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Tag Archive 'machine-learning'

Stellenausschreibung Universität Heidelberg – GIScience
Wissenschaftliche Mitarbeiter:in Geoinformatik - Projekt GeCO

GeCO: Generating high-resolution CO2 maps by Machine Learning-based geodata fusion
Du hast Interesse an Klimawandel, Treibhausgasemissionen und innovativen Geoinformatik-Methoden?
Im Rahmen des vom Heidelberg Center for the Environment (HCE) durch die Exzellenzstrategie geförderten Kooperationsprojektes GeCO suchen wir baldmöglichst nach einer wissenschaftlichen Mitarbeiter:in (m/f/d). Die Abteilung Geoinformatik entwickelt [...]

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Recently a new project has been starting in the context of Climate Change Action research:
GeCO: Generating high-resolution CO2 maps by Machine Learning-based geodata fusion and atmospheric transport modelling
The spatiotemporal distribution of greenhouse gases and their sources on Earth has so far been considered mainly at relatively coarse resolutions. There is a lack of sound [...]

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The AGILE 2021 conference is taking place this week. It is the the 24rd AGILE conference on GIScience. AGILE is the Association of Geographic Information Laboratories in Europe and the 2021 conference is for the first time held as a virtual conference. As in earlier years GIScience Heidelberg and HeiGIT are contributing to the conference with several [...]

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(English version below)
Die Folgen des Klimawandels sind besonders stark in den höheren Breiten unseres Planeten zu spüren. Die Arktis erwärmt sich derzeit überdurchschnittlich schnell. Dies führt zum Auftauen von Permafrost (dauerhaft gefrorenen Böden) mit ernsthaften Konsequenzen für das arktische Ökosystem. Etwa ein Viertel der Landfläche in der Nördlichen Hemisphäre ist durch Permafrost gekennzeichnet. Darin sind [...]

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A couple of viruses are of global interest with respect to human health and well-being. These pathogens include the novel coronavirus SARS-CoV-2, Dengue, Chikungunya, Yellow fever, Zika and Ebola. These viruses show interesting spatio-temporal dynamics. Improved understanding of the driving and moderating factors will help to cope with these pathogens.
The recently funded new project geoEpi [...]

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Lukas Winiwarter of the 3DGeo group was invited by the Austrian Society of Surveying and Geoinformation (OVG) to give a talk on the application of deep learning on point clouds, which took place on March 24. In his talk, Lukas presented four different state-of-the-art approaches to consider the irregular, unordered structure of point clouds, which [...]

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During the EuroSDR workshop we will present our OSMlanduse product (earlier post) to the land use (LU) and land cover community (LC) and highlight class accuracies and a benchmark comparison towards existing national authoritative products. Accuracy estimated to be presented are based on more than 7k reference points collected in the past month through a [...]

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As a user‐generated map of the whole world, OpenStreetMap (OSM) provides valuable information about the natural and built environment. However, the spatial heterogeneity of the data due to cultural differences and the spatially varying mapping process makes the extraction of reliable information difficult. A newly published study investigates the variability of association rules extracted from [...]

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This week 19.-23.10. the autumn school Urban Data Science takes place as a online course set up together by GIScience Heidelberg and the Institute for Transport Studies (IfV), KIT. It is part of an ongoing application for a HeiKA (Heidelberg Karlsruhe Strategic Partnership) project that would foster joint teaching modules between GIScience HD and IfV [...]

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We launched a validation campaign of our new 10meter resolution OSMlanduse product for the member states of the European Union. Please contribute to the validation here. A technique where contributions are checked against each other is implemented to promote quality of information. The mapathon comes in four themes: nature, urban, agriculture or expert.
While the expert campaign [...]

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