Low-cost drone photogrammetry maps tree growth with 5mm accuracy

A research team led by Stephan Nebiker has demonstrated that low-cost consumer drones weighing under 250 grams can reconstruct entire deciduous trees in 3D with 5-6mm point accuracy. The study, accepted at the ISPRS Congress 2026, addresses the long-neglected need to monitor primary tree growth (shoot elongation) — a critical indicator of how forests respond to climate change. Current methods focus on radial growth via dendrometers, but shoot elongation remains poorly understood due to a lack of scalable measurement techniques. The team deployed both off-the-shelf UAVs and a custom multi-camera CraneCam system over a full growing season in two study areas, achieving reconstruction completeness between 92% and 98% depending on the drone type.

The paper introduces a novel 3D-printed ground-truth branch to evaluate the system's ability to capture fine-detail structures like thin shoots. Results show that photogrammetric point clouds from these low-cost platforms can reliably capture tree canopy architecture, enabling precise measurement of shoot elongation across entire trees. The work also explores skeletonization of trees from point clouds, offering a pathway to automated growth monitoring. By making high-precision 3D tree reconstruction accessible with sub-$500 drones, this research opens up large-scale, continuous monitoring of primary growth — data that could significantly improve climate models predicting forest carbon sequestration and drought response.