A Generalized Lidar-Based Model for Predicting the Merchantable Volume of Balsam Fir of Sites Located along a Bioclimatic Gradient in Quebec, Canada

Forests

Benoît St-Onge¹  Gaétan Daigle²  Sarah Yoga³  Jean Bégin³  Martin Riopel⁴ 

[1] Department of Geography, Université du Québec à Montréal, Montréal, QC H3C 3P8, Canada;Department of Mathematics and Statistics, Université Laval, Quebec City, QC G1V 0A6, Canada;Department of Wood and Forest Sciences, Université Laval, Quebec City, QC G1V 0A6, Canada;Direction des Inventaires Forestiers, Ministère des Forêts, de la Faune et des Parcs du Québec, Quebec City, QC G1H 6R1, Canada;

关键词: lidar;    generalized model;    timber merchantable volume;    balsam fir;    temporal discrepancy;    bioclimatic gradient;    canopy height adjustment;    growth adjustment function;   

DOI  :  10.3390/f9040166

来源: DOAJ

【 摘 要 】

Lidar-based models rely on an optimal relationship between the field and the lidar data for accurate predictions of forest attributes. This relationship may be altered by the variability in the stand growth conditions or by the temporal discrepancy between the field inventory and the lidar survey. In this study, we used lidar data to predict the timber merchantable volume (MV) of five sites located along a bioclimatic gradient of temperature and elevation. The temporal discrepancies were up to three years. We adjusted a random canopy height coefficient (accounting for the variability amongst sites), and a growth function (accounting for the growth during the temporal discrepancy), to the predictive model. The MV could be predicted with a pseudo-R2 of 0.86 and a residual standard deviation of 24.3 m3 ha−1. The average biases between the field-measured and the predicted MVs were small. The variability of MV predictions was related to the bioclimatic gradient. Fixed-effect models that included a bioclimatic variable provided similar prediction accuracies. This study suggests that the variability amongst sites, the occurrence of a bioclimatic gradient and temporal discrepancies are essential in building a generalized lidar-based model for timber volume.

【 授权许可】

Unknown