Estimation of conversion factors for wood stacks in landings and their influencing parameters: a comprehensive literature review for America and Europe

Miguel-Díez, Felipe de; Purfürst, Thomas; Acuña, Mauricio; Tolosana, Eduardo; Cremer, Tobias

doi:10.14214/sf.22018

Cited by 2 publications

(1 citation statement)

References 30 publications

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“…Precise knowledge of harvested and saleable volumes is essential for an agreement between forest owners and wood buyers, as well as to the planning of logistics. This is especially true in the case of industrial wood used for engineered wood products or the pulp and paper industry, with relatively low requirements regarding quality grading, which are thus sold in stacks to facilitate the measurement process (Miguel-Díez et al 2023). In the case of higher-value timber assortments, such as sawn timber, where the wood is measured with a highprecision scanner in the sawmill (Knyaz & Maksimov 2014), the measurement of the wood stacks in the forest still plays an important role.…”

Section: Introductionmentioning

confidence: 99%

Comparison of wood stack volume determination between manual, photo-optical, iPad-LiDAR and handheld-LiDAR based measurement methods

Purfürst,

De Miguel-Díez,

Berendt

et al. 2023

iForest

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The measurement of roadside wood stacks in the forest still plays an important role in many forestry operations. Traditional manual measuring methods can be laborious, inaccurate and error-prone. Therefore, the issue is whether 2.5D or 3D optical remote sensing measuring methods provide more precise or detailed results and advantages in further data processing. This study examined and partly developed nine different manual, photo-optical, iPad ® -LiDAR and handheld laser scanner-LiDAR-based wood stack measurement methods. Fortyseven wood stacks, ranging from 8.9 to 209.3 m 3 (totalling approximately 2700 m 3 ), were measured and compared using these nine methods. All the methods give volume estimations, and none can be seen to give the real or true wood stack gross volume. Surprisingly, the results varied significantly within and between the individual methods, with up to a 9% mean relative deviation. The relative deviation is strongly dependent on the size of the wood stack. The 3D measurement methods using iPad ® RGB and LiDAR recorded lower timber volumes than the other methods, in contrast to the method based on samples taken with handheld laser scanner-LiDAR, which overestimated the volume. Generally, optical-and laser-based surveying techniques could be more widely applied in measuring wood stacks in the future. However, such automatic wood stack gross volume determination approaches still face some challenges, regarding accuracy in the case of the 2.5D methods and the lack of automatisation in the case of 3D methods. Consequently, further research is required in the near future.

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Section: Introductionmentioning

confidence: 99%

Comparison of wood stack volume determination between manual, photo-optical, iPad-LiDAR and handheld-LiDAR based measurement methods

Purfürst,

De Miguel-Díez,

Berendt

et al. 2023

iForest

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Conversion Factor Estimation of Stacked Eucalypt Timber Using Supervised Image Classification with Artificial Neural Networks

de Barros,

Boechat Soares,

da Silva

et al. 2024

JST

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Stacked timber is quantified in-store units and then adjusted with a conversion factor for volume estimation in cubic meters, which is important for the wood trade in South America. However, measuring large quantities accurately can be challenging. Digital image processing and artificial intelligence advancements offer promising solutions, making research in this area increasingly attractive. This study aims to estimate conversion factors of stacked Eucalyptus grandis timber using supervised image classification with Artificial Neuronal Network (ANN). Measured data and photographs from an experiment involving thirty stacks of timber were used to achieve this. The conversion factor was determined using photographic methods that involved the applications of equidistant points and ANN and subsequently validated with values observed through the manual method. The ANN method produced more accurate conversion factor estimates than the equidistant points method. Approximately 97% of the ANN estimates were within the ±1% error class, even when using low-resolution digital photographs.

show abstract

Estimation of conversion factors for wood stacks in landings and their influencing parameters: a comprehensive literature review for America and Europe

Cited by 2 publications

References 30 publications

Comparison of wood stack volume determination between manual, photo-optical, iPad-LiDAR and handheld-LiDAR based measurement methods

Comparison of wood stack volume determination between manual, photo-optical, iPad-LiDAR and handheld-LiDAR based measurement methods

Conversion Factor Estimation of Stacked Eucalypt Timber Using Supervised Image Classification with Artificial Neural Networks

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