustainability of the forestry industry.

In our lab, we have been developing techniques using a laser to capture the 3D structure of trees. We have established a world-leading technique to analyze 3D data obtained from the laser within 5% of measurement errors. The 5% error was achieved by a unique neural network technique. We have also established a method to analyze multi-temporal 3D data automatically. We are working on an automatic time-series analysis of 3D data, which is needed for a higher frequency of 3D data acquisition near the future.
Figure 1: The wrapping method for 3D data obtained from lasers to capture the complexity of tree form. See also Kato et al., (2009).
Moreover, we are developing software to expand the role of drones in our society through our international research collaboration with a company making UAV lasers. For example, we support the forest industry to detect a small change of tree growth using high precision measurement technology with low measurement errors.

The functionality of current drones has been dramatically improved, and the flight has been stabilized. The demand from agriculture and forestry fields should be reflected in drone development. We work closely with engineers who can make drones and keep developing technology suitable for forest survey. With our creative mind, our drone's future application is under development for the next 30 years.

  • Capturing Tree Crown Formation through Implicit Surface Reconstruction using AirborneLidar Data, Kato, A., Moskal, L.M., Schiess, P., Swanson, M.E., Calhoun, D., and Stuetzle, W.,Remote Sensing of Environment113, pp. 1148-1162, 2009
    DOI: 10.1016/j.rse.2009.02.010
Akira Kato
Received a Ph.D. from School of Forest Resources, University of Washington in 2008. Since then, has been a faculty at the Graduate School of Horticulture of Chiba University. Specializes in understanding plant and tree structure using high-resolution 3D lasers. He also applies 3D data for natural disasters (e.g. forest fires) to study ecological processes and understand the adaptation of nature for the disaster.