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Category Archive for 'VGI Group'

A paper for the Academic Track of the State of the Map Conference, Milan, has been accepted. We are looking forward to discuss with you following aspects:
A growing number of studies analyzes OSM data, its contributors, usage, and quality.
Such studies were mostly limited to analyzing either small samples of the OSM database or to simple [...]

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Over the last years, the growing OpenStreetMap (OSM) database repeatedly proved its potential for various use cases, including disaster management. Disaster mapping activations show increasing contributions, but oftentimes raise questions related to the quality of the provided Volunteered Geographic Information (VGI).
In order to better monitor and understand OSM mapping and data quality, HeiGIT developed a [...]

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Several geospatial applications require comprehensive semantic information from points-of-interest (POIs). However, this information is frequently dispersed across different collaborative mapping platforms. Surprisingly, there is still a research gap on the conflation of POIs from this type of geo-dataset. In a recent paper by Novack et al. (2018), we focus on the matching aspect of POI [...]

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The ohsome OpenStreetMap history analytics platform, which is currently developed at HeiGIT, will make OSM’s full-history data more easily accessible. We are pleased to announce that we are coming closer to reaching our objectives, hereby sharing a preview of the first ohsome web dashboard. Our dashboards will allow you to explore [...]

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The big spatial data analytics team at HeiGIT is currently developing the ohsome OpenStreetMap history analytics platform. Our aim is to make OSM’s full-history data more easily accessible for various kinds of data analytics tasks on a global scale.
OpenStreetMap (OSM) is a freely available map of the world to which everyone may contribute geographic information. [...]

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Crowdsourcing has been widely applied to extract information from 2D geodata sources such as satellite imagery. In this new study published in the ISPRS Journal of Photogrammetry and Remote Sensing we apply this technique to the growing field of 3D point cloud analysis. This work has been conducted in our 3D-MAPP Project which was funded [...]

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Land use data created by humans (OSM) was fused with satellite remote sensing data, resulting in a conterminous land use data set without gaps. The first version is now available for all Germany at OSMlanduse.org.
When human input (OSM data) was absent a machine generated missing land use information learning from human inputs and using remote [...]

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Recently, deep learning has been widely applied in pattern recognition with satellite images. Deep learning techniques like Convolutional Neural Network and Deep Belief Network have shown outstanding performance in detecting ground objects like buildings and roads, and the learnt deep features are further applied in some prediction tasks like poverty and population mapping. On the [...]

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The first State of Map Conference in Tanzania was organised by the tanzanian OSM community and the Ramani Huria Team based in Dar es Salaam from 8-10th December. The GIScience Research Group contributed to the program by introducing MapSwipe and organizing an workshop on OpenStreetMap and the use of QGIS. (Photo: @InnocentMaholi)

The conference brought together [...]

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GIScience/HeiGIT and disastermappers heidelberg have been proud supporters of the Humanitarian OpenStreetMap Team (HOT) for a couple of years already. Our GIScience/HeiGIT Team is contributing OSM related research, applications and services. The disastermappers furthermore organize mapathons, workshops and webinars, and thereby help to extend the mapping community and raise awareness about OpenStreetMap (OSM), possible applications [...]

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