Svein Solberg

Research Professor

(+47) 928 53 902
svein.solberg@nibio.no

Place
Ås H8

Visiting address
Høgskoleveien 8, 1433 Ås

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Abstract

Clumping index (CI) is a measure of foliage aggregation relative to a random distribution of leaves in space. The CI can help with estimating fractions of sunlit and shaded leaves for a given leaf area index (LAI) value. Both the CI and LAI can be obtained from global Earth Observation data from sensors such as the Moderate Resolution Imaging Spectrometer (MODIS). Here, the synergy between a MODIS-based CI and a MODIS LAI product is examined using the theory of spectral invariants, also referred to as photon recollision probability (‘p-theory’), along with raw LAI-2000/2200 Plant Canopy Analyzer data from 75 sites distributed across a range of plant functional types. The p-theory describes the probability (p-value) that a photon, having intercepted an element in the canopy, will recollide with another canopy element rather than escape the canopy. We show that empirically-based CI maps can be integrated with the MODIS LAI product. Our results indicate that it is feasible to derive approximate p-values for any location solely from Earth Observation data. This approximation is relevant for future applications of the photon recollision probability concept for global and local monitoring of vegetation using Earth Observation data.

Abstract

Uganda designated 16% of its land as Protected Area (PA). The original goal was natural resources, habitat and biodiversity conservation. However, PAs also offer great potential for carbon conservation in the context of climate change mitigation. Drawing on a wall-to-wall map of forest carbon change for the entire Uganda, that was developed using two Digital Elevation Model (DEM) datasets for the period 2000–2012, we (1) quantified forest carbon gain and loss within 713 PAs and their external buffer zones, (2) tested variations in forest carbon change among management categories, and (3) evaluated the effectiveness of PAs and the prevalence of local leakage in terms of forest carbon. The net annual forest carbon gain in PAs of Uganda was 0.22 ± 1.36 t/ha, but a significant proportion (63%) of the PAs exhibited a net carbon loss. Further, carbon gain and loss varied significantly among management categories. About 37% of the PAs were “effective”, i.e., gained or at least maintained forest carbon during the period. Nevertheless, carbon losses in the external buffer zones of those effective PAs significantly contrast with carbon gains inside of the PA boundaries, providing evidence of leakage and thus, isolation. The combined carbon losses inside the boundaries of a large number of PAs, together with leakage in external buffer zones suggest that PAs, regardless of the management categories, are threatened by deforestation and forest degradation. If Uganda will have to benefit from carbon conservation from its large number of PAs through climate change mitigation mechanisms such as REDD+, there is an urgent need to look into some of the current PA management approaches, and design protection strategies that account for the surrounding landscapes and communities outside of the PAs.

Abstract

Monitoring changes in forest height, biomass and carbon stock is important for understanding the drivers of forest change, clarifying the geography and magnitude of the fluxes of the global carbon budget and for providing input data to REDD+. The objective of this study was to investigate the feasibility of covering these monitoring needs using InSAR DEM changes over time and associated estimates of forest biomass change and corresponding net CO2 emissions. A wall-to-wall map of net forest change for Uganda with its tropical forests was derived from two Digital Elevation Model (DEM) datasets, namely the SRTM acquired in 2000 and TanDEM-X acquired around 2012 based on Interferometric SAR (InSAR) and based on the height of the phase center. Errors in the form of bias, as well as parallel lines and belts having a certain height shift in the SRTM DEM were removed, and the penetration difference between X- and C-band SAR into the forest canopy was corrected. On average, we estimated X-band InSAR height to decrease by 7 cm during the period 2000–2012, corresponding to an estimated annual CO2 emission of 5 Mt for the entirety of Uganda. The uncertainty of this estimate given as a 95% confidence interval was 2.9–7.1 Mt. The presented method has a number of issues that require further research, including the particular SRTM biases and artifact errors; the penetration difference between the X- and C-band; the final height adjustment; and the validity of a linear conversion from InSAR height change to AGB change. However, the results corresponded well to other datasets on forest change and AGB stocks, concerning both their geographical variation and their aggregated values.

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Abstract

In the present study we applied X-band interferometric SAR (InSAR) data from the TanDEM-X mission, and investigated the relationship between InSAR height above ground and above-ground biomass (AGB) in a forest with very high biomass. We carried out this study in the East Usambara Mountains in Tanzania, with AGB ranging up to N1000 t/ha. Field inventory provided AGB data for 153 plots of 900 m2 in size. An airborne laser scanning (ALS) provided a DTM as well as AGB predictions for larger 8100 m2 cells over the entire study area. Three TanDEM-X acquisitions provided single-pass InSAR data, from which we generated a Digital Surface Models (DSM) and InSAR height by subtracting the ALS DTM. The results showed that proportionality may represent the relationship where AGB increased with 18.4 t/ha per m increase in InSAR height. The accuracy was low with RMSE = 203 t/ha (44%), which was partly attributable to small field plots and partly to a limited sensitivity of InSAR height to variations in basal area and stand density. An identical proportionality model, with less residual noise, was achieved by replacing the small field plots with the 8100 m2 cells having AGB predictions from ALS data.

Abstract

The use of digital aerial photogrammetry (DAP) for forest inventory purposes has been widely studied and can produce comparable accuracy compared with airborne laser scanning (ALS) in small, homogeneous areas. However, the accuracy of DAP for large scale applications with heterogeneous terrain and forest vegetation has not yet been reported. In this study we examined the accuracy of timber volume, biomass and basal area prediction models based on DAP and national forest inventory (NFI) data on a large area in central Norway. Two separate point clouds were derived from aerial image acquisitions of 2010 and 2013. Vegetation heights were extracted by subtracting terrain elevation derived from ALS. A large number of NFI sample plots (483) measured between 2010 and 2014 were used as reference data to fit linear models for timber volume, biomass and basal area with height metrics derived from the DAP data as explanatory variables. Variables describing the heterogeneous environmental and image acquisition conditions were calculated and their influence on the model accuracy was tested. The results showed that forest parameter prediction using DAP works well when applied to a large area. The model fits of the timber volume, biomass and basal area models were good with R2 of 0.80, 0.81, 0.81 and RMSEs of 41.43 m3 ha−1 (55% of the mean observed value), 32.49 t ha−1 (47%), 5.19 m2 ha−1 (41%), respectively. Only a small proportion of the variation could be attributed to the heterogeneous conditions. The inclusion of the relative sun inclination led to an improvement of the model RMSEs by 2% of the mean observed values. The relatively low cost and stability across large areas make DAP an attractive source of auxiliary information for large scale forest inventories.

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Abstract

The use of Interferometric Synthetic Aperture Radar (InSAR) data has great potential for monitoring large scale forest above ground biomass (AGB) in the tropics due to the increased ability to retrieve 3D information even under cloud cover. To date; results in tropical forests have been inconsistent and further knowledge on the accuracy of models linking AGB and InSAR height data is crucial for the development of large scale forest monitoring programs. This study provides an example of the use of TanDEM-X WorldDEM data to model AGB in Tanzanian woodlands. The primary objective was to assess the accuracy of a model linking AGB with InSAR height from WorldDEM after the subtraction of ground heights. The secondary objective was to assess the possibility of obtaining InSAR height for field plots when the terrain heights were derived from global navigation satellite systems (GNSS); i.e., as an alternative to using airborne laser scanning (ALS). The results revealed that the AGB model using InSAR height had a predictive accuracy of RMSE = 24.1 t·ha−1 ; or 38.8% of the mean AGB when terrain heights were derived from ALS. The results were similar when using terrain heights from GNSS. The accuracy of the predicted AGB was improved when compared to a previous study using TanDEM-X for a sub-area of the area of interest and was of similar magnitude to what was achieved in the same sub-area using ALS data. Overall; this study sheds new light on the opportunities that arise from the use of InSAR data for large scale AGB modelling in tropical woodlands.

Abstract

Interferometric RADAR imagery can play an important role in REDD (Reduced Emissions from Deforestation and Forest Degradation). Interferometric RADAR acquires stereo imagery from which we derive height data. The RADAR heights are located high up in the tree crowns. Height above ground is correlated to forest biomass. Height decreases represent logging, i.e. reduced carbon stock. Height increases represent tree growth, i.e. increased carbon stock.

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Abstract

There is evidence that recently occurring top dieback of Norway spruce (Picea abies (L.) Karsten) tress in southern Norway is associated with drought stress. We compared functional wood traits of 20 healthy looking trees and 20 trees with visual signs of top dieback. SilviScan technology was applied to measure cell dimensions (lumen and cell wall thickness) in a selected set of trunk wood specimens where vulnerability to cavitation (P50) data were available. The wall/lumen ratio ((t/b)²) was a quite good proxy for P50. Cell dimensions were measured on wood cores of all 40 trees; theoretical vulnerability of single annual rings could be thus estimated. Declining trees tended to have lower (t/b)² before and during a period of water deficit (difference between precipitation and potential evapotranspiration) that lasted from 2004 to 2006. The results are discussed with respect to genetic predisposition.

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Abstract

Background: A functional forest carbon measuring, reporting and verification (MRV) system to support climate change mitigation policies, such as REDD+, requires estimates of forest biomass carbon, as an input to estimate emissions. A combination of field inventory and remote sensing is expected to provide those data. By linking Landsat 8 and forest inventory data, we (1) developed linear mixed effects models for total living biomass (TLB) estimation as a function of spectral variables, (2) developed a 30 m resolution map of the total living carbon (TLC), and (3) estimated the total TLB stock of the study area. Inventory data consisted of tree measurements from 500 plots in 63 clusters in a 15,700 km2 study area, in miombo woodlands of Tanzania. The Landsat 8 data comprised two climate data record images covering the inventory area. Results: We found a linear relationship between TLB and Landsat 8 derived spectral variables, and there was no clear evidence of spectral data saturation at higher biomass values. The root-mean-square error of the values predicted by the linear model linking the TLB and the normalized difference vegetation index (NDVI) is equal to 44 t/ha (49 % of the mean value). The estimated TLB for the study area was 140 Mt, with a mean TLB density of 81 t/ha, and a 95 % confidence interval of 74–88 t/ha. We mapped the distribution of TLC of the study area using the TLB model, where TLC was estimated at 47 % of TLB. Conclusion: The low biomass in the miombo woodlands, and the absence of a spectral data saturation problem suggested that Landsat 8 derived NDVI is suitable auxiliary information for carbon monitoring in the context of REDD+, for low-biomass, open-canopy woodlands.

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Abstract

Top dieback in 40–60 years old forest stands of Norway spruce [Picea abies (L.) Karst.] in southern Norway is supposed to be associated with climatic extremes. Our intention was to learn more about the processes related to top dieback and in particular about the plasticity of possible predisposing factors. We aimed at (i) developing proxies for P50 based on anatomical data assessed by SilviScan technology and (ii) testing these proxies for their plasticity regarding climate, in order to (iii) analyze annual variations of hydraulic proxies of healthy looking trees and trees with top dieback upon their impact on tree survival. At two sites we selected 10 tree pairs, i.e., one healthy looking tree and one tree with visual signs of dieback such as dry tops, needle shortening and needle yellowing (n = 40 trees). Vulnerability to cavitation (P50) of the main trunk was assessed in a selected sample set (n = 19) and we thereafter applied SilviScan technology to measure cell dimensions (lumen (b) and cell wall thickness (t)) in these specimen and in all 40 trees in tree rings formed between 1990 and 2010. In a first analysis step, we searched for anatomical proxies for P50. The set of potential proxies included hydraulic lumen diameters and wall reinforcement parameters based on mean, radial, and tangential tracheid diameters. The conduit wall reinforcement based on tangential hydraulic lumen diameters ((t/bht)2) was the best estimate for P50. It was thus possible to relate climatic extremes to the potential vulnerability of single annual rings. Trees with top dieback had significantly lower (t/bht)2 and wider tangential (hydraulic) lumen diameters some years before a period of water deficit (2005–2006). Radial (hydraulic) lumen diameters showed however no significant differences between both tree groups. (t/bht)2 was influenced by annual climate variability; strongest correlations were found with precipitation in September of the previous growing season: high precipitation in previous September resulted in more vulnerable annual rings in the next season. The results are discussed with respect to an “opportunistic behavior” and genetic predisposition to drought sensitivity.

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Abstract

Forest inventories based on field sample surveys, supported by auxiliary remotely sensed data, have the potential to provide transparent and confident estimates of forest carbon stocks required in climate change mitigation schemes such as the REDD+ mechanism. The field plot size is of importance for the precision of carbon stock estimates, and better information of the relationship between plot size and precision can be useful in designing future inventories. Precision estimates of forest biomass estimates developed from 30 concentric field plots with sizes of 700, 900, …, 1900 m2, sampled in a Tanzanian rainforest, were assessed in a model-based inference framework. Remotely sensed data from airborne laser scanning (ALS) and interferometric synthetic aperture radio detection and ranging (InSAR) were used as auxiliary information. The findings indicate that larger field plots are relatively more efficient for inventories supported by remotely sensed ALS and InSAR data. A simulation showed that a pure field-based inventory would have to comprise 3.5–6.0 times as many observations for plot sizes of 700–1900 m2 to achieve the same precision as an inventory supported by ALS data.

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Abstract

Remotely sensed data from airborne laser scanning (ALS) and interferometric synthetic aperture radar (InSAR) can greatly improve the precision of estimates of forest resource parameters such as mean biomass and biomass change per unit area. Field plots are typically used to construct models that relate the variable of interest to explanatory variables derived from the remotely sensed data. The models may then be used in combination with the field plots to provide estimates for a geographical area of interest with corresponding estimates of precision using model-assisted estimators. Previous studies have shown that field plot sizes found suitable for pure field surveys may be sub-optimal for use in combination with remotely sensed data. Plot boundary effects, co-registration problems, and misalignment problems favor larger plots because the relative impact of these effects on the models of relationships may decline by increasing plot size. In a case study in a small boreal forest area in southeastern Norway (852.6 ha) a probability sample of 145 field plots was measured twice over an 11 year period (1998/1999 and 2010). For each plot, field measurements were recorded for two plot sizes (200 m2 and 300/400 m2). Corresponding multitemporal ALS (1999 and 2010) and InSAR data (2000 and 2011) were also available. Biomass for each of the two measurement dates as well as biomass change were modeled for all plot sizes separately using explanatory variables from the ALS and InSAR data, respectively. Biomass change was estimated using model-assisted estimators. Separate estimates were obtained for different methods for estimation of change, like the indirect method (difference between predictions of biomass for each of the two measurement dates) and the direct method (direct prediction of change). Relative efficiency (RE) was calculated by dividing the variance obtained for a pure field-based change estimate by the variance of a corresponding estimate using the model-assisted approach. For ALS, the RE values ranged between 7.5 and 15.0, indicating that approximately 7.5–15.0 as many field plots would be required for a pure field-based estimate to provide the same precision as an ALS-assisted estimate. For InSAR, RE ranged between 1.8 and 2.5. The direct estimation method showed greater REs than the indirect method for both remote sensing technologies. There was clearly a trend of improved RE of the model-assisted estimates by increasing plot size. For ALS and the direct estimation method RE increased from 9.8 for 200 m2 plots to 15.0 for 400 m2 plots. Similar trends of increasing RE with plot size were observed for InSAR. ALS showed on average 3.2–6.0 times greater RE values than InSAR. Because remote sensing can contribute to improved precision of estimates, sample plot size is a prominent design issue in future sample surveys which should be considered with due attention to the great benefits that can be achieved when using remote sensing if the plot size reflects the specific challenges arising from use of remote sensing in the estimation. That is especially the case in the tropics where field resources may be scarce and inaccessibility and poor infrastructure hamper field work.

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Abstract

The aim of this study was to determine whether forest clear-cuts during 2000–2011 could be detected as a decrease in surface height by combining Digital Surface Models (DSMs) from the Shuttle Radar Topography Mission (SRTM) and Tandem-X, and to evaluate the performance of this method using SRTM X- and C-band data as references representing the heights before logging. The study area was located in a Norway spruce-dominated forest estate in southeastern Norway. We interpolated 11-year DSM changes into a 10 m × 10 m raster, and averaged these changes per forest stand. Based on threshold values for DSM decreases we classified the pixels and stands into the categories “clear-cut” and “not clear-cut”, and compared this to a complete record of logged stands during 2000–2011. The classification accuracy was moderate or fairly good. A correct detection was achieved for 59%–67% of the clear-cut stands. Omission errors were most common, occurring in 33%–42% of the stands. Commission errors were found in 13%–21% of the clear-cut stands. The results obtained for X-band SRTM were only marginally better than for C-band. In conclusion, the combination of SRTM and Tandem-X has the potential of providing near global data sets for the recent 12 years’ logging, which should be particularly valuable for deforestation mapping.

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Abstract

We provide a demonstration of the new tomographic profiling (TP) technique, here applied to forestry for the first time. The portable ground-based synthetic aperture radar (GB-SAR) system was used to capture profiles of the vertical polarimetric backscattering patterns through a 7 m tall stand of Norway spruce trees. The TP scheme collects data as for normal SAR imaging, but with the antennae aligned in the along-track direction. Adaptive post-processing meant that each TP scan simultaneously captured along-track image transects over the incidence angle range 0°–60°. An important feature of the derived image products is that incidence angle is constant at every point within an image. The measured HH–VV height backscatter profiles were very similar, whilst the cross-/co-polarization ratio showed very little variation with height through the stand. Backscattering profiles showed closest agreement with the branch biomass distribution through the canopy, rather than with trunk or branch + trunk biomasses. Equivalent interferometric tree heights were estimated from the centre of mass of the backscatter-height distribution, which displayed increasing height with increasing incidence angle. There was no significant vertical separation between the cross- and co-polarization returns.

Abstract

There is a need for monitoring methods for forest volume, biomass and carbon based on satellite remote sensing. In the present study we tested interferometric X-band SAR (InSAR) from the Tandem-X mission. The aim of the study was to describe how accurate volume and biomass could be estimated from InSAR height and test whether the relationships were curvilinear or not. The study area was a spruce dominated forest in southeast Norway. We selected 28 stands in which we established 192 circular sample plots of 250 m2, accurately positioned by a Differential Global Positioning System (dGPS). Plot level data on stem volume and aboveground biomass were derived from field inventory. Stem volume ranged fromzero to 596 m3/ha, and aboveground biomass up to 338 t/ha.We generated 2 Digital Surface Models (DSMs) fromInSAR processing of two co-registered, HH-polarized TanDEM-X image pairs – one ascending and one descending pair.We used a Digital TerrainModel (DTM) from airborne laser scanning (ALS) as a reference and derived a 10 m × 10 m Canopy Height Model (CHM), or InSAR height model. We assigned each plot to the nearest 10 m × 10 m InSAR height pixel. We applied a nonlinear, mixed model for the volume and biomass modeling, and from a full model we removed effects with a backward stepwise approach. InSAR heightwas proportional to volume and aboveground biomass, where a 1 m increase in InSAR height corresponded to a volume increase of 23 m3/ha and a biomass increase of 14 t/ha. Root Mean Square Error (RMSE) values were 43–44% at the plot level and 19–20% at the stand level.

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Abstract

Airborne laser scanning data and corresponding field data were acquired from boreal forests in Norway and Sweden, coniferous and broadleaved forests in Germany and tropical pulpwood plantations in Brazil. Treetop positions were extracted using six different algorithms developed in Finland, Germany, Norway and Sweden, and the accuracy of tree detection and height estimation was assessed. Furthermore, the weaknesses and strengths of the methods under different types of forest were analyzed. The results showed that forest structure strongly affected the performance of all algorithms. Particularly, the success of tree detection was found to be dependent on tree density and clustering. The differences in performance between methods were more pronounced for tree detection than for height estimation. The algorithms showed a slightly better performance in the conditions for which they were developed, while some could be adapted by different parameterization according to training with local data. The results of this study may help guiding the choice of method under different forest types and may be of great value for future refinement of the single-tree detection algorithms.

Abstract

In South-east Norway, several scattered observations of reduced growth and dieback symptoms were observed over the last 20 years in 40-60 years old Norway spruce (Picea abies) trees. Typical symptoms start with yellowing in the top and subsequent dieback downwards from the top. These symptoms are often combined with bark beetle (Ips typographus), honey fungus (Armillaria spp.) infections, and a sudden decrease in diameter and height growth. After about 1-5 years, most of the symptomatic trees are dead.We selected 11 representative stands in six counties. In each stand all trees in ten 250 m2 plots were evaluated, in total about 4000 trees. In each of these 110 plots, one symptomatic and one non-symptomatic tree were investigated in more detail. We measured tree diameter, height, took increment cores and assessed crown condition, wounds, resin flow, stem cracks, bark beetle infection and Armillaria presence. In addition, internode lengths of the last 20 years were measured in two of the stands.Preliminary results of internode lengths and increment cores showed a sudden decrease of height and diameter growth in the symptomatic trees. Many of these trees had a secondary infection of bark beetles and Armillaria. Some years appear to be typical problem years for many of the trees. These years also correspond with summer drought, i.e. negative Palmer drought severity indexes which were estimated for each stand. In comparison, the non-symptomatic trees, growing close to the symptomatic ones, showed none or minor growth reductions and discolouration.Climate change and increased summer drought may worsen spruce dieback problems. Management adaptions are uncertain. We conclude that Norway spruce is sensitive to drought, which reduce the growth and weaken the health, and probably reduce the defence against secondary infections.

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Abstract

This study investigates the relationship between Leaf Area Index (LAI) reduction in pine stands caused by pine sawfly (Neodiprion sertifier) larva and reflectance change measured using multitemporal optical satellite data. The study was carried out in 552 Scots Pine (Pinus sylvestris)-dominated stands in southern Norway (60° 41′ N, 12° 18′ E). Post-damage Satellite Pour l'Observation de la Terre (SPOT) satellite data were calibrated to surface reflectance using reflectance products of the moderate-resolution imaging spectroradiometer (MODIS). Standwise reflectance change was then computed by subtracting a pre-damage SPOT image that had been relative calibrated to the post-damage image using histogram matching. The reflectance changes were related to changes in LAI obtained from multitemporal lidar data calibrated with field measurements made with a LiCOR LAI-2000 plant canopy analyser. The reduced needle biomass growth due to the insect damage caused an increase in reflectance on the order of 0.002–0.015 in the visible and short-wave infrared SPOT bands and a decrease of 0.01 in the near infrared (NIR) band compared with a large reference data set with normally developed stands. A cross-validated discriminant analysis showed that 79% of the damaged stands could be separated from the undamaged stands by using the SPOT data.

Abstract

Top dieback and mortality of Norway spruce is a particular forest damage that has severe occurrences in scattered forest stands in southeast Norway. As a part of a project to study the extent and causes of the damage we are working on an algorithm for automatic detection dead and declining spruce trees for an entire county, - Vestfold. The data set is aerial imagery. The county was covered in 2007. Preliminary tests showed a considerable confusion between dead trees and bare ground. In order to avoid this confusion we have had the imagery automatically processed into a photogrammetric digital surface model (DSM) and true orthophotos. The data set derived from this processing was a 5 layer file, containing blue, green, red, and near-infrared, as well as the height above ground of the canopy height model (a DSM normalized by the terrain height, nDSM)

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Abstract

There is a need for accurate inventory methods that produce relevant and timely information on the forest resources and carbon stocks for forest management planning and for implementation of national strategies under the United Nations Collaborative Program on Reduced Emissions from Deforestation and Forest Degradation in Developing Countries (REDD). Such methods should produce information that is consistent across various geographical scales. Airborne scanning Light Detection and Ranging (LiDAR) is among the most promising remote sensing technologies for estimation of forest resource information such as timber volume and biomass, while acquisition of three dimensional data with Interferometric Synthetic Aperture Radar (InSAR) from space is seen as a relevant option for inventory in the tropics because of its ability to “see through the clouds” and its potential for frequent updates at low costs. Based on a stratified probability sample of 201 field survey plots collected in a 960 km2 boreal forest area in Norway, we demonstrate how total above-ground biomass (AGB) can be estimated at three distinct geographical levels in such a way that the estimates at a smaller level always sum up to the estimate at a larger level. The three levels are (1) a district (the entire study area), (2) a village, local community or estate level, and (3) a stand or patch level. The LiDAR and InSAR data were treated as auxiliary information in the estimation. At the two largest geographical levels model-assisted estimators were employed. A model-based estimation was conducted at the smallest level. Estimates of AGB and corresponding error estimates based on (1) the field sample survey were compared with estimates obtained by using (2) LiDAR and (3) InSAR data as auxiliary information. For the entire study area, the estimates of AGB were 116.0, 101.2, and 111.3 Mg ha−1, respectively. Corresponding standard error estimates were 3.7, 1.6, and 3.2 Mg ha−1. At the smallest geographical level (stand) an independent validation on 35 large field plots was carried out. RMSE values of 17.1–17.3 Mg ha−1 and 42.6–53.2 Mg ha−1 were found for LiDAR and InSAR, respectively. A time lag of six years between acquisition of InSAR data and field inventory has introduced some errors. Significant differences between estimates and reference values were found, illustrating the risk of using pure model-based methods in the estimation when there is a lack of fit in the models. We conclude that the examined remote sensing techniques can provide biomass estimates with smaller estimated errors than a field-based sample survey. The improvement can be highly significant, especially for LiDAR.

Abstract

This study is a part of a larger project designed to find out the causes of top dieback symptoms in Norway spruce in SE Norway. Because sapwood tracheids constitute a water transport system while parenchyma serves as a reserve tissue (Sellin, 1991), the separation and quantification of the sapwood and heartwood may contribute to understanding of the healthy tree functioning. As the extent of sapwood is related to tree vitality, it reflects the tree growth, health and effect of environmental factors (Sandberg & Sterley, 2009). Therefore, the sapwood cross-sectional area is widely used as a biometric parameter indicating the tree vitality, although its estimation and evaluation is prone to scaling errors....

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Abstract

Climate change and rising temperatures have been observed to be related to the increase of forest insect damage in the boreal zone. The common pine sawfly (Diprion pini L.) (Hymenoptera, Diprionidae) is regarded as a significant threat to boreal pine forests. Defoliation by D. pini can cause severe growth loss and tree mortality in Scots pine (Pinus sylvestris L.) (Pinaceae). In this study, logistic LASSO regression, Random Forest (RF) and Most Similar Neighbor method (MSN) were investigated for predicting the defoliation level of individual Scots pines using the features derived from airborne laser scanning (ALS) data and aerial images. Classification accuracies from 83.7% (kappa 0.67) to 88.1% (kappa 0.76) were obtained depending on the method. The most accurate result was produced using RF with a combination of data from the two sensors, while the accuracies when using ALS and image features separately were 80.7% and 87.4%, respectively. Evidently, the combination of ALS and aerial images in detecting needle losses is capable of providing satisfactory estimates for individual trees.

Abstract

The airborne laser scanning (ALS) penetration rate, i.e. the ratio of ground echoes to total echoes, is a proxy for gap fraction. Hence, ALS has a potential for monitoring forest properties that are related to gap fraction, such as leaf area index, canopy cover and disturbance. Furthermore, two gap types may be distinguished: While a pulse that only produces a ground echo most likely hit a large, between-tree gap, a pulse that produces a ground echo as the last of several returns most likely hit smaller, within-canopy gaps. This may be utilized to distinguish between disturbance types such as defoliation and tree removal. However, the ALS penetration rate needs to be calibrated with gap fraction measurements in the field, because it is influenced by technical properties of the acquisition. The aim of this study was to quantify the magnitude of this influence, by comparing repeated acquisitions with different technical specifications. We had at hand 12 ALS acquisitions which could be combined into six pairs, from four spruce and pine dominated forests in Norway. We established 20x20 m grids, and for each grid cell we extracted three penetration variables: first echo penetration, last-of-many echo penetration, and total (i.e., first and last echo). We log-transformed the penetration variables (P1 and P2) from two laser acquisitions, and fitted the no-intercept, linear model log(P1) = log(P2), applying total least squares regression analysis. In a majority of the cases, the penetration variables were very similar, i.e. they deviated by <10%. For the first echo penetration the slopes varied from 0.87 to 1.07 and the R2 values ranged between 0.91 and 0.99. For the last-of-many echo penetration, there was generally weaker correspondence with slopes varying from 0.78 to 1.02, and R2 values ranging from 0.60 to 0.94. Finally, for the total penetration there was again stronger agreement with slopes in the range 0.83-1.03 and R2 values from 0.88 to 0.99. In conclusion, it seems that the penetration ability of different ALS scans in many cases are very similar, and further research may reveal ranges of standardized settings for which field inventory can be redundant.

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Abstract

The suitability of interferometric X-band radar for forest monitoring was investigated. Working in a spruce-dominated forest in southeast Norway, top height, mean height, stand density, stem volume, and biomass were related to space shuttle interferometric height above ground. A ground truth dataset was produced for each radar data pixel in the study area by combining a field inventory and automatic tree detection with airborne laser scanning data. Pixels were aggregated to forest stands. Interferometric height was strongly related to all of the five forest variables, and most strongly to top height with R-2 = 0.71 and RMSE = 13% at the pixel level and R-2 = 0.82 and RMSE = 5.6% at the stand level. Interferometric height was linearly related to stem volume and biomass up to 400 m(3)/ha and 200 t/ha, respectively, and RMSE was approximately 19% for both variables. These errors contain error components caused by the 3.5-year time lag between the radar acquisition and the laser scanning. It is concluded that interferometric X-band radar has potential for use in forest monitoring.

Abstract

There is an increasing need for forest resource monitoring methods, as more attention is paid to deforestation, bio-energy and forests as habitats. Most national forest inventories are based on networks of field inventory plots, sometimes together with satellite data, and airborne laser scanning (ALS) is increasingly used for local forest mapping. These methods are expensive to establish or carry out, and many countries, including some severely affected by deforestation, do not apply such methods.Satellite based remote sensing methods in use today are hampered by problems caused by clouds and saturation at moderate biomass levels. Satellite SAR is not hampered by cloud problems, and monitoring of canopy surface elevation, which is correlated to key forest resource variables, might be a future method in forest monitoring.We here present the main findings of three studies (Solberg et al. 2010, a, b, c) investigating the potential of interferometric SAR (InSAR) for forest monitoring, by describing the relationship between InSAR height above ground and key forest variables. We based this study on InSAR data from the Shuttle Radar Topographic Mission (SRTM) with its acquisition in February 2000. We obtained SRTM InSAR DEM data from DLR for two forest areas in Norway, and built a ground-truth from the combination of field inventory and ALS.The forest areas were dominated by Norway spruce and Scots pine. In each forest area we laid out a number of field inventory plots, where we recorded standard forest variables such as Dbh and tree height, and from this derived plot aggregated variables of top height, mean height, stand density (mean tree height divided by the mean tree spacing), volume and biomass. We used this to calibrate and validate ALS based models, from which we derived estimates of the same variables for each SRTM pixel. This served as reference data for the SRTM data.From the X-band SRTM digital surface model (DSM) image we subtracted a high quality digital terrain model (DTM) derived from the ALS data. This was based on an extraction of ground echoes from the data provider, and the elevations of these echoes were interpolated into a grid fitting the SRTM grid.This produced data on the RADAR echo height above ground (InSAR height), which we related to the forest variables. With digital stand maps we aggregated the variables to the stand level. The X-band microwaves penetrate a little into the canopy, and the InSAR height was on average about 1.2 m below the mean tree height. InSAR height was strongly related to all forest variables, most strongly to top height.Particularly valuable was that stem volume and biomass, ranging up to 400 m3/ha and 200 t/ha, respectively, were linearly related to InSAR height with an accuracy, RMSE, of 19% at the stand level. However, these relationships had an intercept, which represents the microwave penetration into the vegetation, and due to this the relationships were non-linear for forest stands having heights and biomass values close to zero.With a lower quality DTM derived from topographic maps, the relationships were weaker. However, as long as a forest variable is within the ranges of the linear relationship, any change in InSAR elevation would be proportional to a change in forest height, volume or biomass. And, any logging should be detectable as a sudden decrease in InSAR elevation.Hence, a forest monitoring based on X-band InSAR might be suitable even without a DTM. An application of space borne InSAR for forest monitoring would be feasible for large areas at low cost, whereas an ALS acquisition for a part of the area would serve as reference data for calibration.

Abstract

Four alternative airborne laser scanning (ALS) canopy penetration variables were compared for their suitability for mapping of gap fraction, leaf area index and disturbances in a Scots pine forest. The variables were based on either echo counting or intensity, and on either first or first and last echoes. ALS data and field-measured gap fraction and effective leaf area index (LAIe) were gathered before and after a severe insect defoliation by pine sawflies. LAIe is a commonly used form of leaf area index that is mathematically derived from gap fraction, and includes the areas of foliage, branches and trunks, and which is not corrected for the clumping of foliage. The ALS penetration variables were almost equally strongly related to field-measured gap fraction and LAIe. The estimated slopes in the LAIe models varied from 0.94 to 2.71, and had coefficient of determination R 2 values of 0.92–0.94. They were strongly correlated to each other (R 2 values of 0.95–0.98) and agreed fairly well for temporal changes of LAIe during the summer and the insect defoliation (R 2 values of 0.82–0.95). Counting of first and last echoes produced penetration rates close to the gap fraction, and this penetration variable was able to penetrate tree crowns. Ground-only echoes represented mostly between-tree gaps, and canopy-first-ground-last pulses represented mostly within-canopy gaps. However, the penetration variables based on first and last echoes suffered from the problem that a second echo might be impaired both in low and in tall canopies. In low canopies, two adjacent echoes from the same pulse would be too close in time to be separated by the sensor, while in tall canopies the pulse might apparently be fragmented down through the canopy. The intensity-based penetration variables needed to be supplemented with reflectance values, or at least the ratio between reflectance of the canopy and the ground, and this ratio was estimated from the data. The study demonstrated that one might be able to distinguish between disturbance types, e.g. between defoliation and cutting, by comparing alternative ALS penetration variables. Insect defoliation was dominated by an increase in within-canopy gaps and, correspondingly, the fraction of partly penetrating canopy-first-ground-last pulses. Tree removals from cutting were dominated by increases in between-tree gaps and the corresponding fraction of ground-only pulses.

Abstract

Climate change has been observed to be related to the increase of forest insect damages in the boreal zone. The prediction of the changes in the distribution of insect-caused forest damages has become a topical issue in the field of forest research. The common pine sawfly (Diprion pini L.) (Hymenoptera, Diprionidae) is regarded as a significant threat to boreal pine forests. Defoliation by D. pini caused severe growth losses and tree mortality of Scots pine (Pinus sylvestris L.) (Pinaceae). Logistic regression is commonly used in modelling the probability of occurrence of an event. In this study the logistic regression was investigated for predicting the needle loss of individual Scots pines (pine) using the features derived from airborne laser scanning (ALS) data. The defoliation level of 164 trees was determined subjectively in the field. Statistical ALS features were extracted for single trees and used as independent variables in logistic regression models. Classification accuracy of defoliation was 87.8% as respective kappa-value was 0.82. For comparison, only penetration features were selected and classification accuracy of 78.0% was achieved (kappa=0.56). Based on the results, it is concluded that ALS based prediction of needle losses is capable to provide accurate estimates for individual trees.

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Abstract

The aim of this study is to use airborne laser scanning (ALS) data to simulate synthetic aperture radar interferometry (InSAR) elevation data [digital elevation model (DEM)] from the spatial distribution of scatterers. A Shuttle Radar Topography Mission X-band DEM data set and an ALS data set from a spruce-dominated forest area are used. A 3-D grid of voxels is made from the spatial distribution of ALS first echoes. The slant angle penetration rate of the SAR microwaves (P-SAR) is simulated to be a function of the vertical ALS penetration rate (P-ALS), i.e., P-SAR = P-ALS(4). The InSAR DEM and heights above the ground are fairly well reproduced by the simulator. A total least squares regression model between the simulated and measured InSAR DEMs has an R-2 value of 0.99 and a slope of 1 : 1. By subtracting the ALS-based terrain heights (digital terrain model), we obtained InSAR heights, which were reproduced with an R-2 value of 0.78, a slope of 0.96, and a root-mean-square error of 2.3 m. With the simulator, it was demonstrated how a disturbance event would affect the InSAR height. Unfortunately, the relationship was curvilinear and concave, which means that the method is not very sensitive to weak disturbances. This might be partly overcome by using a more vertical incidence angle of the SAR microwaves. The simulator might be used for validation or ground truthing of the InSAR data, as well as gaining understanding of how vegetation changes affect the InSAR data.

Abstract

In European forests, standing stocks are currently higher than ever during the last decades, in part due to reduced logging or the abandonment of agricultural land. However, data from intensive monitoring plots reveal an increased growth even without direct human intervention.We used a set of 363 plots from 16 European countries to investigate the influence of environmental factors on forest growth: nitrogen, sulphur and acid deposition, temperature, precipitation and drought, for Norway spruce, Scots pine, common beech and European as well as sessile oak.We used existing information on site productivity, stand age and stand density to estimate expected growth. Relative tree growth, i.e., the ratio between actual growth within a five-year period and expected growth, was then related to environmental factors in a stepwise multiple regression.The results consistently indicate a fertilizing effect from nitrogen deposition, with roughly one percent increase in site productivity per kg of nitrogen deposition per ha and year, or 20 kg C fixation per kg N deposition. This was most pronounced for plots having soil C/N ratios above 25. We also found a positive albeit less clear relationship between relative growth and summer temperatures.From the study, we cannot conclude on any detrimental effects on growth from sulphur and acid deposition or from drought periods. A very recent study from the U.S., comprising 4800 plots and 24 tree species, confirms our results. However, we also show that the magnitude of N deposition effects on global forest C balance is currently a highly controversial matter, and comment on this debate. http://www.cef-cfr.ca/uploads/Colloque/Programme10_5.pdf

Abstract

The semi-individual tree crown approach (semi-ITC) was used to predict crown base heights (CBH) on the level of single crown segments based on airborne laser scanning (ALS) derived metrics. The root-mean-squared-differences (RMSD) on the segment level were smallest for spruce. However, they were larger than the standard deviation of the measured CBH for pine and birch. The RMSD values were also larger compared to other studies. This can in part be explained by the fact that the semi-ITC approach incorporates errors of the segmentation algorithm. As a consequence, all instead of only correctly identified trees were considered in modeling which results in more realistic RMSD values. After aggregating the individual segment predictions to the plot level, the RMSD values were smaller than the standard deviations of the field measurements and comparable to other studies. The relative RMSD values for birch, spruce, pine and all species were 51.61, 35.22, 49.28, and 13.89%, respectively.

Abstract

The semi-individual tree crown approach (semi-ITC) was used to predict crown base heights (CBH) on the level of single crown segments based on airborne laser scanning (ALS) derived metrics. The root-mean-squared-differences (RMSD) on the segment level were smallest for spruce. However, they were larger than the standard deviation of the measured CBH for pine and birch. The RMSD values were also larger compared to other studies. This can in part be explained by the fact that the semi-ITC approach incorporates errors of the segmentation algorithm. As a consequence, all instead of only correctly identified trees were considered in modeling which results in more realistic RMSD values. After aggregating the individual segment predictions to the plot level, the RMSD values were smaller than the standard deviations of the field measurements and comparable to other studies. The relative RMSD values for birch, spruce, pine and all species were 51.61, 35.22, 49.28, and 13.89%, respectively.

Abstract

Growth of Norway spruce (Picea abies) trees and nitrogen deposition were analysed at about 500 forest plots throughout Norway in six fiveyear periods from 1977 to 2006. Growth was calculated from five repeated calliper measurements of all trees during this period and using treering series from increment cores of a subsample of trees. From the growth data a `relative growth` variable was extracted, being the deviation in % between observed and expected growth rates. The expected growth was estimated from growth models based on site productivity, age and stand density at each plot. The plots were categorized into four age classes. The nitrogen deposition was estimated for each plot for the same five year periods by geographical interpolation of deposition observations at monitoring stations made by the Norwegian Institute for Air Research. Nitrogen deposition from 1977 to 2006 ranged from 1 to 24 kg/ha/yr at the study plots, with about 15 kg/ha/yr in the southernmost region and 3 kg/ha/yr in the northern region of Norway. For the entire 30year period we found a long term relationship between growth and nitrogen deposition, corresponding to a forest growth increase of 0.7% per kg total nitrogen deposition per hectare and year (r2 = 0.13). This is in line with studies carried out on other data sets and for shorter time periods. This apparent fertilizing effect was most pronounced for the youngest forest, while the effect was weak for the oldest forest. The growth increase was observed in the southernmost part of Norway, the region with the highest nitrogen deposition. However, the relationship between nitrogen deposition and growth varied considerably between the time periods. In two of the periods the relationship was slightly negative: these periods corresponded well with summer droughts occurring in the southernmost part of Norway. Drought, as well as other climatic factors, will influence the shortterm variations in forest growth and may obscure the fertilizing effect of nitrogen deposition in some periods. In conclusion, nitrogen deposition has most likely increased growth in Norway spruce in southern Norway. However, our study also shows that inferences from such correlative studies should be drawn with care if the growth period is shorter than 10–15 years because climatic factors produce temporal variations in the relationship between nitrogen deposition and forest growth.

Abstract

Nitrogennedfallet i skog virker gjødslende på skog, og fører derfor til økt karbonbinding. Så selv om nitrogennedfallet er en forurensning, så har det den positive effekt at det bidrar til å motvirke klimaendringene. Spørsmålet er hvor stor denne effekten er. Vi har i vårt EU/Forest Focus-prosjekt ”Assessment of the relative importance of nitrogen deposition, climate change and forest management on the sequestration of carbon at intensive monitoring plots in Europe” estimert denne effekten til å være omkring 30 kg ekstra bundet karbon for hver kg nitrogen som blir avsatt i skog...

Abstract

Insect-induced damages in forests are a major concern for timber production, landscape conservation and ecosystem research. Early detection methods based on remote sensing data can document the severity and spatial extent of ongoing attacks and might aid in designing mitigation measures or even prevention where necessary. In southeastern Norway, a large-scale insect defoliation of pine trees is ongoing. The larvae of the Pine sawfly Neodiprion sertifer reate it with its mass attacks during their feeding on needles in June and July. In the winter before the attack, egg galleries are evident in the needles. This provides a test case for early detection methods and remote sensing techniques for monitoring forest health....

Abstract

The European pine sawfly Neodiprion sertifer is a widely distributed defoliator of pines that can cause substantial growth losses over extensive areas. It attacks most species of twoneedle pines in its distribution area, and have occasional short-lived outbreaks that may cover up to 200.000 ha. In Norway we have had outbreak populations in the eastern part of the country since 2004, and in an ongoing research project we are evaluating aerial application of the Neodiprion sertifer nuclear polyhedrosis virus (NsNPV) to control Neodiprion sertifer....

Abstract

In European forests, standings stocks are currently increasing and are higher than ever during the last decades. This is due to a multitude of reasons; human impacts such as reduced logging or the abandonment of agricultural land are clearly among them. However, data from intensive monitoring plots reveal an increased growth even in the absence of direct human intervention. For this study, we used a set of 363 such plots from 16 European countries, which are a subset of the ICP-Forests Level II plots, and are typically rectangular areas with a size of 0.25 ha. We investigated the influence of environmental factors on forest growth. In particular, the role of nitrogen, sulphur and acid deposition, temperature, precipitation and drought was elucidated. The study focussed on the tree species Norway spruce, Scots pine, common beech and European as well as sessile oak. We used existing information on site productivity, stand age and stand density to estimate expected growth. Relative tree growth was then calculated as the ratio between actual growth, obtained within a five years observation period, and expected growth. The site productivity incorporates past environmental conditions and was either computed from site index curves, where we distinguished Northern, Central and Southern Europe variants, or was taken from expert estimates. The models explained between 18% and 39% of the variance. Site productivity and stand age were positively and negatively related to actual growth, respectively. The results indicated consistently a fertilizing effect from nitrogen deposition, with roughly one percent increase in site productivity per kg of nitrogen deposition per ha and year, most pronounced for plots having soil C/N ratios above 25. We also found a positive albeit less clear relationship between relative growth and summer temperatures. Other influences were uncertain. In particular, we cannot conclude on detrimental effects on growth from sulphur and acid deposition or from drought periods.

Abstract

In the context of an ongoing project on REMote sensing of FORest health (REM-FOR), we analyze airborne high-resolution hyperspectral images of a pine-dominated region in southeast Norway heavily attacked by the Pine sawfly Neodiprion sertifer, leading to severe defoliation. Leaf Area Index (LAI) is used as a proxy of the crown density, and comparing LAI maps from before and after the attack lead to indicators for damage extent. We discuss the application of the Forest Reflectance Model (FRT) of Kuusk and Nilson, which was designed for the application to (managed) Northern European Forests, to model the spectral response from the canopy. It is based on conventional forest inventory data, species-dependent parametrized crown shapes, canopy LAI, needle clumping index, and needle optical properties. Here, however, we run the model in an inverse mode, by iteratively minimizing the discrepancy between measured and simulated reflectances, and predicting the LAI, keeping known parameters of the model fixed. The LAI values are then compared to those obtained with either ground-based Licor LAI2000 measurements, or with airborne laser-scanning. Some preliminary results of this modelling concept for the case study are discussed.

Abstract

Forest health monitoring may be done with remote sensing. Satellite based SAR is one promising technology as it works day and night and with cloud cover, and because it is sensitive to 3D properties. We here apply an interferometry based XDEM approach, where we assumed that an increasing defoliation would cause an increasing X band penetration downwards into the canopy layer, and that the penetration depth is a function of the amount of leaf area index (LAI) penetrated. We had at hand data for a 4 km2 forest area, having an SRTM X and C band SAR data set from 2000; a discrete-return laser scanning data set from 2003; and ground based measurements of some hundred trees and a forest stand map from 2003. We initially adjusted the XDEM and CDEM using elevation data from some agricultural fields nearby the forest using an official, Norwegian DTM data base having a 25mx25m spatial resolution. All further analyses were carried out on a 10mx10m grid. With the laser data we obtained a DTM and a canopy surface model (CSM), where the latter was set to the 75 percentile of the DZ data in each grid cell. The X band penetrated about six m downwards into the canopy layer, which means that for all grid cells having a forest canopy lower than six m, the XDEM was around zero. With an increasing DSM from six m upwards, the DSM could be approximated by the linear function DSM = 6 + 0.91*XDEM, having a RMSE of 4.0 m. The laser data provided the possibility to estimate LAI in every grid cell and at any height in that cell. For every grid cell, an LAI value was estimated for the forest canopy being above the XDEM height, using the method of Solberg et al (2006), where LAI = C * ln(N/Nb), where LAI is effective LAI above a given height; C is a constant calibrated from ground based measurements with the value 2.0, N is the total number of laser pulses; and Nb is the number of laser pulses below the given height. The median LAIaboveX value was 1.42, and 25-75 percentile values being 0.86-2.15. Also, in order to have a more homogeneous data set we redid the analyses using only spruce dominated stands, and excluding all grid cells at stand borders. The latter was set as grid cells that had neighbour grid cells in a neighbour stand. This had however, only a minor influence on the results.

Abstract

The REMFOR project evaluates remote sensing data and methods for monitoring forest health using variation in leaf area index (LAI) as a primary measure of defoliation. A large-scale pine sawfly outbreak in Norway serves as a test case. An LAI map of the study area was derived from airborne LIDAR measurements before and after the insect attack to serve as ground truth for satellite image analysis. The method predicts LAI from laser penetration rates through the canopy layer in accordance with the Beer- Lambert law calibrated with point measurements of LAI with LICOR LAI-2000. Comparing two cloud-free SPOT scenes from September 2004 and September 2005 shows obvious visual patterns of defoliation in pine forests from the 2005 outbreak. Preliminary analysis shows that the insect defoliation caused an increase in middle-infrared (SPOT band4) reflectance and a decrease in SPOT NDVI, and both these responses may be used as a reasonable predictor of LAI loss as derived from laser scanning. MODIS NDVI data were gathered for the area over the period 2000-2006, and the Timesat algorithm is used to smooth the seasonal variation. The insect attack is evident from the smoothed NDVI data both as a reduction in the summer mean value, and as an alteration of the seasonal profile during the larvae feeding period in June and July. REMFOR also encompasses a range of other remote sensing data types, including GLAS LIDAR, SAR and hyperspectral data from both airborne and satellite platforms (e.g. Hyspex and Hyperion). Landsat TM is used to generate a tree species map.

Abstract

Acid rain emerged as an important environmental problem in China in the late 1970s. Many years of record economic growth have been accompanied by increased energy demand, greater coal combustion, and larger emissions of pollutants. As a result of significant emissions and subsequent deposition of sulfur, widespread acid rain is observed in southern and southwestern China. In fact, the deposition of sulfur is in some places higher than what was reported from the ?black triangle? in central Europe in the early 1980s. In addition, nitrogen is emitted from agriculture, power production, and a rapidly increasing number of cars. As a result, considerable deposition of pollutants occurs in forested areas previously thought to be pristine. Little is known about the effects of acid deposition on terrestrial and aquatic ecosystems in China. In this article, we present the current situation and what to expect in the future, largely on the basis of results from a five-year Chinese?Norwegian cooperative project. In the years ahead, new environmental challenges must be expected if proper countermeasures are not put into place.

Abstract

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.

Abstract

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.

Abstract

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.

Abstract

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).

Abstract

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.

Abstract

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.

Abstract

Summer drought, i.e. unusually dry and warm weather, has been a significant stress factor for Norway spruce in southeast Norway during the 14 years of forest monitoring. Dry and warm summers were followed by increases in defoliation, discolouration of foliage, cone formation and mortality. The causal mechanisms are discussed. Most likely, the defoliation resulted from increased needle-fall in the autumn after dry summers.During the monitoring period 19882001, southeast Norway was repeatedly affected by summer drought, in particular, in the early 1990s. The dataset comprised 455 Forest officers plots with annual data on crown condition and mortality. Linear mixed models were used for estimation and hypothesis testing, including a variancecovariance structure for the handling of random effects and temporal autocorrelation.

Abstract

Sulphur deposition is high at all IMPACTS sites and exceed maximum levels observed in Europe and North-America. Dry deposition equals or exceeds wet deposition. The IMPACTS data, in particular those from the remote Lei Gong Shan site clearly document long-range transport of air pollutants. Due to the actual and future energy combustion and emission strategy in China, the long-range transport of air pollutants may significantly increase with subsequent increased environmental damage in rural and remote areas in China. In addition to sulphur deposition, depositions of reactive nitrogen (nitric acid and ammonia) and calcium are also important and clearly demonstrate that pH alone is not a good indicator for acid deposition. High concentrations of ground level ozone, above critical levels for vegetation and forest, are observed at the Liu Xi He site in Guangdong province. Soil acidification gives rise to high concentrations of toxic aluminium in soil water at several sites. At the Tie Shan Ping site in Chongqing aluminium occurs at a level where long-term harmful effects on trees might be expected. Defoliation and mortality have been severe, however, fairly stable. Insect attacks are apparently a major cause, but enhanced insect attacks might be an indirect effect of health weakening due to acidification. Defoliation has been considerable also in Liu Chong Guan in Guiyang, while the three other catchments had minor defoliation only. High foliar nitrogen concentrations are seen in Lei Gong Shan in Guizhou and Cai Jia Tang in Hunan, accompanied by low P/N-ratios. Statistical tests of vegetation change, so far only implemented in Liu Chong Guan, revealed minor changes in number and abundances of vascular plants, but a significant decline in number of bryophytes. This decline is probably related to climatic year-to-year variations. Data from other catchments and longer time periods are needed to identify vegetation changes related to soil acidification or direct effects of air pollutants. Modelling results from Tie Shan Ping suggest that the currently planned 20% reduction in sulphur emissions is far from sufficient to avoid further acidification. As more data are generated, dose-response relationships, critical load estimates and model predictions will obviously be improved.

Abstract

This study shows that it is questionable if critical load modelling can contribute in the search for harmful effects of acid deposition on forest health at present. Critical loads for S and N deposition were calculated using the MAGIC and PROFILE models for more than 100 monitoring plots in Norway spruce forest in south-east Norway. The two models gave different results, likely due to differences in the models, including differences in the time spans applied. The PROFILE model gave considerably more plots with exceedance than the MAGIC model. At plots where the CL was exceeded, calcium/aluminium (Ca/Al) ratios in the soil solutions were low. However, very few of these plots had possible harmful values of the Ca/Al-ratio. More than 50 yr seems in most cases to be needed to bring Ca/Al ratios below 1.0. Present deposition was better correlated with measured forest condition variables such as crown condition and needle chemistry, than with modelled exceedance according to any of the two methods. The deposition of S and N was weakly, negatively correlated to foliar concentrations of P and Ca, and positively to foliar N concentrations and crown density.

Abstract

The Norwegian intensive monitoring programme of forest condition has recorded rainfall, throughfall and soil water data from 1986 at 16 forest plots. Using covariance analysis, this study has examined short term and episodic influences on soil water ionic concentration at three of the plots, and identified both seasonal and long-term temporal trends. Acidity has decreased in bulk precipitation and throughfall, and the concentrations of base cations in the organic soil horizon have increased. Nevertheless, there is evidence of continued acidification in the organic and mineral soil horizons, though of a small scale. The influence of sea salt and drought effects on soil water chemistry are examined, but found to be unimportant in causing acidification effects such as increased soil aluminium concentration.

Abstract

A 5-year Chinese-Norwegian research project was launched in the autumn of 1999. Forested sites for intensive studies are or will be established in the Chongqing municipality and in Guizhou, Hunan and Guangdong provinces in southern China. Previous studies have shown that harmful effects of acid deposition are likely to be most severe in this region. The research and monitoring sites shall give information about acidification mechanisms and effects on vegetation in order to improve policy oriented acidification models and critical load estimates as well as function as interdisciplinary training centers for acid rain research. Furthermore, the project shall improve the basis for developing an efficient regional acid rain monitoring system. At one site in Guizhou and one in Chongqing, research on soil and soilwater chemistry has been ongoing for several years. The forest at these sites appears to show symptoms of reduced vitality. The sensitivity of Chinese forests to acidification is uncertain and will be focused. Decision-makers should get an improved basis for optimal mitigation measures through the project.

Abstract

Relationships between crown density and growth of Norway spruce stands are presented, after removal of the effects of major natural influences. On 569 monitoring plots comprising 40 000 trees, crown density has been annually assessed during 1991 to 1996.Stand growth was determined from measurements of diameter and height in 1991 and in 1996. Various models explaining mean crown density and annual growth of the stands as a function of natural factors, like age and site index, were compared.The influence of the natural factors were then removed by recalculating crown density to residual values from one preferred model, and by recalculating growth to relative values given in percent of model predictions.Crown density and its residuals were positively correlated to growth. These relationships were weak in terms of their ability to explain variation (low R2). However, the various relationships consistently indicated that roughly 1% change in crown density corresponded to 1% change in growth. This relationship also included common spatial variation over Norway: a large part of southeast Norway had unexplained low crown density and unexplained low growth.Some other, smaller regional consistencies were found as well. The study supports the use of crown density assessments, and further it encourages the use of growth data in the search for major stress factors responsible for present forest condition.

Abstract

Relationships within stands between growth and crown condition are presented. The data set contained about 25000 trees on 500 plots. Growth of single trees was determined by diameter measurements in 1991 and 1996. Diameter increments were recalculated to relative values in two steps; firstly relative to their stem diameter, and secondly relative to reference values for trees in the same plot, having no defoliation or no discoloration. These relative increment values, or growth indices, were distributed on a scale common for all plots, rendering them influenced neither by site and stand properties, nor by social status of each tree. The correlation between crown condition and growth, although of moderate strength, did validate crown condition assessments as a meaningful, but rough measure of forest health or vigour. The relationships were concave, and considerable growth depressions were already found at slight levels of defoliation and discoloration. Growth approached zero as defoliation and discoloration increased towards 100%. These relationships applied for all plots, regardless of their site productivity, development stage or regeneration method

Abstract

This study describes how crown density changes were distributed within monitoring plots, in order to determine whether the reduced crown density observed could be explained as a worsening of a limited number of unhealthy or small and slightly suppressed trees.Crown density, yellowing, coning and stem diameter data were available from 447 selected plots comprising 22560 single trees all having a complete 1990-97 series of crown condition data.The eight years series of crown density for each tree were recalculated to two median values, for 1990-93 and 1994-97, in order to reduce the influence from short time variations including random errors. The scores for yellowing and amounts of cones were averaged over the years 1990-93. These variables, and diameter, were recalculated to rank indices within each plot.Relationships between variables were described by graphs and examined by correlation analyses of the indices. The trees tended to retain their internal ranking. Generally, when crown density for a plot has changed, most of the trees were affected. The most defoliated trees in each plots had the least negative changes, but except from that the trees were equally affected regardless of their yellowing, amount of cones, and their size.The results demonstrates that any effects from competition between the trees were sufficiently removed in the assessments, even in densely stocked stands.

Abstract

This study aims to evaluate the quality of crown density data, based on independent, pairwise tree assessments. The data originates from monitoring of forest health (crown condition) in Norway; 250 plots, comprising 12 000 individual trees of Norway spruc e, have been reassessed by a single observer during 1990-95. Of the trees, 2300 were controlled more than twice, providing the possibility of evaluating the quality of assessed temporal changes of crown density. True errors (standard deviation) are estima ted to be about 10% for single trees and 5% for plot means, while the real standard deviation of the differences were slightly higher. The errors of the temporal changes of crown density were of similar magnitude. Systematic differences in crown density w ere found between sites and plot types, partly resulting from observer bias. However, the results suggest that observer bias is really the result of each observer\"s personal style in assessment.

Abstract

On the local county monitoring plots located throughout Norway a reduction of crown density has been noted during 1988-97. The aim of this study was to determine whether this change could be attributed to normal effects from increased age on the plots.The dataset comprised around 580 plots and 27 000 single trees of Norway spruce, where each tree was provided with ten years of crown density measures. A two step approach was used, firstly to search for an expectancy for normal reduction of crown density by age derived from the dataset, and then to compare this with the actual reduction. The interpretation was somewhat complicated as the various results were tangled into each other.Highly significant correlations were found between crown density and age. The relationship indicated an annual reduction of crown density around 0.12%-units, however, the relationship varied both between years and between regions, and it was not possible to definitely determine whether the relationship was best described by linear or non-linear models.Of major importance here is that the relationship appeared to be influenced by the presence of stresses, which effects tended to be more severe in old stands. Based on this it seems questionable whether an expectancy for normal ageing can be properly defined. However, in the present study it could still be definitely determined that the mean crown density change of -0.41%-units annually was too negative to be attributed to normal ageing, as it was clearly below all the suggested expectancies from the various models.This suggests that the amount of stress in the period under study has been higher than normal, and this encourages the search for causal agents in further studies. Changes in silviculture may have had some influence.The results were valid for most of Norway, with the exception of western and northern regions. Crown density assessments are subjective, which may possibly give erroneous time trends, however, it is argued that this is less likely to be of major importance in the present data.

Abstract

Concentrations of pigments in needles of yellowish Norway spruce (Picea abies (L.) Karst.) trees suffering from either N, Mg or K deficiency in field sites in southeast Norway are reported. The yellowish trees had a considerably lower (roughly 50%) pigment concentration, as well as a lower chlorophyll/carotenoid ratio, compared to the green trees within the same sites. Yellowing was interpreted as a general bleaching of colour, as well as a slight turn from the green (chlorophylls) towards yellow (lutein). Concentrations of pigments were highly intercorrelated. N deficiency was especially associated with low a-carotene concentrations. This was interpreted as a-carotene being the most sensitive pigment to stress. However, this pigment might be specifically sensitive to N deficiency. Carbohydrate concentrations were slightly higher in yellowish trees.