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.
2006
Forfattere
Aksel GranhusSammendrag
No abstract has been registered
Sammendrag
This analysis is based on climatic data and increment cores from about 550 Forest officers from latitude 58-70N and longitude 6-18E. The strength of the data is the high number of plots scattering over most of the Norway spruce forest area in Norway. Tree ring-widths were transformed to ring indices to remove age disturbances and strengthen the climatic signal on the tree growth.We used regression analyses to examine the annually growth responses of these ring indices against 42 monthly climatic variables. The climatic variables we used were mean month temperature, precipitation and Palmer drought severity index (PDSI) with a range from previous year July to current years August.The results showed some correlations of climate on growth, with the June weather as most important. The most important variable in the lowlands (altitude 500 m) of southeastern Norway was the June precipitation, and the June temperature in the rest of the country.
Sammendrag
This study is based on data from the Level I and from forest Officers plots. We combined three sets of data on growth, deposition and soil chemistry, totally 204 plots in south-eastern and mid-Norway. As response variable we used observed growth in % of estimated growth calculated from standard Norwegian growth models. In this way we filtered out the influence of site and stand properties as this were included in the model.The dependent deposition variable used was the N deposition from the national air and precipitation monitoring program. The dependent soil chemistry variables were N, C/N ratio, base saturation, pH, Al, and Ca/Al ratio. Soil chemistry variables should reflect the properties that most likely are influenced by S and N deposition, and that could influence the trees in the hypothesised ways.We used analyses of covariance as statistical method. Growth was positively correlated to nitrogen deposition and to soil nitrogen, and negatively correlated to the C/N ratio in the soil. Also, nitrogen deposition was positively correlated to soil nitrogen and negatively to soil C/N.It was concluded that N deposition probably has increased N availability and thereby growth in southernmost Norway with an order of magnitude around 25%. There were no relationships between growth and the soil acidification variables pH, base saturation, Al concentration or Ca/Al-ratio, and we concluded that no evidence for negative effects of soil acidification on forest growth was found.
Forfattere
Aksel GranhusSammendrag
No abstract has been registered
Sammendrag
We examined growth responses of Norway spruce using tree-ring series from increment cores and monthly climate variables over the period 19001998. The 1398 cores were selected from 588 plots scattered all over Norway. We correlated tree-ring indices with temperature, precipitation, Palmer drought severity index and length of the growing season.The weather in June had the largest influence on ring widths. However, two different, and almost opposite, response types were found: Tree growth was restricted by June precipitation in the lowlands in southeastern Norway, but by the June temperature in other regions and at high altitudes.In order to define the shift between these two main response types, we correlated response functions with various 30-year mean climatic variables, including humidity and aridity indices. The 30-year mean June temperature was the variable most clearly showing this shift in response, with a threshold at 1213C. At sites with normal temperature below this threshold, spruce responded positively to unusually warm and dry June months, and vice versa.
Sammendrag
In this study, we present a new method for single tree segmentation and characterization from a canopy surface model (CSM), and its corresponding point cloud, based on airborne laser scanning. The method comprises new algorithms for controlling the shape of crown segments, and for residual adjustment of the canopy surface model (CSM). We present a new criterion that measures the success of locating trees, and demonstrate how this criterion can be used for optimizing the degree of CSM smoothing. From the adjusted CSM segments, we derived tree height and crown diameter, and based on all first laser pulse measurements within the segments we derived crown-base height. The method was applied and validated in a Norway spruce dominated forest reserve having a heterogeneous structure. The number of trees automatically detected varied with social status of the trees, from 93 percent of the dominant trees to 19 percent of the suppressed trees. The RMSE values for tree height, crown diameter, and crown-base height were around 1.2 m, 1.1 m, and 3.5 m, respectively. The method overestimated crown diameter (0.8 m) and crown base height (3.0 m).
2005
Forfattere
Svein SolbergSammendrag
Forest damage will result in two general effects: defoliation and/or discolouration. The two available techniques in remote sensing of forests today, LiDAR and spectroscopy, are promising tools for monitoring these two, respectively. Merging data on foliar mass, estimated by LiDAR, with data on chlorophyll concentrations, estimated by spectroscopy, can provide data on chlorophyll mass pr area unit. Monitoring the temporal changes of this is likely to be a very good measure for variations in forest health.In order to check out the possibilities for this, we are now working on building relationships between foliar mass data and LiDAR data for single spruce trees. In total we have measurements of position and stem diameter on about 2000 trees distributed on 16 plots, where 64 trees are intensively sampled for estimating foliar mass, as well as crown size.We need to parameterize a relationship between the LiDAR data for each of these trees and their foliar mass (or leaf area). If we succeed to build this relationship, we will scale it up to provide foliar mass (or leaf area) estimates for every 10x10 m pixels in two SPOT images of the area.Together with a similar up-scaling of chlorophyll concentrations, based on spectroscopy, we will test the possibility of estimating chlorophyll mass per area from SPOT or other satellites. In addition, we have visually assessed data on crown density for all the trees, being a rough, but valuable data-set for validating the relationship.The work, being in progress now, includes several tasks:a) finding an appropriate canopy surface modelb) segmentation of treesc) estimating crown volume, and evt d) handling of smaller trees standing below (this is a heterogenous canopy layer forest) and e) handling of the relative influence of stem and branches.Additionally, we see some other benefits from using LiDAR together with airborne hyperspectral data and satellite data in general. Firstly, the combination of high resolution LiDAR and hyper-spectral data, is a good basis for separating the signals from ground vegetation and from the tree canopy. Secondly, LiDAR provides both a DTM and a canopy surface model, and they are two alternative surface models for the geo-referencing of other data, and for appropriate handling of effects of shadowing and obstacles from tall trees.
2004
Forfattere
Lars Sandved Dalen H. Danforth J. Einset Carl Gunnar Fossdal Aksel Granhus Øystein Johnsen Harald Kvaalen Nina Elisabeth Nagy P. Rinne Linda Ripel S. Torre Gunnhild Søgaard C. van der SchootSammendrag
No abstract has been registered
Sammendrag
No abstract has been registered
Sammendrag
Extensive monitoring of forest health in Europe has been carried out for two decades, based mainly on defoliation and discolouration. Together these two variables reflect chlorophyll amounts in the tree crown, i.e. as an indicator of foliar mass, and chlorophyll concentration in the foliage, respectively.In a current project we try to apply remote sensing techniques to estimate canopy chlorophyll mass, being a suitable forest health variable. So far, we limit this to Norway spruce only. LIDAR data here play an important role, together with optical and spectral data, either from survey flights or from satellites. We intend to model relationships between foliar mass and LIDAR data for sample trees, and then scale up this to foliar mass estimates for the entire LIDAR area.Similarly, we try to scale up chlorophyll concentrations in sample trees, by modelling a relationship between sample tree chlorophyll and hyper-spectral data. The estimates of foliar mass and chlorophyll concentrations are then aggregated to every 10x10 m pixel of a SPOT satellite scene which is also covered by airborne data, providing an up-scaled ground truth. If we are successful with this, it might be a starting point for developing a new nationwide forest health monitoring system in Norway.