Tag: data fusion
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Stellenausschreibung Geoinformatik Heidelberg – Project GeCO: Generating high-resolution CO2 maps by Machine Learning-based geodata fusion
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…
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New Project: GeCO: Generating high-resolution CO2 maps by Machine Learning-based geodata fusion and atmospheric transport modelling
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…
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Multisource and Multitemporal Data Fusion in Remote Sensing: A Comprehensive Review of the State of the Art
The recent, sharp increase in the availability of data captured by different sensors, combined with their considerable heterogeneity, poses a serious challenge for the effective and efficient processing of remotely sensed data. Such an increase in remote sensing and ancillary data sets, however, opens up the possibility of utilizing multimodal data sets in a joint…
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Hyperspectral and LiDAR Fusion Using Deep Three-Stream Convolutional Neural Networks
Our feature paper “Hyperspectral and LiDAR Fusion Using Deep Three-Stream Convolutional Neural Networks” is now published online. Recently, convolutional neural networks (CNN) have been intensively investigated for the classification of remote sensing data by extracting invariant and abstract features suitable for classification. In this paper, a novel framework is proposed for the fusion of hyperspectral…
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EU Sentinel 2 osmlanduse.org fusion @ Toulouse Space show
Another chapter in machine human fusion land use device narrative: new Sentinel 2 osmlanduse.org product results based on OpenStreetMap plus Sentinel 2 data plus Machine Learning were presented at ToulouseSpaceShow 2018 during a European Space Agency (ESA) Research and User Support (RUS) event. Stay tuned: The new product will soon be available for all EU…
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RICH-VGI workshop at 18th AGILE conference, Lisbon
Our AGILE workshop called RICH-VGI (enRICHment of volunteered geographic information (VGI): Techniques, practices and current state of knowledge) was held on June 9, 2015 in Lisbon as part of the 18th AGILE Conference on Geographic Information Science of the Association of Geographic Information Laboratories in Europe (AGILE) with comparatively a large number of participants. The…
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Derivation of an OSM graph with TMC LCL traffic information to provide real time traffic services
Increasing traffic, especially in urban areas, leads to more and more infrastructural bottlenecks and congestion inside transportation networks. The aim is therefore to use existing transport networks as efficiently as possible. Current traffic and incident reports from the Traffic Message Channel (TMC) are an important source of information to provide further services in the context…
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Elucidating Environmental History with 100 Million Laser Beams
The Heidelberg University has published a press release about our work on laser scanning and subsurface geodata fused for 3D reconstruction of karst depressions on Crete. https://www.youtube.com/watch?v=_9jgPC6zGl8