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Category Archive for 'VGI Group'

With the aim of rapidly estimating the updated state of the CORINE land-cover map at the frequency with which the OpenStreetMap (OSM) dataset is edited and extended, we propose an approach for automatically associating widely used OSM tags to Level 1 and Level 2 CORINE land-cover classes. This association is probabilistic and is undertaken based [...]

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Among semi-automated methods and pre-processed data products, crowdsourcing is another tool which can help to collect information on human settlements and complement existing data, yet it’s accuracy is debated. Whereas the potential of crowdsourced datasets for training of machine learning algorithms has been explored recently, only few work has been done towards utilizing machine learning [...]

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Accessibility is a widely discussed topic and there are a growing number of efforts to sensitise European cities and municipalities to the topic. A focus of such efforts is the facilitation of easy access to public places for everyone, including those with walking disabilities, balance and visual disorders, as well as people requiring the use [...]

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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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