Daily multispectral observations from Envisats MERIS sensor are being combined with a sophisticated processing algorithm and powerful Grid computing to reveal global photosynthesis activity on land. This permits researchers to trace the state of health of terrestrial plant cover, identifying areas under stress and assessing damage from drought or fires.
An algorithm developed by the European Commissions Joint Research Centre (EC-JRC) in Ispra, Italy is the basis for global monthly photosynthesis maps derived from MERIS imagery. Their production represents a demanding data-processing task only made possible on a routine basis through the Earth Science Grid-On-Demand service available from ESRIN, the European Centre for Earth Observation, in Frascati.
Maps of anomalies in photosynthesis levels over European countries have then been produced by scientists at the Institute for Environment and Sustainability of EC-JRC, based on observations gathered from 1998 to 2002.
Mariangela D’Acunto | alfa
5000 tons of plastic released into the environment every year
12.07.2019 | Empa - Eidgenössische Materialprüfungs- und Forschungsanstalt
Climate impact of clouds made from airplane contrails may triple by 2050
27.06.2019 | European Geosciences Union
Scientists at the University Würzburg and University Hospital of Würzburg found that megakaryocytes act as “bouncers” and thus modulate bone marrow niche properties and cell migration dynamics. The study was published in July in the Journal “Haematologica”.
Hematopoiesis is the process of forming blood cells, which occurs predominantly in the bone marrow. The bone marrow produces all types of blood cells: red...
For some phenomena in quantum many-body physics several competing theories exist. But which of them describes a quantum phenomenon best? A team of researchers from the Technical University of Munich (TUM) and Harvard University in the United States has now successfully deployed artificial neural networks for image analysis of quantum systems.
Is that a dog or a cat? Such a classification is a prime example of machine learning: artificial neural networks can be trained to analyze images by looking...
An international research group led by scientists from the University of Bayreuth has produced a previously unknown material: Rhenium nitride pernitride. Thanks to combining properties that were previously considered incompatible, it looks set to become highly attractive for technological applications. Indeed, it is a super-hard metallic conductor that can withstand extremely high pressures like a diamond. A process now developed in Bayreuth opens up the possibility of producing rhenium nitride pernitride and other technologically interesting materials in sufficiently large quantity for their properties characterisation. The new findings are presented in "Nature Communications".
The possibility of finding a compound that was metallically conductive, super-hard, and ultra-incompressible was long considered unlikely in science. It was...
An interdisciplinary research team at the Technical University of Munich (TUM) has built platinum nanoparticles for catalysis in fuel cells: The new size-optimized catalysts are twice as good as the best process commercially available today.
Fuel cells may well replace batteries as the power source for electric cars. They consume hydrogen, a gas which could be produced for example using surplus...
The fly agaric with its red hat is perhaps the most evocative of the diverse and variously colored mushroom species. Hitherto, the purpose of these colors was...
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