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.
2025
Abstract
No abstract has been registered
Authors
Heikki Korpunen Yrjö Nuutinen Paula Jylhä Lars Eliasson Aksel Granhus Juha Laitila Stephan Hoffmann Timo MuhonenAbstract
• Overall forest management objectives and stand properties set the requirements and possibilities for harvesting in continuous cover forestry (CCF). • Harvester and forwarder operators play a key role in successful CCF harvesting, as both productivity and quality of work are essential factors in harvesting operations. • Optimal stand conditions improve work productivity on selection harvesting sites; harvested stem volume correlates well with work productivity in cutting, and density of remaining trees does not significantly reduce work productivity in forwarding. • Carefully executed group cutting and shelterwood harvesting can reduce the number of damaged remaining trees, which is beneficial for future tree generations. • Research-based information is needed about work productivity in harvesting, damage caused by harvesting, and optimisation of strip road and forest road networks for CCF.
Abstract
Study region: Six forest dominant catchments in Norway: two are micro- (< 10 km 2 meso- (< 1000 km 2 ) and two are macro-scale (> 10000 km 2 ), two are ) catchments. Study focus: This study focuses on the combined climate and forest impacts on streamflow, hydrological components as well as flood and low flow levels. In addition, the relative contributions of climate and forest impacts are distinguished. New hydrological insights for the region: This study provides the first hydrological projections in Norwegian catchments driven by both the climate projections and their corresponding forest projections. Due to warmer climate and higher precipitation under the Representative Concentration Pathway scenarios (RCP2.6 and RCP4.5), continuous increase in forest timber volume is projected in five out of six catchments. The combined effects of climate and forest development lead to median changes in annual streamflow ranging from 2 % to 8 %. Climate is the major driver of streamflow changes, and forest growth slightly offsets the increase in streamflow caused by climate and reduces runoff generation locally. Forest growth reduces the flood levels caused by climate by up to 3 % in all catchments except one with large clear-cutting areas. Forest growth leads to increase in low flow levels in three coniferous forest dominant catchments while it aggravates the low flow conditions in the catchments with high coverage of deciduous forest in the summer half-year.
Authors
Mostafa Hoseini Helle Ross Gobakken Stephan Hoffmann Csongor Horvath Johannes Rahlf Jan Bjerketvedt Stefano Puliti Rasmus AstrupAbstract
RoadSens is a platform designed to expedite the digitalization process of forest roads, a cornerstone of efficient forest operations and management. We incorporate stereo-vision spatial mapping and deep-learning image segmentation to extract, measure, and analyze various geometric features of the roads. The features are precisely georeferenced by fusing post-processing results of an integrated global navigation satellite system (GNSS) module and odometric localization data obtained from the stereo camera. The first version of RoadSens, RSv1, provides measurements of longitudinal slope, horizontal/vertical radius of curvature and various cross-sectional parameters, e.g., visible road width, centerline/midpoint positions, left and right sidefall slopes, and the depth and distance of visible ditches from the road’s edges. The potential of RSv1 is demonstrated and validated through its application to two road segments in southern Norway. The results highlight a promising performance. The trained image segmentation model detects the road surface with the precision and recall values of 96.8 and 81.9 , respectively. The measurements of visible road width indicate sub-decimeter level inter-consistency and 0.38 m median accuracy. The cross-section profiles over the road surface show 0.87 correlation and 9.8 cm root mean squared error (RMSE) against ground truth. The RSv1’s georeferenced road midpoints exhibit an overall accuracy of 21.6 cm in horizontal direction. The GNSS height measurements, which are used to derive longitudinal slope and vertical curvature exhibit an average error of 5.7 cm compared to ground truth. The study also identifies and discusses the limitations and issues of RSv1, which provide useful insights into the challenges in future versions.
2024
Abstract
No abstract has been registered
Authors
Heikki KorpunenAbstract
No abstract has been registered
Abstract
No abstract has been registered
Authors
Sylwia Wierzcholska Patryk Czortek Amy Elizabeth Eycott Fride Høistad Schei John-Arvid Grytnes Bogdan JaroszewiczAbstract
No abstract has been registered
Authors
Fride Høistad Schei Mie Prik Arnberg John-Arvid Grytnes Maren Stien Johansen Jørund Johansen Anna Birgitte Milford Anders Røynstrand Mari Mette TollefsrudAbstract
No abstract has been registered
Authors
Pablo Moreno-García Flavia Montaño-Centellas Yu Liu Evelin Y. Reyes-Mendez Rohit Raj Jha Robert P. Guralnick Ryan Folk Donald M. Waller Kris Verheyen Lander Baeten Antoine Becker-Scarpitta Imre Berki Markus Bernhardt-Römermann Jörg Brunet Hans Van Calster Markéta Chudomelová Deborah Closset Pieter De Frenne Guillaume Decocq Frank S. Gilliam John-Arvid Grytnes Radim Hédl Thilo Heinken Bogdan Jaroszewicz Martin Kopecký Jonathan Lenoir Martin Macek František Máliš Tobias Naaf Anna Orczewska Petr Petřík Kamila Reczyńska Fride Høistad Schei Wolfgang Schmidt Alina Stachurska-Swakoń Tibor Standovár Krzysztof Świerkosz Balázs Teleki Ondřej Vild Daijiang LiAbstract
No abstract has been registered