Norway spruce bark thickness models based on log midspan diameter for use in mechanized forest harvesting in Czechia

Martin, Jay K.; Natov, Pavel; Dvořák, Jiří; Szała, Leszek

doi:10.1080/02827581.2019.1650952

Cited by 6 publications

(6 citation statements)

References 24 publications

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“…However, even if the choice of equation used in determining volume of bark is a source of error 20 , bark factors with a focus on bark thickness are well studied and the performances of several equations for different tree species show good results 10 , 11 , 16 , 30 , 33 . Such bark thickness factors are for example used when harvesters estimate under-bark volumes from over-bark measurements 6 , 34 . In this study we analyzed the accuracy of bark volume estimation on discs under laboratory conditions and on logs under real world conditions.…”

Section: Discussionmentioning

confidence: 99%

Comparison of different approaches to estimate bark volume of industrial wood at disc and log scale

Berendt

Miguel-Díez

Wallor

et al. 2021

Sci Rep

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Within the wood supply chain, the measurement of roundwood plays a key role due to its high economic impact. While wood industry mainly processes the solid wood, the bark mostly remains as an industrial by-product. In Central Europe, it is common that the wood is sold over bark but that the price is calculated on a timber volume under bark. However, logs are often measured as stacks and, thus, the volume includes not only the solid wood content but also the bark portion. Mostly, the deduction factors used to estimate the solid wood content are based on bark thickness. The aim of this study was to compare the estimation of bark volume from scaling formulae with the real bark volume, obtained by xylometric technique. Moreover, the measurements were performed using logs under practice conditions and using discs under laboratory conditions. The mean bark volume was 6.9 dm3 and 26.4 cm3 for the Norway spruce logs and the Scots pine discs respectively. Whereas the results showed good performances regarding the root mean square error, the coefficient of determination (R2) and the mean absolute error for the volume estimation of the total volume of discs and logs (over bark), the performances were much lower for the bark volume estimations only.

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Section: Discussionmentioning

confidence: 99%

Comparison of different approaches to estimate bark volume of industrial wood at disc and log scale

Berendt

Miguel-Díez

Wallor

et al. 2021

Sci Rep

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“…The fit of the linear functions to the CCT data was tested through the mean absolute error (the average absolute difference between the values predicted by the linear models and the CCT values; MAE), mean absolute percentage error (the average absolute difference between the linearly modeled values and the CCT values divided by the CCT value, multiplied by 100; MAPE), root mean square error (the square root of the average of squared errors; RMSE), mean bias error (the average difference between the predicted values predicted through the linear models and the CCT values; MBE), and mean percentage error (the average difference between the values predicted by the linear models and the CCT values divided by the mean CCT double bark thickness, multiplied by 100; MPE). The procedure was described in more detail for Norway spruce by Jankovský et al (2019).…”

Section: Construction Of Linear Function and Statistical Analysismentioning

confidence: 99%

“…insects, fungi) and abiotic (e.g. weather, fire, physical damage) environmental factors (Jankovský et al 2019). Its thickness and texture differ significantly from extremely rough to fine, depending on e.g.…”

Section: Introductionmentioning

confidence: 99%

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Double Bark Thickness Estimation Models of Common European Broadleaved Species for Harvester Timber Volume Estimation in Czechia

Martin¹,

Dvořák²,

Löwe³

et al. 2022

Croat. j. for. eng. (Online)

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The share of the annual volume of harvester-produced timber in Czech forest bioeconomy has increased in the last decades. To estimate under-bark timber volume, harvester systems allow choosing between two different bark deduction models – diameter band (DBM) and linear model. However, linear models were not calibrated for the conditions of Czech forestry. Therefore, the objective of this research was to develop, for local conditions in Czechia, linear functions for estimating the double bark thickness of two groups of broadleaved species (beech and oak) and to test their viability based on real harvest data. To create the linear functions, official Czech cubing tables were used. Data from real harvests were gathered from fifteen harvesters. A sample containing 4995 logs belonging to the beech group was analyzed using descriptive statistics and the Paired Wilcoxon tests. The mean double bark thickness for beech group was 15.1 mm (polynomial and linear model). For oak group, it was 15.48 mm (polynomial) or 15.49 mm (linear). The results of real harvests for beech group revealed that the mean double bark thickness estimated by the polynomial function was 7.08 mm. The linear function estimates were closer to the value estimated by the polynomial (6.84 mm) than DBM estimates (6.68 mm). Therefore, we can state that the newly developed linear models can be used in fully mechanized harvesting instead of manual bark deduction methods in Czechia.

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“…However, the Czech polynomial model cannot be input into the forest machine systems, thus presenting the need to either localize the methods from different countries or continue measuring all timber manually. To remedy this problem, Jankovský et al [51,52] have linearized the standard polynomial bark deduction models for all main species groups into the so-called LinBark function, thus enabling the use of automated timber scaling by harvester forest machine systems in Czechia.…”

Section: Introductionmentioning

confidence: 99%

Accuracy of Double Bark Thickness Estimation Methods Used in Spruce—(Picea abies L. Karst) Timber Production in Czechia

Jankovský,

Dudáková,

Allman

et al. 2023

Forests

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The accurate estimation of bark thickness is important for foresters for several reasons. It is crucial for timber volume estimation and can help improve the quality of forestry records, and bark has a growing commercial importance as a high-value bioresource. The problem is that models such as the Czech Cubic Tables (CCT) polynomial model are frequently unique. Furthermore, the official method requires rounding down the midspan over-bark diameter (DOB) to the nearest centimetre to estimate the double bark thickness (DBT) and merchantable timber volume. Therefore, we verified the significance of the effects of rounding down the midspan DOB on DBT using a dataset of 438 recently harvested Norway spruce (Picea Abies L. Karst.) logs from the Central Bohemian region. The correlation analysis showed that for measured data without rounding down the diameters, the variability of the DBT was able to explain only 8% of the DOB variability. As for the rounded-down data, the coefficient of determination was slightly higher, reaching 9%. The paired-samples T-tests showed a significant difference between the DBT as calculated directly from measured data and that from the rounded-down over-bark diameters (p < 0.05). The polynomial and linear models underestimated the DBT (2.24 and 1.75 mm on average, respectively) on measured data. In contrast, for data from the rounded-down DOB, the models overestimated the DBT (2.70 or 3.18 mm on average, respectively).

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Norway spruce bark thickness models based on log midspan diameter for use in mechanized forest harvesting in Czechia

Cited by 6 publications

References 24 publications

Comparison of different approaches to estimate bark volume of industrial wood at disc and log scale

Comparison of different approaches to estimate bark volume of industrial wood at disc and log scale

Double Bark Thickness Estimation Models of Common European Broadleaved Species for Harvester Timber Volume Estimation in Czechia

Accuracy of Double Bark Thickness Estimation Methods Used in Spruce—(Picea abies L. Karst) Timber Production in Czechia

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