Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2019
Abstract
Root and butt-rot (RBR) has a significant impact on both the material and economic outcome of timber harvesting, and therewith on the individual forest owner and collectively on the forest and wood processing industries. An accurate recording of the presence of RBR during timber harvesting would enable a mapping of the location and extent of the problem, providing a basis for evaluating spread in a climate anticipated to enhance pathogenic growth in the future. Therefore, a system to automatically identify and detect the presence of RBR would constitute an important contribution in addressing the problem without increasing workload complexity for the machine operator. In this study we developed and evaluated an approach based on RGB images to automatically detect tree-stumps and classify them as to the absence or presence of rot. Furthermore, since knowledge of the extent of RBR is valuable in categorizing logs, we also classify stumps to three classes of infestation; rot = 0%, 0% < rot < 50% and rot >= 50%. In this work we used deep learning approaches and conventional machine learning algorithms for detection and classification tasks. The results showed that tree-stumps were detected with precision rate of 95% and recall of 80%. Using only the correct output (TP) of the stump detector, stumps without and with root and butt-rot were correctly classified with accuracy of 83.5% and 77.5%. Classifying rot to three classes resulted in 79.4%, 72.4% and 74.1% accuracy for stumps with rot = 0%, 0% < rot < 50% and rot >= 50\%, respectively. With some modifications, the algorithm developed could be used either during the harvesting operation to detect RBR regions on the tree-stumps or as a RBR detector for post-harvest assessment of tree-stumps and logs.
Abstract
No abstract has been registered
Abstract
A novel method for age-independent site index estimation is demonstrated using repeated single-tree airborne laser scanning (ALS) data. A spruce-dominated study area of 114 km2 in southern Norway was covered by single-tree ALS twice, i.e. in 2008 and 2014. We identified top height trees wall-to-wall, and for each of them we derived based on the two heights and the 6-year period length. We reconstructed past, annual height growth in a field campaign on 31 sample trees, and this showed good correspondence with ALS based heights. We found a considerable increase in site index, i.e. about 5 m in the H40 system, from the old site index values. This increase corresponded to a productivity increase of 62%. This increase appeared to mainly represent a real temporal trend caused by changing growing conditions. In addition, the increase could partly result from underestimation in old site index values. The method has the advantages of not requiring tree-age data, of representing current growing conditions, and as well that it is a cost-effective method with wall-towall coverage. In slow-growing forests and short time periods, the method is least reliable due to possible systematic differences in canopy penetration between repeated ALS scans.
Abstract
No abstract has been registered
Abstract
No abstract has been registered
Abstract
The pine-dominated forests of Western Norway have been found to harbour viable populations of woodpeckers, including the highly specialized White-backed Woodpecker Dendrocopos leucotos. The aim of this study was to investigate to what extent there were any changes in frequencies of woodpeckers, in particular the White-backed Woodpecker and the Grey-headed Woodpecker Picus canus, by resurveying 60 plots (each 1 km2 ) originally surveyed during 1994/1995. The resurvey was performed in 2013/2014. The White-backed Woodpecker was found to be the most common woodpecker species in both time periods. The Grey-headed Woodpecker was found to have a statistically significant decline from 27% of the 60 plots in 1994/95 to only 12% in 2013/14. The other four species all increased in frequency; although none of those increased frequencies were found to be statistically significant. We discuss possible explanations to why pine forests in Western Norway constitute a valuable habitat for the White-backed Woodpecker at the same time as it has drastically declined in other parts of Norway and Western Europe. In general, the reduced frequency of Grey-headed Woodpecker is not fully understood, although we suggest that cold winters during the years prior to the surveys in 2013/14 may be an important factor.
Abstract
Carbon footprint over the life cycle is one of the most common environmental performance indicators. In recent years, several wood material producers have published environmental product declarations (EPDs) according to the EN 15804, which makes it possible to compare the carbon footprint of product alternatives. The objective of this study was to investigate the effect of service life aspects by comparing the carbon footprint of treated wood decking products with similar performance expectations. The results showed that the modified wood products had substantially larger carbon footprints during manufacturing than preservative-treated decking materials. Replacement of modified wood during service life creates a huge impact on life cycle carbon footprint, while maintenance with oil provided a large contribution for preservative-treated decking. Hence, service life and maintenance intervals are crucial for the performance ranking between products. The methodological issues to be aware of are: how the functional unit specifies the key performance requirements for the installed product, and whether full replacement is the best modeling option in cases where the decking installation is close to the end of the required service life.
Abstract
No abstract has been registered
Abstract
Surface albedo is an important physical attribute of the climate system and satellite retrievals are useful for understanding how it varies in time and space. Surface albedo is sensitive to land cover and structure, which can vary considerably within the area comprising the effective spatial resolution of the satellite-based retrieval. This is particularly true for MODIS products and for topographically complex regions, such as Norway, which makes it difficult to separate the environmental drivers (e.g., temperature and snow) from those related to land cover and vegetation structure. In the present study, we employ high resolution datasets of Norwegian land cover and structure to spectrally unmix MODIS surface albedo retrievals (MCD43A3 v6) to study how surface albedo varies with land cover and structure. Such insights are useful for constraining land cover-dependent albedo parameterizations in models employed for regional climate or hydrological research and for developing new empirical models. At the scale of individual land cover types, we found that the monthly surface albedo can be predicted at a high accuracy when given additional information about forest structure, snow cover, and near surface air temperature. Such predictions can provide useful empirical benchmarks for climate model predictions made at the land cover level, which is critical for instilling greater confidence in the albedo-related climate impacts of anthropogenic land use/land cover change (LULCC).
Abstract
No abstract has been registered