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Remote Sens. 2017, 9(8), 808; https://doi.org/10.3390/rs9080808

Modeling the Effect of the Spatial Pattern of Airborne Lidar Returns on the Prediction and the Uncertainty of Timber Merchantable Volume

1
Department of Wood and Forest Sciences, Université Laval, Quebec City, QC G1V 0A6, Canada
2
Department of Geography, Université du Québec à Montréal, Montréal, QC H3C 3P8, Canada
*
Author to whom correspondence should be addressed.
Academic Editors: Lars T. Waser and Prasad S. Thenkabail
Received: 1 June 2017 / Revised: 24 July 2017 / Accepted: 1 August 2017 / Published: 6 August 2017
(This article belongs to the Section Forest Remote Sensing)
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Abstract

Lidar data are regularly used to characterize forest structures. In this study, we determine the effects of three lidar attributes (density, spacing, scanning angle) on the accuracy and the uncertainty of timber merchantable volume estimates of balsam fir stands (Abies balsamea (L.) Mill.) in eastern Canada. We used lidar point clouds to compute predictor variables of the merchantable volume in a nonlinear model. The best model included the mean height of first returns, the proportion of first returns below 2 m and the canopy surface roughness index. Our analysis shows a high correlation between lidar and field data of 119 plots (pseudo-R2 = 0.91), however, residuals were heteroscedastic. More precise parameter estimates were obtained by adding to the model a variance function of variables describing the mean height of returns and the skewness of the area distribution of triangulated lidar returns. The residual standard deviation was better estimated (3.7 m3 ha−1 multiplied by the variance function versus 28.0 m3 ha−1). We found no effect of density on the predictions (p-value = 0.74). This suggests that the height and the spatial pattern of returns, rather than the density, should be considered to better assess the uncertainty of merchantable volume estimates. View Full-Text
Keywords: lidar; timber merchantable volume; spatial distribution; return density; return spacing; scanning angle; residual variance lidar; timber merchantable volume; spatial distribution; return density; return spacing; scanning angle; residual variance
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Yoga, S.; Bégin, J.; St-Onge, B.; Riopel, M. Modeling the Effect of the Spatial Pattern of Airborne Lidar Returns on the Prediction and the Uncertainty of Timber Merchantable Volume. Remote Sens. 2017, 9, 808.

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