An Equation for Estimating Total Volume of Both Stands and Single Trees of Black Spruce

Evert, F.

doi:10.5558/tfc59026-1

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…The fitted bivariate cumulative distribution function of DBH and HT is in Figure 1. For each drawn pair of DBH and HT, the value of VOL came from application of Evert's volume equation (Evert 1983) that was fitted using the data from the 785 felled trees.…”

Section: Methodsmentioning

confidence: 99%

Retrieval of among-stand variances from one observation per stand

Magnussen¹,

Breidenbach²

2020

J. For. Sci.

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Forest inventories provide predictions of stand means on a routine basis from models with auxiliary variables from remote sensing as predictors and response variables from field data. Many forest inventory sampling designs do not afford a direct estimation of the among-stand variance. As consequence, the confidence interval for a model-based prediction of a stand mean is typically too narrow. We propose a new method to compute (from empirical regression residuals) an among-stand variance under sample designs that stratify sample selections by an auxiliary variable, but otherwise do not allow a direct estimation of this variance. We test the method in simulated sampling from a complex artificial population with an age class structure. Two sampling designs are used (one-per-stratum, and quasi systematic), neither recognize stands. Among-stand estimates of variance obtained with the proposed method underestimated the actual variance by 30-50%, yet 95% confidence intervals for a stand mean achieved a coverage that was either slightly better or at par with the coverage achieved with empirical linear best unbiased estimates obtained under less efficient two-stage designs.

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Section: Methodsmentioning

confidence: 99%

Retrieval of among-stand variances from one observation per stand

Magnussen¹,

Breidenbach²

2020

J. For. Sci.

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“…(6) Test of homogeneity of the residual when they are plotted against the independent variable. (7) Validation of the selected model by using an independent dataset.…”

Section: Construction Techniquementioning

confidence: 99%

The Use of Mathematical and Statistical Analysis in Selecting of Best Regression Equation for Quercus Infectoria G.Olivier

Salih

2023

IOP Conf. Ser.: Earth Environ. Sci.

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The purpose of this study is to use mathematical and statistical analysis in testing the performance ability of standard volume models in volume prediction of Gall Oak trees. A sample of 205 non - destructive trees was purposely selected from Duhok Governorate, Kurdistan region, Iraq. Of which 157 were used for estimating the parameters of regression models and the rest (48) trees served as validation data. Using computer facilities, the available software packages, and tools including STATGRAPHIC Centurion and Excel tool, the parameters of 28 models were estimated. A multistage procedure was used for screening the generated regression equations and selecting the most appropriate one, which underwent validation with independent data. In this study, a new criterion was proposed and used for testing the accuracy of regression equations in the prediction of the dependent variable. At the end of this process, the regression equation Vt = 0.00442+0.0108D^1.917H was finally selected as the most appropriate one that fits the data.

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Stand volume functions forpicea abiesin western Norway

Næsset

1995

Scandinavian Journal of Forest Research

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An Equation for Estimating Total Volume of Both Stands and Single Trees of Black Spruce

Cited by 3 publications

References 2 publications

Retrieval of among-stand variances from one observation per stand

Retrieval of among-stand variances from one observation per stand

The Use of Mathematical and Statistical Analysis in Selecting of Best Regression Equation for Quercus Infectoria G.Olivier

Stand volume functions forpicea abiesin western Norway

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