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The influence that parameters crookedness and taper have on the stack volume was analyzed by using a 3D-simulation model in this study. To do so, log length, diameters at the midpoint and both ends, crookedness, bark thickness, taper and ovality were measured in 1000 logs of Scots pine. From this database, several data sets with different proportions of crooked and tapered logs in stack as well as with different degrees of taper and crookedness were created and taken as basis to simulate the stacks and carry out the analysis. The results show how the variation of these parameters influences the stack volume and provide their volume variation grades. These rates of variation were compared with measurement guidelines of some countries and previous research works. In conclusion, the parameters crookedness and taper influence the stack volume to a considerable extent. Specifically, the stack volume is increased as the crookedness degree or the proportion of crooked logs increases. In contrast, the stack volume is reduced as the taper degree or the proportion of tapered logs increases. Furthermore, the results demonstrate the capability of this simulation model to provide accurate results which can serve as a basis for future studies.
Comparison of different approaches to estimate bark volume of industrial wood at disc and log scale
(2021)
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.
The accurate estimation of timber volume is of the utmost importance. For industrial timber, the volume is often estimated as stacked cubic meters. In addition to manual measurements, volume estimation is possible with photo-optical systems. Over 100 piles of industrial timber of broadleaved tree species were analyzed. In the study, a standard manual measurement method for the estimation of wood pile volumes was compared with a smartphone based photo-optical application for the determination of woodpile volume. Mean gross volume of the piles was approximately 56 m3 and mean width of piles was 9.43 m. A strong correlation was found between the manual measurements and the photo-optical measurement. However, volume estimation of large volume piles seems to perform better in comparison to piles with small volumes. Further research is needed to determine the effects of variables such as log quality or quality of pile on volume estimation accuracy.
The quantification of the solid wood content in a wood stack has been an object of investigation since the 18th century. Particularly, the log parameters exert a considerable influence on the volume of the stack, such as (1) the log midpoint diameter, (2) average bark thickness, (3) crookedness, and (4) log taper. Although many of these parameters have already been studied and some are already considered in many countries when measuring wood stacks, their influence has not been analyzed individually so far since a broad statistical database is needed and the data collection is very costly. Consequently, a 3D-simulation model was developed based on a cross-platform game engine. This model generates virtual wood stacks based on a data set of logs which are defined by the user. The simulation of a stack can be done in a few seconds only and each stack generated can be visualized once all iterations are done. The simulation results are the stacked cubic volume, solid wood cubic volume, and the respective conversion factors. The model, fed with both real data and user-defined data, allows for a detailed analysis of the effect of each parameter on the results, as the user can vary their values discretionary. To obtain the first results from real data, 1000 logs of Scots pine (Pinus sylvestris L.) were measured. The first simulations based on these data show reliable results and it is possible to quantify the influence of the proportion of crooked wood in a pile on the stack volume and the conversion factor. In addition, the results are highly in line with the real trials that have already been performed in parallel. A further scientific evaluation and statistical analysis will be done in a second study phase. However, the model already provides a reasonable tool that is easy to apply for the forest and wood industry in order to make the most accurate estimate possible of the solid wood content in a wood pile.
Assessing the solid wood content is crucial when acquiring stacked roundwood. A frequently used method for this is to multiply determined conversion factors by the measured gross volume. However, the conversion factors are influenced by several log and stack parameters. Although these parameters have been identified and studied, their individual influence has not yet been analyzed using a broad statistical basis. This is due to the considerable financial resources that the data collection entails. To overcome this shortcoming, a 3D-simulation model was developed. It generates virtual wood stacks of randomized composition based on one individual data set of logs, which may be real or defined by the user. In this study, the development and evaluation of the simulation model are presented. The model was evaluated by conducting a sensitivity and a quantitative analysis of the simulation outcomes based on real measurements of 405 logs of Norway spruce and 20 stacks constituted with these. The results of the simulation outcomes revealed a small overestimation of the net volume of real stacks: by 1.2% for net volume over bark and by 3.2% for net volume under bark. Furthermore, according to the calculated mean bias error (MBE), the model underestimates the gross volume by 0.02%. In addition, the results of the sensitivity analysis confirmed the capability of the model to adequately consider variations in the input parameters and to provide reliable outcomes.
One method for estimating the solid wood content in a stack involves using conversion factors and multiplying these by the measured gross volume. The conversion factors can vary depending on several log and stack parameters. The aim of this study was to analyze eleven parameters using a 3D simulation model based on 541 measured logs of Norway spruce. To this end, 50 data sets were created from measured logs, where the parameters of interest in this study (e.g., length, crookedness, taper …) were classified according to different ranges. After that, 64 runs of simulations were carried out. In each simulation run, 150 stacks were modeled. The simulation results were compared with previous studies and with the measurement guidelines of several countries. This analysis revealed that the parameters midpoint diameter, length, crookedness, delimbing quality and the proportion of moderately and highly crooked logs in a stack have a considerable influence on the conversion factors. Taper, proportion of butt logs in a stack and stack height have a modest effect as do the proportion of tapered and crooked logs for low and high taper and low crookedness. In contrast, ovality and the proportion of logs stacked in opposite directions have a marginal influence on the conversion factors. Based on findings from these analyses, the current measurement guidelines of different countries can now be adapted to achieve a higher degree of accuracy.
The aim of this study was the development of a methodical processing line for estimating the log’s volume from scanning logs using a long-range high-speed personal laser scanner (PLS) GeoSLAM ZEB HORIZON and simultaneous localization and mapping (SLAM) technology in an open-source software framework of Cloud Compare. Additionally, the accuracy and precision of using PLS and the suggested method when measuring roundwood volume was examined compared to measurements made using a xylometer and estimations obtained from applying the formulae of Huber, Smalian and Newton. For this purpose, several parameters were measured in 50 logs of Norway spruce with an average length of 2.53 m and a mean diameter of 19.97 cm. Afterwards, the volume of these 50 logs was measured with a xylometer. The results of these measurements served as reference values. The same 50 logs were subsequently scanned with the PLS. The scans were converted into point clouds and were analyzed in Cloud Compare to estimate the volume of the scanned logs. Next, the root mean square error (RMSE) and the mean bias error (MBE) as well as their relative values were calculated for the volumes determined in Cloud Compare and estimated with the above mentioned formulae. The calculated RMSE (and relative RMSE) determined a deviation of the logs' volumes estimated in Cloud Compare from the xylometric volumes of 2.88 dm3 (3.54%) whereas the deviations of the log’s volumes calculated applying the formulae of Huber, Smalian and Newton from the xylometric volumes were respectively 9.63 dm3 (11.83%), 10.33 dm3 (12.69%) and 4.69 dm3 (5.76%). The calculated MBE (and relative MBE) showed that the estimated volumes in Cloud Compare and those using the formulae were overestimated, with the lowest overestimation of 0.10 dm3 (0.12%) in Cloud Compare and the highest, 5.50 dm3 (6.75%), using the Smalian formula. Therefore, it can be stated that results of suggested methodical processing line came closest to the logs' volumes obtained with the xylometer, i.e., they were more accurate and precise compared to the conventionally formulae for log’s volume estimation. The implementation of this method has the potential filling a gap towards a wall-to-wall complete digitization of the roundwood commercialization and ensure transparency and acceptance between the stakeholders involved in the wood supply chain.
In commercial transaction of stacked roundwood, the estimation of the stack net volume plays a key role. One generalized method to determine the net volume is using conversion factors that relate the gross and net volumes. In this literature review the developed methods to estimate the conversion factors as well as their influencing parameters were analyzed based on 153 references from America and Europe. According to the results, 48 different methods (including their variants) for estimating the conversion factors were developed. The newest methods enabled their accurate determination inexpensively, e.g., photo-optical methods or 3D simulation models. The analyzed references revealed that 30 parameters influence the conversion factors. Based on this comprehensive review, each stakeholder involved in the roundwood supply chain can know which method is used for estimating the conversion factors in the analyzed territories and which influencing parameters should be considered when purchasing roundwood in order to accurately assess the solid wood content in the stacks.
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. Forty-seven wood stacks, ranging from 8.9 to 209.3 m3 (totalling approximately 2700 m3), 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.