International benchmarking of terrestrial laser scanning approaches for forest inventories

Liang, Xinlian; Hyyppä, Juha; Kaartinen, Harri; Lehtomäki, Matti; Pyörälä, Jiri; Pfeifer, Norbert; Holopainen, Markus; Brolly, Gábor; Pirotti, Francesco; Trochta, Jan; Wang, Jinhu; Jo, Hyunwoo; Katoh, Masato; Liu, Luxia; Mokroš, Martin; Morel, Jules; Olofsson, Kenneth; Lopez, Jose Alejandro Poveda; Saarinen, Ninni; Wang, Jinhu; Xi, Zhouxi; Zheng, Guang; Kankare, Ville; Luoma, Ville; Yu, Xiaowei; Chen, Liang; Vastaranta, Mikko; Hackenberg, Jan

doi:10.1016/j.isprsjprs.2018.06.021

Cited by 327 publications

(357 citation statements)

References 52 publications

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“…Type II error, or commission, is the number of trees falsely extracted [36]. In accordance with the TLS benchmarking project [49], the accuracy of tree extraction was assessed by the completeness, correctness, and mean accuracy of detection. The completeness is defined by the percentage of the extracted trees in the field.…”

Section: Evaluation Methodsmentioning

confidence: 99%

Improved 3D Stem Mapping Method and Elliptic Hypothesis-Based DBH Estimation from Terrestrial Laser Scanning Data

Qian

Tang

et al. 2020

Remote Sensing

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The detailed structure information under the forest canopy is important for forestry surveying. As a high-precision environmental sensing and measurement method, terrestrial laser scanning (TLS) is widely used in high-precision forestry surveying. In TLS-based forestry surveys, stem-mapping, which is focused on detecting and extracting trunks, is one of the core data processing tasks and the basis for the subsequent calculation of tree attributes; one of the most basic attributes is the diameter at breast height (DBH). This article explores and improves the methods for stem mapping and DBH estimation from TLS data. Firstly, an improved 3D stem mapping algorithm considering the growth direction in random sample consistency (RANSAC) cylinder fitting is proposed to extract and fit the individual tree point cloud section. It constructs the hierarchical optimum cylinder of the trunk and introduces the growth direction into the establishment of the backbone buffer in the next layer. Experimental results show that it can effectively remove most of the branches and reduce the interference of the branches to the discrimination of trunks and improve the integrity of stem extraction by about 36%. Secondly, a robust least squares ellipse fitting method based on the elliptic hypothesis is proposed for DBH estimation. Experimental results show that the DBH estimation accuracy of the proposed estimation method is improved compared with other methods. The mean root mean squared error (RMSE) of the proposed estimation method is 1.14 cm, compared with other methods with a mean RMSE of 1.70, 2.03, and 2.14 cm. The mean relative accuracy of the proposed estimation method is 95.2%, compared with other methods with a mean relative accuracy of 92.9%, 91.9%, and 90.9%.

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Section: Evaluation Methodsmentioning

confidence: 99%

Improved 3D Stem Mapping Method and Elliptic Hypothesis-Based DBH Estimation from Terrestrial Laser Scanning Data

Qian

Tang

et al. 2020

Remote Sensing

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“…At the sample plot level, TLS point clouds were co-registered with a mean distance error of 2.9 mm and standard deviation 1.2 mm, mean horizontal error was 1.3 mm (standard deviation 0.4 mm) and mean vertical error 2.3 mm (standard deviation 1.2 mm) (Saarinen et al 2020) indicating high geometric accuracy of the point clouds. When similarly collected point clouds have been used to automatically measure tree diameters at multiple heights along a stem, root mean square error less than 1 cm can be expected in boreal forest conditions (Liang et al 2018).…”

Section: Technical Validationmentioning

confidence: 99%

Detailed point cloud data on stem size and shape of Scots pine trees

Saarinen

Kankare

Yrttimaa

et al. 2020

Preprint

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Quantitative assessment of the effects of forest management on tree size and shape has been challenging as there has been a lack of methodologies for characterizing differences and possible changes comprehensively in space and time. Terrestrial laser scanning (TLS) and photogrammetric point clouds provide three-dimensional (3D) information on tree stem reconstructions required for characterizing differences between stem shapes and growth allocation. This data set includes 3D reconstructions of stems of Scots pine (Pinus sylvestris L.) trees from sample plots with different thinning treatments. The thinning treatments include two intensities of thinning, three thinning types as well as control (i.e. no thinning treatment since the establishment). The data set can be used in developing point clouds processing algorithms for single tree stem reconstruction and for investigating variation in stem size and shape of Scots pine trees. Additionally, it offers possibilities in characterizing the effects of various thinning treatments on stem size and shape of Scots pine trees from boreal forests. Data set: Zenodo https://zenodo.org/record/3701271 Data set license: Attribution 4.0 International (CC BY 4.0)

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“…Through the use of a focused short‐wavelength laser pulse, TLS has a strong capability to penetrate forest canopy and collect high‐fidelity three‐dimensional data of trees in the form of point cloud (Calders et al, ). Numerous studies have proven that TLS is an objective, accurate, and efficient method to extract trunk traits (e.g., tree height and DBH) (Calders et al, ; Li et al, ; Liang et al, ; Liang et al, ; Luo et al, ; Vicari et al, ; Wang et al, ). With the assistance of individual tree segmentation and stem‐leaf segmentation algorithms, detailed crown architecture traits are also becoming possible to acquire in a repeatable and accurate way (Disney, ; Jin, Su, Gao, et al, ; Jin, Su, Wu, et al, ; Li et al, ; Li et al, ; Moorthy et al, ; Tao, Guo, et al, ; Tao, Wu, et al, ), which provides a new tool to observe changes in tree architecture.…”

Section: Introductionmentioning

confidence: 99%

Large‐Scale Geographical Variations and Climatic Controls on Crown Architecture Traits

Wang

et al. 2020

JGR Biogeosciences

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Crown architecture is a critical component for a tree to interact with the ambient environment and to compete with neighbors. However, little is known regarding how climate variability may shape crown architecture traits across large geographical extents and whether crown architecture traits have coordinated variations with trunk and leaf traits to climate gradients. Here we used Quercus mongolica trees as an example, used the cutting‐edge terrestrial laser scanning technique to accurately characterize their crown architecture traits, and explored their variabilities along with environmental variability across large climate gradients in northern China. Our results showed that there are significant spatial variations in trunk, crown, and leaf traits even for the same genetic group across large environmental gradients. Tree height and leaf size had tight covariations with precipitation (|R|> 0.8, p < 0.01). We also observed coordinated variations among crown architecture traits related to canopy shape (e.g., primary branch insertion angle, chord length ratio), trunk traits (e.g., tree height), leaf traits (e.g., specific leaf area), and climate variability, highlighting there are likely fundamental evolutionary strategies regulating these covariations. With a projected drier and hotter climate scenario in this region, our results further suggest trees are expected to transit from a “tree shape” to a “shrub shape,” with large ecological and ecophysiological impacts on this region.

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International benchmarking of terrestrial laser scanning approaches for forest inventories

Cited by 327 publications

References 52 publications

Improved 3D Stem Mapping Method and Elliptic Hypothesis-Based DBH Estimation from Terrestrial Laser Scanning Data

Improved 3D Stem Mapping Method and Elliptic Hypothesis-Based DBH Estimation from Terrestrial Laser Scanning Data

Detailed point cloud data on stem size and shape of Scots pine trees

Large‐Scale Geographical Variations and Climatic Controls on Crown Architecture Traits

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