Differences in Timber Volume Estimates Using Various Algorithms Available in the Control and Information Systems of Harvesters

Abstract

Timber is the most important source of revenue in forestry and, therefore, is necessary to precisely estimate its volume. The share of timber volume produced by harvesters is annually growing in many European countries. Suitable settings of harvesters will allow us to achieve the most accurate volume estimates of the produced timber. In this study, we compared the different methods of log volume estimation applied by control and information systems of harvesters. The aim was to analyze the price categories that can be set up in the StanForD standard and to determine the differences between the algorithms used for log volume estimations. We obtained the data from *.STM files collected from March 2017 until June 2018 on a medium-size harvester. We analyzed price categories and found seven different algorithms used to estimate the log volumes. Log volume estimates according to Algorithm A2 were considered as standard because these estimates should be closest to the true log volumes. Significant differences, except the difference between Algorithm A2 and Algorithm A3, were found between log volumes estimated by different algorithms. After categorization of logs to assortments, the results showed that significant differences existed between algorithms in each assortment. In the roundwood assortment, which contains the most valuable logs, a difference of more than 6% was found between the log volumes estimated by Algorithm A5 and Algorithm A2. This is interesting because Algorithm A5 is widely used in some Central European countries. To obtain volumes closest to the true volumes, we should use Algorithm A2 for the harvester production outputs. The resulting differences between the algorithms can be used to estimate the volume difference between harvester outputs using the different price categories. Understanding this setting of harvesters and the differences between the price categories will provide users useful information in applied forest management.

Models to Estimate the Bark Volume for Larix sp. in Poland

“…The goodness-of fit measures obtained for validation dataset proved the good performance of the best models chosen based on AIC for bark volume prediction in case of d and V as independent variables (Table 2). For height, R 2 and RMSE values were lower than ones calculated with calibration dataset. Residues of the validated models were not normally-distributed and their means differed significantly from 0 indicating systematic bias (Table 2).…”

“…Both these equations showed similar performance for bV as well as for %bV. For bark volume, the lowest R 2 and RMSE values characterized models using height as the independent value, while the highest ones were observed for equations based on total tree volume (Table 1). Such relationship only partially confirms previous findings as height turns to perform weaker as a bark volume descriptor than reported by other authors [5][6].…”

“…In Central Europe, it is a common practice to sell the timber with the bark, however the customer pays for the volume estimated under the bark. The conversion of over-bark measurements to under-bark records is made using various methods of bark thickness or bark volume determination [1,2]. Therefore, in addition to the improvement of the measurement methods and equipment, efforts are undertaken to develop better and better models that allow to determine bark features precisely [3].…”

Untitled

“…Strong sanitary and health conditions and a good level of security are a major competitive advantage for most European countries in travel and tourism (World Economic Forum, 2017). Diverse natural conditions and various cultural assets, together with a high level of care for the environment, provide a quality framework for the realization of tourism (Vasylchak, Halachenko, 2016;Löwe et al, 2019;World Economic Forum, 2019). E.U.…”

What Happens to Wood after a Tree Is Attacked by a Bark Beetle?

“…Economic profit from the sale of wood is the primary source of income in forestry, so it is necessary to determine as accurately as possible the tradable timber volume [30] and, simultaneously, know its quality. The highest quality ranges of wood have several times higher price at the same volume than ranges of lower qualities.…”