Category: VGI Group
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DeepVGI: Deep Learning with Volunteered Geographic Information
Deep learning techniques, esp. Convolutional Neural Networks (CNNs), are now widely studied for predictive analytics with remote sensing images, which can be further applied in different domains for ground object detection, population mapping, etc. These methods usually train predicting models with the supervision of a large set of training examples. However, finding ground truths especially…
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CAP4Access Comes to a Close
On Tuesday 17th January, the CAP4Access/MyAccessible.EU came to a close after three years with the successful completion of the final European Commission review meeting in Brussels. Reviewers were highly pleased with the outcomes of the project, both on the technical and societal fronts. At GIScience in Heidelberg, through the EC FP7 project we have extended…
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Intrinsic quality assessment of building footprints data on OpenStreetMap
Recently some of our work on intrinsic VGI quality analysis has been published. In this work we propose a framework to assess the quality of OSM building footprints data without using any reference data. More specifically, the OSM history data will be examined regarding the development of attributes, geometries and positions of building footprints. In…
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GIScience Research Group support for Humanitarian OpenStreetMap team Fundraising Campaign
One main focus of the GIScience Research Group is the research and education with respect to advancing methods, technologies and applications of Volunteered Geographic Information – in particular OpenStreetMap – for applications from logistics to humanitarian aid. In this vein, the group has been also been supporting the work of the Humanitarian OpenStreetMap (HOT) team…
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A review of volunteered geographic information quality assessment methods
While Volunteered Geographic Information (VGI) is gaining more and more popularity and VGI datasets are being used in various projects, there are always concerns about the quality of them. During the past years several studies have been performed regarding VGI quality assessment by employing different methods/approaches. However, if one needs to evaluate the quality of…
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OpenRouteService 3.3 is going Mobile – Routing in the Americas, Gradients and more!
In our latest release we have primarily focused on optimising and stabilising the backend and on adding new elements to provide an improved user experience throughout the OpenRouteService 3.3 based on OpenStreetMap data. After many requests from our community, we for starters can happily announce that we have made the service responsive for your mobile smartphones.…
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Deriving incline values for street networks from voluntarily collected GPS traces
When producing optimal routes through an environment, considering the incline of surfaces can be of great benefit in a number of use cases. For instance, incline may be considered when computing the most energy-efficient routes for electric cars and bicycles. Likewise, pedestrians with restricted mobility (such as wheelchair users, parents with pushchairs, and the elderly)…
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A conceptual model for quality assessment of VGI for the purpose of flood management
Volunteered Geographic Information (VGI) has emerged as a potential source of geographic information for different domains. Despite the many advantages associated with it, such information lacks of quality assurance, since it is provided by individuals with different motivations and backgrounds. In response to this, several methods have been proposed to assess the quality of volunteered…