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Articles containing the keyword 'precision'

Category : Research article

article id 10732, category Research article
Ana Aza, A. Maarit I. Kallio, Timo Pukkala, Ari Hietala, Terje Gobakken, Rasmus Astrup. (2022). Species selection in areas subjected to risk of root and butt rot: applying Precision forestry in Norway. Silva Fennica vol. 56 no. 3 article id 10732. https://doi.org/10.14214/sf.10732
Keywords: Norway spruce; Scots pine; growth modelling; precision forestry; root and butt rot severity; tree species selection
Highlights: We present the best species to plant on previously spruce-dominated sites with different site indexes and rot levels; We recommend planting Norway spruce on low-rot sites, Scots pine on higher-rot sites, and allowing natural regeneration on low site indexes; We demonstrate the Precision forestry method for determining the optimal tree species in heterogenous stands; In the case study, the method increased net present value by approximately 6% on average.
Abstract | Full text in HTML | Full text in PDF | Author Info

Norway’s most common tree species, Picea abies (L.) Karst. (Norway spruce), is often infected with Heterobasidion parviporum Niemelä & Korhonen and Heterobasidion annosum (Fr.) Bref.. Because Pinus sylvestris L. (Scots pine) is less susceptible to rot, it is worth considering if converting rot-infested spruce stands to pine improves economic performance. We examined the economically optimal choice between planting Norway spruce and Scots pine for previously spruce-dominated clear-cut sites of different site indexes with initial rot levels varying from 0% to 100% of stumps on the site. While it is optimal to continue to plant Norway spruce in regions with low rot levels, shifting to Scots pine pays off when rot levels get higher. The threshold rot level for changing from Norway spruce to Scots pine increases with the site index. We present a case study demonstrating a practical method (“Precision forestry”) for determining the tree species in a stand at the pixel level when the stand is heterogeneous both in site indexes and rot levels. This method is consistent with the concept of Precision forestry, which aims to plan and execute site-specific forest management activities to improve the quality of wood products while minimising waste, increasing profits, and maintaining environmental quality. The material for the study includes data on rot levels and site indexes in 71 clear-cut stands. Compared to planting the entire stand with a single species, pixel-level optimised species selection increases the net present value in almost every stand, with average increase of approximately 6%.

  • Aza, Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, PO Box 5003, NO-1432, Ås, Norway ORCID https://orcid.org/0000-0002-6416-6697 E-mail: anfe@nmbu.no (email)
  • Kallio, Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, PO Box 5003, NO-1432, Ås, Norway E-mail: maarit.kallio@nmbu.no
  • Pukkala, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: timo.pukkala@uef.fi
  • Hietala, Norwegian Institute of Bioeconomy Research, PO Box 115, NO-1431 Ås, Norway E-mail: ari.hietala@nibio.no
  • Gobakken, Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, PO Box 5003, NO-1432, Ås, Norway E-mail: terje.gobakken@nmbu.no
  • Astrup, Norwegian Institute of Bioeconomy Research, PO Box 115, NO-1431 Ås, Norway E-mail: rasmus.astrup@nibio.no
article id 10608, category Research article
Lennart Noordermeer, Erik Næsset, Terje Gobakken. (2022). Effects of harvester positioning errors on merchantable timber volume predicted and estimated from airborne laser scanner data in mature Norway spruce forests. Silva Fennica vol. 56 no. 1 article id 10608. https://doi.org/10.14214/sf.10608
Keywords: forest inventory; ALS; forest harvester; GNSS; precision forestry
Highlights: Timber volume was estimated using harvester and airborne laser scanner (ALS) data acquired with different scanners over eight years; The year of ALS acquisition did not have a significant effect on errors in timber volume estimates; Accuracies of timber volume estimates decreased significantly with increasing levels of positioning error; When using inaccurately positioned harvester data, larger grid cells are beneficial.
Abstract | Full text in HTML | Full text in PDF | Author Info

Newly developed positioning systems in cut-to-length harvesters enable georeferencing of individual trees with submeter accuracy. Together with detailed tree measurements recorded during processing of the tree, georeferenced harvester data are emerging as a valuable tool for forest inventory. Previous studies have shown that harvester data can be linked to airborne laser scanner (ALS) data to estimate a range of forest attributes. However, there is little empirical evidence of the benefits of improved positioning accuracy of harvester data. The two objectives of this study were to (1) assess the accuracy of timber volume estimation using harvester data and ALS data acquired with different scanners over multiple years and (2) assess how harvester positioning errors affect merchantable timber volume predicted and estimated from ALS data. We used harvester data from 33 commercial logging operations, comprising 93 731 harvested stems georeferenced with sub-meter accuracy, as plot-level training data in an enhanced area-based inventory approach. By randomly altering the tree positions in Monte Carlo simulations, we assessed how prediction and estimation errors were influenced by different combinations of simulated positioning errors and grid cell sizes. We simulated positioning errors of 1, 2, …, 15 m and used grid cells of 100, 200, 300 and 400 m2. Values of root mean square errors obtained for cell-level predictions of timber volume differed significantly for the different grid cell sizes. The use of larger grid cells resulted in a greater accuracy of timber volume predictions, which were also less affected by positioning errors. Accuracies of timber volume estimates at logging operation level decreased significantly with increasing levels of positioning error. The results highlight the benefit of accurate positioning of harvester data in forest inventory applications. Further, the results indicate that when estimating timber volume from ALS data and inaccurately positioned harvester data, larger grid cells are beneficial.

  • Noordermeer, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, NMBU, P.O. Box 5003, NO-1432 Ås, Norway E-mail: lennart.noordermeer@nmbu.no (email)
  • Næsset, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, NMBU, P.O. Box 5003, NO-1432 Ås, Norway E-mail: erik.naesset@nmbu.no
  • Gobakken, Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, NMBU, P.O. Box 5003, NO-1432 Ås, Norway E-mail: terje.gobakken@nmbu.no
article id 1340, category Research article
Mostafa Farhadi, Mulualem Tigabu, Per Christer Odén. (2015). Near Infrared Spectroscopy as non-destructive method for sorting viable, petrified and empty seeds of Larix sibirica. Silva Fennica vol. 49 no. 5 article id 1340. https://doi.org/10.14214/sf.1340
Keywords: larch; NIRS; OPLS; precision sowing; seed sorting; seed quality
Highlights: Near Infrared spectroscopy discriminates filled-viable, empty and petrified seeds of Larix sibirica with 98%, 82% and 87% accuracy, respectively based on spectral differences attributed to moisture and storage reserves; The classification accuracy reached 100% when sorting seeds into viable and non-viable class; The results demonstrate that NIR spectroscopy has great potential as non-destructive sorting technique to upgrade seed lot quality.
Abstract | Full text in HTML | Full text in PDF | Author Info

Larix sibirica Ledeb. is one of the promising timber species for planting in the boreal ecosystem; but poor seed lot quality is the major hurdle for production of sufficient quantity of planting stocks. Here, we evaluated the potential of Near Infrared (NIR) Spectroscopy for sorting viable and non-viable seeds, as the conventional sorting technique is inefficient. NIR reflectance spectra were collected from single seeds, and discriminant models were developed with Orthogonal Projections to Latent Structure – Discriminant Analysis (OPLS-DA). The computed model predicted the class membership of filled-viable, empty and petrified seeds in the test set with 98%, 82% and 87% accuracy, respectively. When two-class OPLS-DA model was fitted to discriminate viable and non-viable (empty and petrified seeds combined), the predicted class membership of test set samples was 100% for both classes. The origins of spectral differences between non-viable (petrified and empty) and viable seeds were attributed to differences in seed moisture content and storage reserves. In conclusion, the result provides evidence that NIR spectroscopy is a powerful non-destructive method for sorting non-viable seeds of Larix sibirica; thus efforts should be made to develop on-line sorting system for large-scale seed handling.

  • Farhadi, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, SE-230 53 Alnarp, Sweden E-mail: mostafa.farhadi@slu.se
  • Tigabu, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, SE-230 53 Alnarp, Sweden E-mail: mulualem.tigabu@slu.se (email)
  • Odén, Swedish University of Agricultural Sciences, Southern Swedish Forest Research Centre, P.O. Box 49, SE-230 53 Alnarp, Sweden E-mail: per.oden@slu.se
article id 459, category Research article
Tomi Tulokas, Jawdat Tannous. (2010). Research method and improvement of log rotation in sawmills. Silva Fennica vol. 44 no. 1 article id 459. https://doi.org/10.14214/sf.459
Keywords: yield; log rotation; sawing; optimizing; precision; standard deviation
Abstract | View details | Full text in PDF | Author Info
  • Tulokas, Centre for Timber Engineering, Edinburgh Napier University, 10 Colinton Road, Edinburgh EH10 5DT, UK E-mail: tomi.tulokas@lut.fi (email)
  • Tannous, School of Engineering and the Built Environment, Edinburgh Napier University, 10 Colinton Road, Edinburgh EH10 5DT, UK E-mail: jt@nn.uk
article id 478, category Research article
Ronald E. McRoberts, Daniel G. Wendt, Greg C. Liknes. (2005). Stratified estimation of forest inventory variables using spatially summarized stratifications. Silva Fennica vol. 39 no. 4 article id 478. https://doi.org/10.14214/sf.478
Keywords: bias; precision; classified satellite imagery; Internet; variance
Abstract | View details | Full text in PDF | Author Info
Large area natural resource inventory programs typically report estimates for selected geographic areas such as states or provinces, counties, and municipalities. To increase the precision of estimates, inventory programs may use stratified estimation, with classified satellite imagery having been found to be an efficient and effective basis for stratification. For the benefit of users who desire additional analyses, the inventory programs often make data and estimation procedures available via the Internet. For their own analyses, users frequently request access to stratifications used by the inventory programs. When data analysis is via the Internet and stratifications are based on classifications of even medium resolution satellite imagery, the memory requirements for storing the stratifications and the online time for processing them may be excessive. One solution is to summarize the stratifications at coarser spatial scales, thus reducing both storage requirements and processing time. If the bias and loss of precision resulting from using summaries of stratifications is acceptably small, then this approach is viable. Methods were investigated for using summaries of stratifications that do not require storing and processing the entire pixel-level stratifications. Methods that summarized satellite image-based 30 m x 30 m pixel stratifications at spatial scales up to 2400 ha produced stratified estimates of the mean that were generally within 5-percent of estimates for the same areas obtained using the pixel stratifications. In addition, stratified estimates of variances using summarized stratifications realized nearly all the gain in precision that was obtained with the underlying pixel stratifications.
  • McRoberts, North Central Research Station, USDA Forest Service, 1992 Folwell Avenue, Saint Paul, Minnesota, USA 5510 E-mail: rmcroberts@fs.fed.us (email)
  • Wendt, Region 9, USDA Forest Service, 626 East Wisconsin Avenue, Milwaukee, Wisconsin 53202, USA E-mail: dgw@nn.us
  • Liknes, North Central Research Station, USDA Forest Service, 1992 Folwell Avenue, Saint Paul, Minnesota, USA 5510 E-mail: gcl@nn.us

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