Abstract

The forest plots survey's primary measurement factors are the diameter at breast height (DBH), tree height, and the individual tree volume. The reconstruction of a 3D forest scene based on dense images can contribute to the automatic extraction of individual tree parameters. Close-range photogrammetry (CRP) can achieve the reconstruction of a 3D scene from the sequence images at a highly efficient and low cost. However, the reconstructed point clouds often miss the trees' upper part, resulting in the tree height and volume not being measured directly. This paper proposes an integrating extraction framework and methods of the DBH, tree height, and individual tree volume for achieving automatic measurement of the individual tree parameters with high accuracy based on CRP. Four plantation plots in Wangyedian Forest Farm, Inner Mongolia, and Gaofeng Forest Farm, Guangxi Zhuang, are selected to obtain sequence close-up photographs and construct 3D scenes. The DBH, tree height, and trunk volume of the individual tree are extracted using circle fitting, stem curve fitting, growth equation, and segmentation measurement. The extracted individual tree parameters from Terrestrial laser scanning (TLS) are used as validation data to evaluate the accuracy. It shows a good performance in two Larix gmelinii plots, one Pinus tabulaeformis plot, and one Eucalyptus grandis plot with the accuracy of extracted DBH above 90%, which is 90.18%, 96.54%, 90.17%, and 95.00%, respectively. The accuracy of extracted tree height of the four plots is all above 85%, which is 93.34%, 91.71%, 90.32%, and 85.96%, respectively, and the accuracy of trunk volume is 91.55%, 91.94%, 89.86%, and 89.6%, respectively. The results show that our proposed integrated parameter extraction frame and methods can achieve high accuracy economically, efficiently, and conveniently, and be used for automatic measurements of individual tree factors in forest plot surveys.

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