Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 685-688, 2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
23 Jun 2016
M. Karpina, M. Jarząbek-Rychard, P. Tymków, and A. Borkowski Institute of Geodesy and Geoinformatics, Wroclaw University of Environmental and Life Science, Poland
Keywords: UAV, point cloud, biomass estimation, tree height Abstract. Manual in-situ measurements of geometric tree parameters for the biomass volume estimation are time-consuming and economically non-effective. Photogrammetric techniques can be deployed in order to automate the measurement procedure. The purpose of the presented work is an automatic tree growth estimation based on Unmanned Aircraft Vehicle (UAV) imagery. The experiment was conducted in an agriculture test field with scots pine canopies. The data was collected using a Leica Aibotix X6V2 platform equipped with a Nikon D800 camera. Reference geometric parameters of selected sample plants were measured manually each week. In situ measurements were correlated with the UAV data acquisition. The correlation aimed at the investigation of optimal conditions for a flight and parameter settings for image acquisition. The collected images are processed in a state of the art tool resulting in a generation of dense 3D point clouds. The algorithm is developed in order to estimate geometric tree parameters from 3D points. Stem positions and tree tops are identified automatically in a cross section, followed by the calculation of tree heights. The automatically derived height values are compared to the reference measurements performed manually. The comparison allows for the evaluation of automatic growth estimation process. The accuracy achieved using UAV photogrammetry for tree heights estimation is about 5cm.
Conference paper (PDF, 1264 KB)

Citation: Karpina, M., Jarząbek-Rychard, M., Tymków, P., and Borkowski, A.: UAV-BASED AUTOMATIC TREE GROWTH MEASUREMENT FOR BIOMASS ESTIMATION, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 685-688,, 2016.

BibTeX EndNote Reference Manager XML