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.
2010
Authors
Miguel D. Mahecha Markus Reichstein Nuno Carvalhais Gitta Lasslop Holger Lange Sonia I. Seneviratne Rodrigo Vargas Christof Ammann M.Altaf Arain Alessandro Cescatti Ivan A. Janssens Mirco Migliavacca Leonardo Montagnani Andrew D. RichardsonAbstract
The respiratory release of carbon dioxide (CO2) from the land surface is a major flux in the global carbon cycle, antipodal to photosynthetic CO2 uptake. Understanding the sensitivity of respiratory processes to temperature is central for quantifying the climate–carbon cycle feedback. We approximated the sensitivity of terrestrial ecosystem respiration to air temperature (Q10) across 60 FLUXNET sites with the use of a methodology that circumvents confounding effects. Contrary to previous findings, our results suggest that Q10 is independent of mean annual temperature, does not differ among biomes, and is confined to values around 1.4 ± 0.1. The strong relation between photosynthesis and respiration, by contrast, is highly variable among sites. The results may partly explain a less pronounced climate–carbon cycle feedback than suggested by current carbon cycle climate models.
Abstract
Information retrieval from spatiotemporal data cubes is key to earth system sciences. Respective analyses need to consider two fundamental issues: First, natural phenomena fluctuate on different time scales. Second, these characteristic temporal patterns induce multiple geographical gradients. Here we propose an integrated approach of subsignal extraction and dimensionality reduction to extract geographical gradients on multiple time scales. The approach is exemplified using global remote sensing estimates of photosynthetic activity. A wide range of partly well interpretable gradients is retrieved. For instance, well known climate-induced anomalies in FAPAR over Africa and South America during the last severe ENSO event are identified. Also, the precise geographical patterns of the annual–seasonal cycle and its phasing are isolated. Other features lead to new questions on the underlying environmental dynamics. Our method can provide benchmarks for comparisons of data cubes, model runs, and thus be used as a basis for sophisticated model performance evaluations.
Authors
Tuula Kantola Mikko Vastaranta Xiaowei Yu Paivi Lyytikainen-Saarenmaa Markus Holopainen Mervi Talvitie Sanna Kaasalainen Svein Solberg Juha HyyppäAbstract
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.
Authors
Svein SolbergAbstract
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.
Authors
Tuula Kantola Mikko Vastaranta Xiaowei Yu Paivi Lyytikainen-Saarenmaa Markus Holopainen Mervi Talvitie Sanna Kaasalainen Svein Solberg Juha HyyppäAbstract
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.
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.
Authors
Tore SkrøppaAbstract
No abstract has been registered
Authors
Tore SkrøppaAbstract
No abstract has been registered
Authors
Tore SkrøppaAbstract
No abstract has been registered
Authors
Tore SkrøppaAbstract
No abstract has been registered