Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2021
Sammendrag
Norske klimaforskere kan ha kjent til menneskeskapt global oppvarming fra tidlig på 1960-tallet. Men først på 1980-tallet ble det et høyaktuelt tema. Hvorfor tok det så lang tid?
Sammendrag
In agricultural catchments, hydrological processes are highly linked to particle and nutrient loss and can lead to a degradation of the ecological status of the water. Global warming and land use changes influence the hydrological regime. This effect is especially strong in cold regions. In this study, we used long-term hydrological monitoring data (22–26 years) from small agricultural catchments in Norway. We applied a Mann–Kendall trend and wavelet coherence analysis to detect annual and seasonal changes and to evaluate the coupling between runoff, climate, and water sources. The trend analysis showed a significant increase in the annual and seasonal mean air temperature. In all sites, hydrological changes were more difficult to detect. Discharge increased in autumn and winter, but this trend did not hold for all catchments. We found a strong coherence between discharge and precipitation, between discharge and snow water equivalent and discharge and soil water storage capacity. We detected different hydrological regimes of rain and snow-dominated catchments. The catchments responded differently to changes due to their location and inherent characteristics. Our results highlight the importance of studying local annual and seasonal changes in hydrological regimes to understand the effect of climate and the importance for site-specific management plans.
Sammendrag
The aim of this study was to demonstrate how aquacultural sludge can be processed and utilized as an organic nutrient solution (ONS) for hydroponic lettuce production. By using a previous developed method, approximately 80% of the processed sludge was reclaimed as a clear, nutrient-rich solution. The performance of the recovered nutrient solution on lettuce growth was assessed in a nutrient film hydroponic system. The results were compared to the results obtained using a conventional nutrient solution (CNS). Yield, fresh weight, water consumption, and nutrient and heavy metal content in leaf tissue were measured. In spite of a 16% lower average fresh weight obtained in ONS compared to the weight obtained in CNS, there was no statistical difference of the yield of lettuce among the two nutrient solutions. After the cultivation period, 90% of the lettuce heads grown in ONS exceeded the marked weight of 150 g. Foliar analysis revealed a similar or higher content of all nutrients, except of magnesium and molybdenum in the leaves of lettuce grown in the ONS compared to lettuce grown in the CNS. This study shows that nutrients recovered from aquacultural sludge can be utilized as fertilizer, thereby reducing the dependency on mineral fertilizer in hydroponic and aquaponic systems.
Sammendrag
Rapid technological advances in airborne hyperspectral and lidar systems paved the way for using machine learning algorithms to map urban environments. Both hyperspectral and lidar systems can discriminate among many significant urban structures and materials properties, which are not recognizable by applying conventional RGB cameras. In most recent years, the fusion of hyperspectral and lidar sensors has overcome challenges related to the limits of active and passive remote sensing systems, providing promising results in urban land cover classification. This paper presents principles and key features for airborne hyperspectral imaging, lidar, and the fusion of those, as well as applications of these for urban land cover classification. In addition, machine learning and deep learning classification algorithms suitable for classifying individual urban classes such as buildings, vegetation, and roads have been reviewed, focusing on extracted features critical for classification of urban surfaces, transferability, dimensionality, and computational expense.
Sammendrag
The purpose of this research is to develop a method for estimating the spatially and temporally resolved moisture content of thermally modified Scots pine (Pinus sylvestris) using remote sensing. Hyperspectral time series imaging in the NIR wavelength region (953–2516 nm) was used to gather information about the absorbance of eight thermally modified pine samples each minute as they dried during a period of approximately 20 h. After preprocessing the collected spectral data and identifying an appropriate wavelength selection, partial least squares regression (PLS) was used to map the absorbance data of each pine sample to a distribution of moisture contents within the samples at different time steps during the drying process. To enable separate studying and comparison of the drying dynamics taking place within the early- and latewood regions of the pine samples, the collected images were spatially segmented to separate between early- and latewood pixels. The results of the study indicate that the 1966–2244 nm region of a NIR spectrum, when preprocessed with extended multiplicative scatter correction and first order derivation, can be used to model the average moisture content of thermally modified pine using PLS. The methods presented in this paper allows for estimation and visualization of the intrasample spatial distribution of moisture in thermally modified pine wood.
Forfattere
Kjetil FadnesSammendrag
Det er ikke registrert sammendrag
Forfattere
Bjørn Egil FløSammendrag
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Forfattere
Bjørn Egil FløSammendrag
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Forfattere
Annbjørg KristoffersenSammendrag
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Sammendrag
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