Mapping tree health in 3D: innovations in sensor position measurement for acoustic tomography using 3D scanner

Abstract

Acoustic computed tomography plays an important role in assessing the health and structural integrity of trees, and has applications in forestry management and environmental conservation. Traditionally, the precise measurement of sensor distances within tree trunks using manual methods, such as rulers, has been the standard practice. In this study, a novel approach utilizing 3D scan technology to measure sensor distances within tree trunks was introduced, offering a comparative assessment of its advantages over traditional methods. A schematic representation of sensor distance measurement using both a ruler and a 3D scanner, revealing differences in measurement lengths, is presented. Additionally, the methodology for determining sensor positions via 3D scanning is detailed, including the use of markers and precise distance measurements. The results demonstrate that a 3D scan yields sensor positions that closely approximate those obtained via traditional ruler measurements. Comparative analyses reveal nearly identical maps of velocity rays and minimal relative errors, reinforcing the reliability of the 3D scanning technique. These findings further support the use of 3D scanning as a viable alternative for sensor position measurement in the acoustic tomography of tree samples.