Determining the current position in a forest is essential for many applications and is often carried out using smartphones. Modern smartphones now support various GNSS constellations and multi-frequency analyses, which are expected to provide more accurate positioning. This study compares the static autonomous GNSS positioning accuracy under forest conditions of four multi-frequency multi-constellation smartphones as well as six single-frequency smartphones and a geodetic receiver. Measurements were carried out at 15 different study sites under forest canopies, with 24 measurements lasting approximately 10 min each taken for the 11 GNSS receivers. The results indicate that, on average, multi-frequency smartphones can achieve a higher positioning accuracy. However, the accuracy varies greatly between smartphones, even between identical or quasi-identical tested smartphones. Therefore, no accuracy should be generalised depending on the number of usable frequencies or constellations, but each smartphone should be considered separately. The dual-frequency Xiaomi Mi 10 clearly stands out compared with the other smartphone with a DRMS of 4.56 m and has a 34% lower absolute error than the best single-frequency phone.
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.
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.
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