Investigating the Feasibility of Multi-Scan Terrestrial Laser Scanning to Characterize Tree Communities in Southern Boreal Forests

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http://hdl.handle.net/10138/304498

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Yrttimaa , T , Saarinen , N , Kankare , V , Liang , X , Hyyppa , J , Holopainen , M & Vastaranta , M 2019 , ' Investigating the Feasibility of Multi-Scan Terrestrial Laser Scanning to Characterize Tree Communities in Southern Boreal Forests ' , Remote Sensing , vol. 11 , no. 12 , 1423 . https://doi.org/10.3390/rs11121423

Title: Investigating the Feasibility of Multi-Scan Terrestrial Laser Scanning to Characterize Tree Communities in Southern Boreal Forests
Author: Yrttimaa, Tuomas; Saarinen, Ninni; Kankare, Ville; Liang, Xinlian; Hyyppa, Juha; Holopainen, Markus; Vastaranta, Mikko
Contributor: University of Helsinki, Laboratory of Forest Resources Management and Geo-information Science
University of Helsinki, Forest Health Group
University of Helsinki, Forest Health Group
University of Helsinki, Department of Forest Sciences
University of Helsinki, Department of Forest Sciences
Date: 2019-06-02
Language: eng
Number of pages: 22
Belongs to series: Remote Sensing
ISSN: 2072-4292
URI: http://hdl.handle.net/10138/304498
Abstract: Terrestrial laser scanning (TLS) has proven to accurately represent individual trees, while the use of TLS for plot-level forest characterization has been studied less. We used 91 sample plots to assess the feasibility of TLS in estimating plot-level forest inventory attributes, namely the stem number (N), basal area (G), and volume (V) as well as the basal area weighed mean diameter (D-g) and height (H-g). The effect of the sample plot size was investigated by using different-sized sample plots with a fixed scan set-up to also observe possible differences in the quality of point clouds. The Gini coefficient was used to measure the variation in tree size distribution at the plot-level to investigate the relationship between stand heterogeneity and the performance of the TLS-based method. Higher performances in tree detection and forest attribute estimation were recorded for sample plots with a low degree of tree size variation. The TLS-based approach captured 95% of the variation in H-g and V, 85% of the variation in D-g and G, and 67% of the variation in N. By increasing the sample plot size, the tree detection rate was decreased, and the accuracy of the estimates, especially G and N, decreased. This study emphasizes the feasibility of TLS-based approaches in plot-level forest inventories in varying southern boreal forest conditions.
Subject: 4112 Forestry
TLS
ground-based LiDAR
point cloud
forest inventory
BIOMASS ESTIMATION
AIRBORNE
BIODIVERSITY
DIVERSITY
HEIGHT
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