A novel solution for extracting individual tree crown parameters in high-density plantation considering inter-tree growth competition using terrestrial close-range scanning and photogrammetry technology

Abstract

Automatic tree crown mapping, crown width (CW) and crown projection area (CPA) extraction are the basis for high-precision estimation of forest productivity and carbon stock. Terrestrial close-range observation (TCRO) technology, mainly including terrestrial laser scanning (TLS) and close-range photogrammetry (CRP), measures individual tree structural parameters by generating detailed three-dimensional (3D) points, making it a potential replacement for labor-intensive manual forest inventories. However, accurate extraction of crown parameters using TCRO in high-density forests remain a challenge due to different degrees of missing crown information caused by occlusion between trees and limitations of computer 3D modeling techniques and segmentation methods. Here, we propose a model for estimating crown parameters using tree spacing, diameter at breast height (DBH) and stand age, which collaboratively considers the advantages of TCRO data and the bioecological mechanisms of inter-tree competition. First, an approach to construct a tree triangulation network with tree position and tree spacing is designed based on the analysis of the bioecological mechanisms of inter-tree competition relationships. Second, a model to quantify inter-tree competition using tree spacing, DBH and stand age is developed to extract CW and CPA. We demonstrate the generality of our model to high-density forests in subtropical China with TLS data. It shows a good performance in Chinese fir, Eucalyptus and Spingbract Chinkapin-dominated plots with estimation accuracy (EA) ≥ 90.22 % and relative root mean square error (rRMSE) ≤ 0.1286 for CW and EA ≥ 84.51 % and rRMSE ≤ 0.1861 for CPA. In addition, the performance in estimating CW (EA = 89.80 %) and CPA (EA = 86.13 %) using CRP point clouds demonstrate the applicability of our model to CRP. The proposed model collaboratively considers inter-tree competition mechanism and TCRO data characteristics, therefore it is interpretable in terms of bioecological principle and universal for different forest environments (e.g., coniferous, broad-leaved and mixed coniferous species). The results show that the method provides an efficient solution for automatic and accurate measurements of the crown parameters in the forest sample plot investigation, which can support the fine forest management and carbon stock estimation.