2017
DOI: 10.1016/j.foreco.2016.09.012
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A generalized nonlinear mixed-effects height to crown base model for Mongolian oak in northeast China

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Cited by 72 publications
(122 citation statements)
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“…Tree diameter at breast height (DBH) is an important characteristic and can be directly measured on the ground. It is an indicator of tree vigor and used to describe stand structure, estimate tree volume and biomass, and select sample trees in a forest inventory [1][2][3][4]. However, it would be costly and time consuming to collect DBH data over a large forest area.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Tree diameter at breast height (DBH) is an important characteristic and can be directly measured on the ground. It is an indicator of tree vigor and used to describe stand structure, estimate tree volume and biomass, and select sample trees in a forest inventory [1][2][3][4]. However, it would be costly and time consuming to collect DBH data over a large forest area.…”
Section: Introductionmentioning
confidence: 99%
“…An appropriate solution to this problem is to apply nonlinear mixed-effects (NLME) modeling. This method has been mostly used to develop forest models in recent years [3,21,22], as this analyzes the mutually correlated observations more effectively and results in a higher prediction accuracy compared to OLS regression [23,24]. To the authors' knowledge, although a number of studies have used tree height and crown characteristics [3,4,22] as predictors in DBH estimation models [1, 18,25], none of the studies have applied the NLME modeling approach and airborne LiDAR data to establish DBH models.…”
Section: Introductionmentioning
confidence: 99%
“…However, additional sample trees may be needed for the stands with heterogeneous structures to obtain a similar precision [55,89]. An optimum size of sample of trees required for localizing the mixed-effects model is discussed in various literature [41,43,53,55,56,80,91], and they conclude that the larger the size of the sub-sample trees to be used for calibration is, the higher the prediction precision is. Though the reduction of the prediction errors becomes insignificant after four or five sample trees, measurement costs increase [53,80].…”
Section: Discussionmentioning
confidence: 99%
“…The parameters in the developed mixed-effects height-diameter model were estimated by maximum likelihood using the Lindstrom and Bates (LB) algorithm implemented in the R software (version 3.2.2) nlme function based on fitting dataset [27]. Detailed descriptions of the mixed-effects modeling are presented in the references [28][29][30][31].…”
Section: Traditional Approachmentioning
confidence: 99%