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.
2017
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Johannes RahlfAbstract
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Björn KlimekAbstract
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Eva BrodAbstract
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Matthias KoeslingAbstract
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Ricardo Fonseca Werner Creixell Javier Maiguashca Victor Rueda-AyalaAbstract
Image analysis is essential through a wide range of scientific areas and most of them have one task in common, i.e. object detection. Thus automated detection algorithms had generated a lot of interest. This proposal identifies objects with similar features on a frame. The inputs are the image where to look at, and a single appearance of the object we are looking for. The object is searched by a sliding window of various sizes. A positive detection is given by a cascaded classifier that compares input patches from sliding window to the object model. The cascaded classifier has three stages: variance comparison, layers of pixel comparisons and patch correlation. Object model is a collection of templates which are generated from scales and rotations of the first appearance. This algorithm is capable to handle change in scale, in plane rotation, illumination, partial occlusion and background clutter. The proposed framework was tested on high cluttered background aerial image, for identifying palm oil trees. Promising results were achieved, suggesting this is a powerful tool for remote sensing image analysis and has potential applications for a wide range of sciences which require image analysis.
Authors
Jutta Kapfer Radim Hédl Gerald Jurasinski Martin Kopecký Fride Høistad Schei John-Arvid GrytnesAbstract
Background: Resurveying historical vegetation plots has become more and more popular in recent years as it provides a unique opportunity to estimate vegetation and environmental changes over the past decades. Most historical plots, however, are not permanentlymarked and uncertainty in plot location, in addition to observer bias and seasonal bias, may add significant errors to temporal change. These errorsmay havemajor implications for the reliability of studies on long-term environmental change and deserve closer attention of vegetation ecologists. Methods: Vegetation data obtained from the resurveying of non-permanently marked plots are assessed for their potential to study environmental change effects on plant communities and the challenges the use of such data have to meet. We describe the properties of vegetation resurveys, distinguishing basic types of plots according to relocation error, and we highlight the potential of such data types for studying vegetation dynamics and their drivers. Finally, we summarize the challenges and limitations of resurveying non-permanently marked vegetation plots for different purposes in environmental change research. Results and conclusions: Re-sampling error is caused by three main independent sources of error: error caused by plot relocation, observer bias and seasonality bias. For relocation error, vegetation plots can be divided into permanent and non-permanent plots, while the latter are further divided into quasi-permanent (with approximate relocation) and non-traceable (with random relocation within a sampled area) plots. To reduce the inherent sources of error in resurvey data, the following precautions should be followed: (i) resurvey historical vegetation plots whose approximate plot location within a study area is known; (ii) consider all information available from historical studies in order to keep plot relocation errors low; (iii) resurvey at times of the year when vegetation development is comparable to the historical survey to control for seasonal variability in vegetation; (iv) retain a high level of experience of the observers to keep observer bias low; and (v) edit and standardize data sets before analyses.
Authors
Branko Ćupina Svetlana Vujić Dorde Krstić Branko Djurić Sali Aliu Maja Manojlović Ranko Čabilovski Peder LombnæsAbstract
Three perennial legumes (alfalfa, red clover and birdsfoot trefoil) and four cool-season perennial grasses (orchardgrass, tall fescue, Italian ryegrass and red fescue) were grown in legume–grass combinations and in pure stands of individual species, at three locations in the West Balkan region (Novi Sad, Banja Luka and Pristina) in the period from 2012 to 2015. The study evaluated dry matter yield, legume–grass–weed proportion and forage quality. High annual forage yield of legume–grass mixtures can be obtained with proper selection of species and an appropriate legume–grass ratio. However, high and stable yield, particularly in the case of grasses, depends on the amount and schedule of precipitation as well as the cutting time. The mixtures and legume pure stands achieved better forage production both per cutting and on the annual basis and had better forage quality than grass pure stands.
Abstract
No abstract has been registered
Abstract
No abstract has been registered