Abstract
Terrestrial laser scanners provide accurate and detailed point clouds of forest plots, which can be used as an alternative to destructive measurements during forest inventories. Various specialized algorithms have been developed to provide automatic and objective estimates of forest attributes from point clouds. The STEP (Snakes for Tuboid Extraction from Point cloud) algorithm was developed to estimate both stem diameter at breast height and stem diameters along the bole length. Here, we evaluate the accuracy of this algorithm and compare its performance with two other state-of-the-art algorithms that were designed for the same purpose (i.e., the CompuTree and SimpleTree algorithms). We tested each algorithm against point clouds that incorporated various degrees of noise and occlusion. We applied these algorithms to three contrasting test sites: (1) simulated scenes of coniferous stands in Newfoundland (Canada), (2) test sites of deciduous stands in Phalsbourg (France), and (3) coniferous plantations in Quebec, Canada. In most cases, the STEP algorithm predicted diameter at breast height with higher R2 and lower RMSE than the other two algorithms. The STEP algorithm also achieved greater accuracy when estimating stem diameter in occluded and noisy point clouds, with mean errors in the range of 1.1 cm to 2.28 cm. The CompuTree and SimpleTree algorithms respectively produced errors in the range of 2.62 cm to 6.1 cm and 1.03 cm to 3.34 cm, respectively. Unlike CompuTree or SimpleTree, the STEP algorithm was not able to estimate trunk diameter in the uppermost portions of the trees. Our results show that the STEP algorithm is more adapted to extract DBH and stem diameter automatically from occluded and noisy point clouds. Our study also highlights that SimpleTree and CompuTree require data filtering and results corrections. Conversely, none of these procedures were applied for the implementation of the STEP algorithm.
Highlights
Long-term preservation of forest resources can only be achieved through accurate forest monitoring and reliable forest inventories, which are accomplished using precise measuring methods
In an attempt to overcome the limitations of terrestrial laser scanners (TLS), we developed a new algorithm that is based upon a Hough transform (HT) variant called STEP (Snake for Tuboid Extraction from Point cloud) [54]
We validated the STEP algorithm with a large set of trees that were extracted from TLS acquisitions in forest environments under various conditions
Summary
Long-term preservation of forest resources can only be achieved through accurate forest monitoring and reliable forest inventories, which are accomplished using precise measuring methods. Forests 2019, 10, 599 measurement of key forest attributes contributes to our understanding of complex ecological processes. Among these attributes, diameter at breast height (DBH, diameter of the trunk at 1.30 m above the ground-surface) and stem diameter as a function of height are of particular importance for forest inventories. DBH measurement has become an essential part of a forester’s practice and is a reference variable for the development of allometric models. These models tie DBH to many useful structural variables, especially tree height [1], merchantable or total wood volume [2], biomass [3], and total leaf area [4]. The operator’s visual estimates of the measurement leads to potential errors [5,6,7]
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