Browsing by Subject "wood procurement"

Sort by: Order: Results:

Now showing items 1-4 of 4
  • Pyörälä, Jiri; Kankare, Ville; Vastaranta, Mikko; Rikala, Juha; Holopainen, Markus; Sipi, Marketta; Hyyppä, Juha; Uusitalo, Jori (2018)
    While X-ray scanning is increasingly used to measure the interior quality of logs, terrestrial laser scanning (TLS) could be used to collect information on external tree characteristics. As branches are one key indicator of wood quality, we compared TLS and X-ray scanning data in deriving whorl locations and each whorl's maximum branch and knot diameters for 162 Scots pine (Pinus sylvestris L.) log sections. The mean number of identified whorls per tree was 37.25 and 22.93 using X-ray and TLS data, respectively. The lowest TLS-derived whorl in each sample tree was an average 5.56 m higher than that of the X-ray data. Whorl-to-whorl mean distances and the means of the maximum branch and knot diameters in a whorl measured for each sample tree using TLS and X-ray data had mean differences of -0.12 m and -6.5 mm, respectively. One of the most utilized wood quality indicators, tree-specific maximum knot diameter measured by X-ray, had no statistically significant difference to the tree-specific maximum branch diameter measured from the TLS point cloud. It appears challenging to directly derive comparative branch structure information using TLS and X-ray. However, some features that are extractable from TLS point clouds are potential wood quality indicators.
  • Saukkola, Atte; Melkas, Timo; Riekki, Kirsi; Sirparanta, Sanna; Peuhkurinen, Jussi; Holopainen, Markus; Hyyppa, Juha; Vastaranta, Mikko (2019)
    The aim of the study was to develop a new method to use tree stem information recorded by harvesters along operative logging in remote sensing-based prediction of forest inventory attributes in mature stands. The reference sample plots were formed from harvester data, using two different tree positions: harvester positions (XYH) in global satellite navigation system and computationally improved harvester head positions (XYHH). Study materials consisted of 158 mature Norway-spruce-dominated stands located in Southern Finland that were clear-cut during 2015-16. Tree attributes were derived from the stem dimensions recorded by the harvester. The forest inventory attributes were compiled for both stands and sample plots generated for stands for four different sample plot sizes (254, 509, 761, and 1018 m(2)). Prediction models between the harvester-based forest inventory attributes and remote sensing features of sample plots were developed. The stand-level predictions were obtained, and basal-area weighted mean diameter (D-g) and basal-area weighted mean height (H-g) were nearly constant for all model alternatives with relative root-mean-square errors (RMSE) roughly 10-11% and 6-8%, respectively, and minor biases. For basal area (G) and volume (V), using either of the position methods, resulted in roughly similar predictions at best, with approximately 25% relative RMSE and 15% bias. With XYHH positions, the predictions of G and V were nearly independent of the sample plot size within 254-761 m(2). Therefore, the harvester-based data can be used as ground truth for remote sensing forest inventory methods. In predicting the forest inventory attributes, it is advisable to utilize harvester head positions (XYHH) and a smallest plot size of 254 m(2). Instead, if only harvester positions (XYH) are available, expanding the sample plot size to 761 m(2) reaches a similar accuracy to that obtained using XYHH positions, as the larger sample plot moderates the uncertainties when determining the individual tree position.
  • Pyörälä, Jiri; Liang, Xinlian; Vastaranta, Mikko; Saarinen, Ninni; Kankare, Ville; Wang, Yunsheng; Holopainen, Markus; Hyyppä, Juha (2018)
    State-of-the-art technology available at sawmills enables measurements of whorl numbers and the maximum branch diameter for individual logs, but such information is currently unavailable at the wood procurement planning phase. The first step toward more detailed evaluation of standing timber is to introduce a method that produces similar wood quality indicators in standing forests as those currently used in sawmills. Our aim was to develop a quantitative method to detect and model branches from terrestrial laser scanning (TLS) point clouds data of trees in a forest environment. The test data were obtained from 158 Scots pines (Pinus sylvestris L.) in six mature forest stands. The method was evaluated for the accuracy of the following branch parameters: Number of whorls per tree and for every whorl, the maximum branch diameter and the branch insertion angle associated with it. The analysis concentrated on log-sections (stem diameter > 15 cm) where the branches most affect wood's value added. The quantitative whorl detection method had an accuracy of 69.9% and a 1.9% false positive rate. The estimates of the maximum branch diameters and the corresponding insertion angles for each whorl were underestimated by 0.34 cm (11.1%) and 0.67 degrees (1.0%), with a root-mean-squared error of 1.42 cm (46.0%) and 17.2 degrees (26.3%), respectively. Distance from the scanner, occlusion, and wind were the main external factors that affect the method's functionality. Thus, the completeness and point density of the data should be addressed when applying TLS point cloud based tree models to assess branch parameters.
  • Onali, Harri (Helsingin yliopisto, 2017)
    The paper industry is one of the largest industrial sectors in India. In general, wood procurement processes play an important role in the operations of the paper industry, but there is very less research on India in this topic. The purpose of this study was to evaluate the present state of wood procurement in the Indian paper industry and finally to detect possible bottlenecks in the system. The data was collected by interviews from a total of 10 paper mills in India. Paper industry in India is entirely based on a plantation forestry, where private farming plays a very large role. Wood procurement begins with planning. The field officers cooperate with the vendors in the field. The vendors are private operators who trade directly with up to thousands of farmers and are therefore necessary for the successful operations. Wood is almost always harvested manually by axes and rarely with chain saws. Long-distance transport is mainly carried out by trucks which can carry about 15 to 20 tons of wood at a time. At the reception, the quality of the raw material and the papers are checked, and the load size is weighed. After reception, the wood is transported either to the wood yard or alternatively directly to the chipper. The load is unloaded either by loaders, or sometimes, but rarely, by hand. The results show clearly that the mills are dissatisfied with the present state of wood procurement. The biggest problem is that there the domestic supply is insufficient, which makes the wood raw material price very high and forces the industry to buy wood from abroad and longer distances which affect negatively to transport costs. In India, land ownings of farmers are also small and it complicates efficient wood procurement processes. In addition, farming trees does not interest the local people. Infrastructure is also weak and the use of trains in wood transport is difficult. Some mills stated that the policy plays too big role in determining the price of the raw material. In addition, expertise in supply chain management is weak and no suitable software is available.