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Forests 2016, 7(11), 252;

Automating Plot-Level Stem Analysis from Terrestrial Laser Scanning

Department of Geography, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada
Author to whom correspondence should be addressed.
Academic Editors: Juha Hyyppä, Xinlian Liang and Eetu Puttonen
Received: 25 August 2016 / Revised: 8 October 2016 / Accepted: 24 October 2016 / Published: 28 October 2016
(This article belongs to the Special Issue Forest Ground Observations through Terrestrial Point Clouds)
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Terrestrial laser scanning (TLS) provides an accurate means of analyzing individual tree attributes, and can be extended to plots using multiple TLS scans. However, multiple TLS scans may reduce the effectiveness of individual tree structure quantification, often due to understory occupation, mutual tree occlusion, and other influences. The procedure to delineate accurate tree attributes from plot scans involves onerous steps and automated integration is challenging in the literature. This study proposes a fully automatic approach composed of ground filtering, stem detection, and stem form extraction algorithms, with emphasis on accuracy and feasibility. The delineated attributes can be useful to analyze terrain, tree biomass and fiber quality. The automation was experimented on a mature pine plot in Finland with both single scan (SS) and multiple scans (MS) datasets. With mensuration as reference, digital terrain models (DTM), stem locations, diameters at breast height (DBHs), stem heights, and stem forms of the whole plot were extracted and validated. Results of this study were best using the multiple scans (MS) dataset, where 76% of stems were detected (n = 49). Height extraction accuracy was 0.68 (r2) and 1.7 m (RMSE), and DBH extraction accuracy was 0.97 (r2) and 0.90 cm (RMSE). Height-wise stem diameter extraction accuracy was 0.76 (r2) and 2.4 cm (RMSE). View Full-Text
Keywords: terrestrial laser scanning; forestry; DTM; DBH; stem detection; stem form; automatic; plot scale; TLS; point cloud segmentation terrestrial laser scanning; forestry; DTM; DBH; stem detection; stem form; automatic; plot scale; TLS; point cloud segmentation

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Xi, Z.; Hopkinson, C.; Chasmer, L. Automating Plot-Level Stem Analysis from Terrestrial Laser Scanning. Forests 2016, 7, 252.

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