Automated Volumetric Measurements of Truckloads through Multi-View Photogrammetry and 3D Reconstruction Software

Abstract

Since wood represents an important proportion of the delivered cost, it is important to embrace and implement correct measurement procedures and technologies that provide better wood volume estimates of logs on trucks. Poor measurements not only impact the revenue obtained by haulage contractors and forest companies but also might affect their contractual business relationship. Although laser scanning has become a mature and more affordable technology in the forestry domain, it remains expensive to adopt and implement in real-life operating conditions. In this study, multi-view Structure from Motion (SfM) photogrammetry and commercial 3D image processing software were tested as an innovative and alternative method for automated volumetric measurement of truckloads. The images were collected with a small UAV, which was flown around logging trucks transporting Eucalyptus nitens pulplogs. Photogrammetric commercial software was used to process the images and generate 3D models of each truckload. The levels of accuracy obtained with multi-view SfM photogrammetry and 3D reconstruction obtained in this study were comparable to those reported in previous studies with laser scanning systems for truckloads with similar logs and species. The deviations between the actual and predicted solid volume of logs on trucks ranged between –3.2% and 3.5%, with an average deviation of –0.05%. In absolute terms, the average deviation was only 0.5 m3 or 1.7%. Although several aspects must be addressed for the operational implementation of SfM photogrammetry, the results of this study demonstrate the great potential for this method to be used as a cost-effective tool to aid in the determination of the solid volume of logs on trucks.