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Open AccessArticle

Assessing the Effects of Sample Size on Parametrizing a Taper Curve Equation and the Resultant Stem-Volume Estimates

1
Department of Forest Sciences, University of Helsinki, P.O. Box 27, 00014 Helsinki, Finland
2
School of Forest Sciences, University of Eastern Finland, P.O. Box 111, 80101 Joensuu, Finland
3
Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute (National Land Survey of Finland), Geodeetinrinne 2, 02431 Masala, Finland
4
Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 West Burnside Road, Victoria, BC V8Z 1M5, Canada
*
Author to whom correspondence should be addressed.
Forests 2019, 10(10), 848; https://doi.org/10.3390/f10100848
Received: 13 September 2019 / Revised: 23 September 2019 / Accepted: 26 September 2019 / Published: 29 September 2019
(This article belongs to the Section Forest Inventory, Quantitative Methods and Remote Sensing)
Large and comprehensive datasets, traditionally based on destructive stem analysis or other labor-intensive approaches, are commonly considered as a necessity in developing stem-volume equations. The aim here was to investigate how a decreasing number of sample trees affects parametrizing an existing taper curve equation and resultant stem-volume estimates. Furthermore, the potential of terrestrial laser scanning (TLS) in producing taper curves was examined. A TLS-based taper curve was derived for 246 Scots pines (Pinus sylvestris L.) from southern Finland to parametrize an existing taper curve equation. To assess sensitivity of the parametrization regarding sample size, the number of Scots pines included in the parametrization varied between full census and 1 Scots pine at a time. Root mean square error of stem-volume estimates remained ≤20.9% and the mean absolute difference was relatively constant (≤9.0%) between stem-volume estimates when the sample size included ≥46 Scots pines. Thus, it can be concluded that, with a rather small sample size, a taper curve equation can be re-parametrized for local conditions using point clouds from TLS to produce consistent stem-volume estimates. View Full-Text
Keywords: ground-based LiDAR; terrestrial laser scanning; TLS; volume modelling; forest sciences ground-based LiDAR; terrestrial laser scanning; TLS; volume modelling; forest sciences
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MDPI and ACS Style

Saarinen, N.; Kankare, V.; Pyörälä, J.; Yrttimaa, T.; Liang, X.; Wulder, M.A.; Holopainen, M.; Hyyppä, J.; Vastaranta, M. Assessing the Effects of Sample Size on Parametrizing a Taper Curve Equation and the Resultant Stem-Volume Estimates. Forests 2019, 10, 848.

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