Influence of Scanner Position and Plot Size on the Accuracy of Tree Detection and Diameter Estimation Using Terrestrial Laser Scanning on Forest Inventory Plots

Gollob, Christoph; Ritter, Tim; Wassermann, Clemens; Nothdurft, Arne

doi:10.3390/rs11131602

Cited by 55 publications

(63 citation statements)

References 74 publications

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“…Literature provide overall detection percentages to exceed 97% [16,17], with a slight decrease for smaller diameters. Although depended on the structure and number of scans [24], the~10% decrease is similar to our results. Height estimation remained an issue no matter the species or sample plot structure, similar to Saarinen et al [11].…”

Section: Discussionsupporting

confidence: 91%

“…There are still some factors that constrain the applicability of the technology, leading to the impossibility of gaining such results for all interest aspects (e.g., diameter, height, volume, crown area). But even so, research covering the aspect of combining point clouds from multiple positions [23] or that of pre-designing the acquisition network [24] as compensating measures. As such, for most of the intended goals, we followed and extended the previous work addressing both tree and stand level [25,26], forest type influence [27] and even terrestrial laser best practice guides [28,29].…”

Section: Introductionmentioning

confidence: 99%

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Retrieval of Forest Structural Parameters from Terrestrial Laser Scanning: A Romanian Case Study

Pascu

Dobre

Badea

et al. 2020

Forests

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Research Highlights: The present study case investigates the differences occurring when tree’s biophysical parameters are extracted through single and multiple scans. Scan sessions covered mountainous and hill regions of the Carpathian forests. Background and Objectives: We focused on analyzing stems, as a function of diameter at breast height (DBH) and the total height (H), at sample plot level for natural forests, with the purpose of assessing the potential for transitioning available methodology to field work in Romania. Materials and Methods: We performed single and multiple scans using a FARO Focus 3D X130 phase shift terrestrial laser scanner at 122kpts and 0.3:0.15 mm noise compression ratio, resulting in an average point density of 6pts at 10m. The point cloud we obtained underpinned the DBH and heights analysis. In order to reach values similar to those measured in the field, we used both the original and the segmented point clouds, postprocessed in subsamples of different radii. Results: Pearson’s correlation coefficient above 0.8 for diameters showed high correlation with the field measurements. Diameter averages displayed differences within tolerances (0.02m) for 10 out of 12 plots. Height analysis led to poorer results. For both acquisition methods, the values of the correlation coefficient peaked at 0.6. The initial hypothesis that trees positioned at a distance equivalent to their height can be measured more precise, was not valid; no increase in correlation strength was visible for either heights or diameters as the distance from scanner varied (r = 0.52). Conclusions: With regard to tree biophysical parameters extraction, the acquisition method has no major influence upon visible trees. We emphasize the term “visible”, as an increase in the number of acquisitions led to an increased number of detected trees (16% in old stands and 29% in young stands).

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Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Retrieval of Forest Structural Parameters from Terrestrial Laser Scanning: A Romanian Case Study

Pascu

Dobre

Badea

et al. 2020

Forests

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“…Occlusion decreases the capacity of a point cloud to properly digitize trees or forest stands [43]. Use of a multi-scan approach in TLS data acquisition decreases point cloud occlusion, thus improving the performance of a TLS-based method to characterize forest stands, especially the ones with a complex structure [22,44,45]. On a forest stand, occlusion affects the performance of a TLS-based method on both horizontal and vertical dimensions.…”

Section: Discussionmentioning

confidence: 99%

Structural Changes in Boreal Forests Can Be Quantified Using Terrestrial Laser Scanning

et al. 2020

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Terrestrial laser scanning (TLS) has been adopted as a feasible technique to digitize trees and forest stands, providing accurate information on tree and forest structural attributes. However, there is limited understanding on how a variety of forest structural changes can be quantified using TLS in boreal forest conditions. In this study, we assessed the accuracy and feasibility of TLS in quantifying changes in the structure of boreal forests. We collected TLS data and field reference from 37 sample plots in 2014 (T1) and 2019 (T2). Tree stems typically have planar, vertical, and cylindrical characteristics in a point cloud, and thus we applied surface normal filtering, point cloud clustering, and RANSAC-cylinder filtering to identify these geometries and to characterize trees and forest stands at both time points. The results strengthened the existing knowledge that TLS has the capacity to characterize trees and forest stands in space and showed that TLS could characterize structural changes in time in boreal forest conditions. Root-mean-square-errors (RMSEs) in the estimates for changes in the tree attributes were 0.99–1.22 cm for diameter at breast height (Δdbh), 44.14–55.49 cm2 for basal area (Δg), and 1.91–4.85 m for tree height (Δh). In general, tree attributes were estimated more accurately for Scots pine trees, followed by Norway spruce and broadleaved trees. At the forest stand level, an RMSE of 0.60–1.13 cm was recorded for changes in basal area-weighted mean diameter (ΔDg), 0.81–2.26 m for changes in basal area-weighted mean height (ΔHg), 1.40–2.34 m2/ha for changes in mean basal area (ΔG), and 74–193 n/ha for changes in the number of trees per hectare (ΔTPH). The plot-level accuracy was higher in Scots pine-dominated sample plots than in Norway spruce-dominated and mixed-species sample plots. TLS-derived tree and forest structural attributes at time points T1 and T2 differed significantly from each other (p < 0.05). If there was an increase or decrease in dbh, g, h, height of the crown base, crown ratio, Dg, Hg, or G recorded in the field, a similar outcome was achieved by using TLS. Our results provided new information on the feasibility of TLS for the purposes of forest ecosystem growth monitoring.

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“…Occlusion decreases the capacity of a point cloud to properly digitize trees or forest stands [42]. Use of a multi-scan approach in TLS data acquisition decreases point cloud occlusion, thus improving the performance of a TLS-based method to characterize forest stands, especially the ones with a complex structure [43][44][45]. On a forest stand, occlusion affects the performance of a TLS-based method on both horizontal and vertical dimensions.…”

Section: Discussionmentioning

confidence: 99%

Structural Changes in Boreal Forests Can Be Quantified Using Terrestrial Laser Scanning

Yrttimaa¹,

Luoma²,

Saarinen³

et al. 2020

Preprint

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Terrestrial laser scanning (TLS) has been adopted as a feasible technique to digitize trees and forest stands, providing accurate information on tree and forest structural attributes. However, there is limited understanding on how a variety of forest structural changes can be quantified using TLS in boreal forest conditions. In this study, we assessed the accuracy and feasibility of TLS in quantifying changes in the structure of boreal forests. We collected TLS data and field reference from 37 sample plots in 2014 (T1) and 2019 (T2). Tree stems typically have planar, vertical, and cylindrical characteristics in a point cloud, and thus we applied surface normal filtering, point cloud clustering, and RANSAC-cylinder filtering to identify these geometries and to characterize trees and forest stands at both time points. The results strengthened the existing knowledge that TLS has the capacity to characterize trees and forest stands in space and showed that TLS could characterize structural changes in time in boreal forest conditions. Root-mean-square-errors (RMSEs) in the estimates for changes in the tree attributes were 0.99-1.22 cm for diameter at breast height (Δdbh), 44.14-55.49 cm2 for basal area (Δg), and 1.91-4.85 m for tree height (Δh). In general, tree attributes were estimated more accurately for Scots pine trees, followed by Norway spruce and broadleaved trees. At the forest stand level, an RMSE of 0.60-1.13 cm was recorded for changes in basal area-weighted mean diameter (ΔDg), 0.81-2.26 m for changes in basal area-weighted mean height (ΔHg), 1.40-2.34 m2/ha for changes in mean basal area (ΔG), and 74-193 n/ha for changes in the number of trees per hectare (ΔTPH). The plot-level accuracy was higher in Scots pine-dominated sample plots than in Norway spruce-dominated and mixed-species sample plots. TLS-derived tree and forest structural attributes at time points T1 and T2 differed significantly from each other (p < 0.05). If there was an increase or decrease in dbh, g, h, height of the crown base, crown ratio, Dg, Hg, or G recorded in the field, a similar outcome was achieved by using TLS. Our results provided new information on the feasibility of TLS for the purposes of forest ecosystem growth monitoring.

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Influence of Scanner Position and Plot Size on the Accuracy of Tree Detection and Diameter Estimation Using Terrestrial Laser Scanning on Forest Inventory Plots

Cited by 55 publications

References 74 publications

Retrieval of Forest Structural Parameters from Terrestrial Laser Scanning: A Romanian Case Study

Retrieval of Forest Structural Parameters from Terrestrial Laser Scanning: A Romanian Case Study

Structural Changes in Boreal Forests Can Be Quantified Using Terrestrial Laser Scanning

Structural Changes in Boreal Forests Can Be Quantified Using Terrestrial Laser Scanning

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