Methodology for measuring dendrometric parameters in a mediterranean forest with UAVs flying inside forest

Abstract

Accurate field measurements of tree morphological features are essential for effective forest inventory and the sustainable management of forest resources. Traditional methods involve time-consuming and expensive tree-by-tree measurements conducted by specialized technicians, which can lead to subjective measurement errors. To address these limitations, advanced sensor technologies have garnered attention in recent years. Terrestrial laser scanning (TLS) has been widely employed due to its high precision in deriving tree attributes at the plot level. However, TLS has certain drawbacks, including high acquisition costs, limited portability, and the requirement for specialized software and expertise. As alternatives, aerial photogrammetry and computer vision algorithms have emerged to obtain high-resolution 3D measurements of forest vegetation.This study proposes a novel approach utilizing a small drone under the forest canopy to estimate biometric parameters such as trunk diameter at various heights and circumference. By joining the capabilities of drones with the structure-from-motion approach, this study presents a promising solution for cost-effective and accurate estimation of biometric parameters in forest inventories. Moreover, the results demonstrate superior accuracy compared to those reported in previous studies with improvements up to one order of magnitude.