Taiwan Uses LiDAR to Monitor Roadside Trees, Replacing Manual Estimates

Taiwan's Forestry Research Institute (FRI) is revolutionizing roadside tree management by employing vehicle-mounted LiDAR technology to monitor growth indicators along the Pingtung highway. This initiative is part of the "Planting 100 Miles" 2.0 project, aimed at enhancing the ecological benefits and greening outcomes of the roadway.

The FRI has confirmed that this advanced monitoring method offers superior accuracy and dramatically boosts the efficiency of traditional manual surveys. The institute plans to expand its research this year, selecting specific road sections and tree species for a 14-kilometer survey to establish a comprehensive growth database.

The Pingtung highway serves as a primary route to the Kenting National Park. The government's "Planting 100 Miles" project seeks to create a dynamic green landscape along this route. To scientifically track the growth metrics of roadside trees, the FRI previously evaluated various sensing technologies, including drone-based LiDAR, handheld LiDAR, and vehicle-mounted LiDAR. Their assessment concluded that vehicle-mounted LiDAR is best suited for large-scale survey tasks.

Research findings indicate that the technology's measurements for diameter at breast height and tree height align closely with on-site survey results, meeting research accuracy requirements. It can precisely reconstruct the 3D spatial structure of trees. Compared to traditional manual surveys, vehicle-mounted LiDAR not only significantly enhances efficiency but also eliminates the risks associated with personnel conducting field surveys on public roads. Furthermore, it provides high-quality, quantifiable foundational information for subsequent scientific research.

This year, the FRI will further expand its efforts by creating digital files for roadside trees along a 14-kilometer stretch. Using point cloud technology, they will accurately calculate growth indicators such as diameter at breast height, tree height, and crown width. This data will be integrated into a spatial database for monitoring tree growth, serving as a basis for analyzing cross-year scanning data. This will enable precise tracking of tree growth rates and biomass increments in the Pingtung environment, ultimately estimating overall carbon sequestration benefits and dynamic changes.