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Tag Archive 'OSMlanduse'

Large-scale mapping activities can benefit from the vastly increasing availability of earth observation (EO) data, especially when combined with volunteered geographical information (VGI) using machine learning (ML). High-resolution maps of inland surface water bodies are important for water supply and natural disaster mitigation as well as for monitoring, managing, and preserving landscapes and ecosystems.
In a [...]

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HeiGIT wants to serve you even better. Therefore we are conducting user feedback surveys regarding our various services.
If you have ever used one of our OpenStreetMap based Online Services (or will do so now) for whatever purpose, we’d be very happy if you took the time and filled out the respective survey.
THANK YOU! We will [...]

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The Horizon 2020 LandSense project was concluded successful. Please find a selection of the produced publications and deliverables here. The project has enabled our group to pursue quality aspects of voluntarily collected geo information data and to ramp up efforts related to OSMlanduse.
Together with the University of Nottingham (Giles Foody) and Institut national de l’information géographique [...]

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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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Am am 29.10.20, 16:30 Uhr veranstaltet das Netzwerk Geoinformation der Metropolregion Rhein-Neckar GeoNet.MRN zum Thema:
Flächennutzung und Flächenmanagement: Ein Geoinformation Meetup
Teilnahme: Kostenlos und ohne Anmeldung mit Teams unter diesem Link.
Themen des Meetups sind die Online-Beteiligung von Kommunen, Bürgern sowie Firmen und Institutionen im Bereich Flächenmanagement mit Fokus auf die Siedlungs- und Verkehrsentwicklung und [...]

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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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Find here a new update of the OSMlanduse.org map. By injecting known tags provided by OpenStreetMap (OSM) into a remote sensing feature space using deep learning, tags were predicted when absent thus creating a contiguous map - initially for the member states of the EU. By design our method can be applied when- and wherever [...]

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Recently a new DFG project proposal was accepted to the GIScience Research Group Heidelberg within the DFG priority programme VisVGI (Volunteered Geographic Information: Interpretation, Visualisation and Social Computing” [SPP 1894]). It is joint collaboration project together with Prof. Begüm Demir from TU Berlin.
IDEAL-VGI: Information Discovery from Big Earth Observation Data Archives by Learning from Volunteered [...]

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Last week, GIScience Heidelberg successfully held two collaborative workshops about OpenStreetMap (OSM) at the Department of Earth Observation in Jena. Dr. Chistian Thiel and his team from the University of Jena kindly organized the event. Three members of the GIScience Research Group and the Heidelberg Institute for Geoinformation Technology (HeiGIT), Dr. Michael Schultz, Benjamin Herfort [...]

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A new study has been published in the international open access journal Geo-spatial Information Science (GSIS, Taylor & Francis), that explores the land use/land cover (LULC) separability by the machine-generated and user-generated Flickr photo tags (i.e. the auto-tags and the user-tags, respectively), based on an authoritative LULC dataset for San Diego County in the United [...]

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