Assessment of tree structure using a 3D image analysis technique—A proof of concept

Efforts to improve the efficiency and efficacy of tree structure and crown architecture measurement are necessary to reduce error associated with indirect estimation of volume, which affects biophysical and ecosystem modelling, as well as resource assessment. In this short communication, we test the potential for a commercial SfM-MVS (Structure from Motion coupled with Multiple-View Stereophotogrammetry) software package, Photoscan-Professional, to accurately determine tree height, stem diameter, and eventually volume. SfM is a technique in computer vision, which calculates the 3D position of objects in a scene from a series of photographs. It uses a technique assuming that an object in a 3D scene is located on a vector between the image of the object in the camera and the object itself. The technique allows the construction of a 3D pointcloud, such as the one produced by laser technologies – terrestrial or airborne LiDAR. SfM requires no camera calibration or control points to construct an initial model. Moreover, it is a low-cost alternative to laser technologies. The second part of our method – MVS – is a visualization technique that reconstructs a 3D textured mesh of the scene from the SfM-derived pointcloud and RGB photographs. As a proof of concept, our methods were limited to two scenarios: (1) a single potted tree in a lab environment, where exact measurements could be made, and (2) two trees of different species and size in natural environments to test feasibility outside the laboratory. Precise measurements of tree height and stem diameter were compared with estimates obtained from the 3D model created using SfM-MVS. The results indicate that the SfM method is a promising – and inexpensive – alternative to terrestrial LiDAR and 3D scanners. Tree height estimates had error of 2.59%, while stem diameter estimates had error of 3.7%. The MVS algorithm used in this study was developed for plan surfaces such as topography or ‘compact’ objects and does not provide a representative 3D mesh for slender trees, although it works well for large stems. The authors link this disparity to the complex branching structure of trees.Future work requires (1) the development of effective automated volume reconstruction software specific to trees, and (2) the validation of the wide-scale applicability of the technology, which must include trees of various size, species, and growth forms. Moreover, future testing must include more complex environments, such as heterogeneous urban sites or closed-canopy forest sites where the proximity of other features may limit the utility of the new technology.