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Open AccessArticle

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

1
School of Forest Sciences, University of Eastern Finland, P.O. Box 111, 80101 Joensuu, Finland
2
Department of Forest Sciences, University of Helsinki, P.O. Box 27, 00014 Helsinki, Finland
3
Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute (National Land Survey of Finland), Geodeetinrinne 2, 02431 Masala, Finland
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(12), 1423; https://doi.org/10.3390/rs11121423
Received: 14 May 2019 / Revised: 6 June 2019 / Accepted: 13 June 2019 / Published: 14 June 2019
(This article belongs to the Section Forest Remote Sensing)
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 (Dg) and height (Hg). 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 Hg and V, 85% of the variation in Dg 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. View Full-Text
Keywords: TLS; ground-based LiDAR; point cloud; forest inventory TLS; ground-based LiDAR; point cloud; forest inventory
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Yrttimaa, T.; Saarinen, N.; Kankare, V.; Liang, X.; Hyyppä, J.; Holopainen, M.; Vastaranta, M. Investigating the Feasibility of Multi-Scan Terrestrial Laser Scanning to Characterize Tree Communities in Southern Boreal Forests. Remote Sens. 2019, 11, 1423.

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