Browsing by Subject "DIAMETER ESTIMATION"

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  • Pyorala, Jiri; Kankare, Ville; Liang, Xinlian; Saarinen, Ninni; Rikala, Juha; Kivinen, Veli-Pekka; Sipi, Marketta; Holopainen, Markus; Hyyppa, Juha; Vastaranta, Mikko (2019)
    Wood procurement in sawmills could be improved by resolving detailed three-dimensional stem geometry references from standing timber. This could be achieved, using the increasingly available terrestrial point clouds from various sources. Here, we collected terrestrial laser-scanning (TLS) data from 52 Scots pines (Pinus sylvestris L.) with the purpose of evaluating the accuracy of the log geometry and analysing its relationship with wood quality. For reference, the log-specific top-end diameter, volume, tapering, sweep, basic density and knottiness were measured in a sawmill. We produced stem models from the TLS data and bucked them into logs similar to those measured in the sawmill. In comparison to the sawmill data, the log-specific TLS-based top-end diameter, volume, taper and sweep estimates showed relative mean differences of 1.6, -2.4, -3.0 and 78 per cent, respectively. The correlation coefficients between increasing taper and decreasing wood density and whorl-to-whorl distances were 0.49 and -0.51, respectively. Although the stem-model geometry was resolved from the point clouds with similar accuracy to that at the sawmills, the remaining uncertainty in defining the sweep and linking the wood quality with stem geometry may currently limit the method's feasibilities. Instead of static TLS, mobile platforms would likely be more suitable for operational point cloud data acquisition.
  • Yrttimaa, Tuomas; Saarinen, Ninni; Luoma, Ville; Tanhuanpaa, Topi; Kankare, Ville; Liang, Xinlian; Hyyppa, Juha; Holopainen, Markus; Vastaranta, Mikko (2019)
    Dead wood is a key forest structural component for maintaining biodiversity and storing carbon. Despite its important role in a forest ecosystem, quantifying dead wood alongside standing trees has often neglected when investigating the feasibility of terrestrial laser scanning (TLS) in forest inventories. The objective of this study was therefore to develop an automatic method for detecting and characterizing downed dead wood with a diameter exceeding 5 cm using multi-scan TLS data. The developed four-stage algorithm included (1) RANSAC-cylinder filtering, (2) point cloud rasterization, (3) raster image segmentation, and (4) dead wood trunk positioning. For each detected trunk, geometry-related quality attributes such as dimensions and volume were automatically determined from the point cloud. For method development and validation, reference data were collected from 20 sample plots representing diverse southern boreal forest conditions. Using the developed method, the downed dead wood trunks were detected with an overall completeness of 33% and correctness of 76%. Up to 92% of the downed dead wood volume were detected at plot level with mean value of 68%. We were able to improve the detection accuracy of individual trunks with visual interpretation of the point cloud, in which case the overall completeness was increased to 72% with mean proportion of detected dead wood volume of 83%. Downed dead wood volume was automatically estimated with an RMSE of 15.0 m(3)/ha (59.3%), which was reduced to 6.4 m(3)/ha (25.3%) as visual interpretation was utilized to aid the trunk detection. The reliability of TLS-based dead wood mapping was found to increase as the dimensions of dead wood trunks increased. Dense vegetation caused occlusion and reduced the trunk detection accuracy. Therefore, when collecting the data, attention must be paid to the point cloud quality. Nevertheless, the results of this study strengthen the feasibility of TLS-based approaches in mapping biodiversity indicators by demonstrating an improved performance in quantifying ecologically most valuable downed dead wood in diverse forest conditions.
  • Luoma, Ville; Saarinen, Ninni; Kankare, Ville; Tanhuanpaa, Topi; Kaartinen, Harri; Kukko, Antero; Holopainen, Markus; Hyyppa, Juha; Vastaranta, Mikko (2019)
    Exact knowledge over tree growth is valuable information for decision makers when considering the purposes of sustainable forest management and planning or optimizing the use of timber, for example. Terrestrial laser scanning (TLS) can be used for measuring tree and forest attributes in very high detail. The study aims at characterizing changes in individual tree attributes (e.g., stem volume growth and taper) during a nine year-long study period in boreal forest conditions. TLS-based three-dimensional (3D) point cloud data were used for identifying and quantifying these changes. The results showed that observing changes in stem volume was possible from TLS point cloud data collected at two different time points. The average volume growth of sample trees was 0.226 m(3) during the study period, and the mean relative change in stem volume was 65.0%. In addition, the results of a pairwise Student's t-test gave strong support (p-value 0.0001) that the used method was able to detect tree growth within the nine-year period between 2008-2017. The findings of this study allow the further development of enhanced methods for TLS-based single tree and forest growth modeling and estimation, which can thus improve the accuracy of forest inventories and offer better tools for future decision-making processes.
  • Yrttimaa, Tuomas; Saarinen, Ninni; Kankare, Ville; Hynynen, Jari; Huuskonen, Saija; Holopainen, Markus; Hyyppä, Juha; Vastaranta, Mikko (2020)
    There is a limited understanding of how forest structure affects the performance of methods based on terrestrial laser scanning (TLS) in characterizing trees and forest environments. We aim to improve this understanding by studying how different forest management activities that shape tree size distributions affect the TLS-based forest characterization accuracy in managed Scots pine (Pinus sylvestris L.) stands. For that purpose, we investigated 27 sample plots consisting of three different thinning types, two thinning intensities as well as control plots without any treatments. Multi-scan TLS point clouds were collected from the sample plots, and a point cloud processing algorithm was used to segment individual trees and classify the segmented point clouds into stem and crown points. The classified point clouds were further used to estimate tree and forest structural attributes. With the TLS-based forest characterization, almost 100% completeness in tree detection, 0.7 cm (3.4%) root-mean-square- error (RMSE) in diameter-at-breast-height measurements, 0.9–1.4 m (4.5–7.3%) RMSE in tree height measure-ments, and <6% relative RMSE in the estimates of forest structural attributes (i.e. mean basal area, number of trees per hectare, mean volume, basal area-weighted mean diameter and height) were obtained depending on the applied thinning type. Thinnings decreased variation in horizontal and vertical forest structure, which especially favoured the TLS-based tree detection and tree height measurements, enabling reliable estimates for forest structural attributes. A considerably lower performance was recorded for the control plots. Thinning intensity was noticed to affect more on the accuracy of TLS-based forest characterization than thinning type. The number of trees per hectare and the proportion of suppressed trees were recognized as the main factors affecting the accuracy of TLS-based forest characterization. The more variation there was in the tree size distribution, the more challenging it was for the TLS-based method to capture all the trees and derive the tree and forest structural attributes. In general, consistent accuracy and reliability in the estimates of tree and forest attributes can be expected when using TLS for characterizing managed boreal forests.