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Within the European FP7 project “CAP4Access“, we studied the usage of crowdsourced geographic information (and more specifically OpenStreetMap data) for improving accessibility in selected European regions. This 3 year research study led to several implementations and extensions of Open Source GI solutions with respect to OSM data quality assessment as well as wheelchair routing and [...]

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In a newly published open access paper, we present a system that generates customized pedestrian routes entirely based on data from OpenStreetMap (OSM). The system enables users to define to what extent they would like the route to have green areas (e.g., parks, squares, trees), social places (e.g., cafes, restaurants, shops) and quieter streets (i.e., [...]

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In our most recent 3DGeo publication, colleagues from KU Leuven together with us developed a new method to extract drainage ditches from LiDAR point clouds in a fully automatic process.

Ditches are often absent in hydrographic geodatasets and their mapping would benefit from a cost and labor effective alternative to field surveys. We propose [...]

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Understanding how citizens interact with transportation system is a key to solving a variety of urban issues in general and traffic congestion in particular. Recently, scholars have put efforts on the pertinent work ranging from developing traffic predictors to understanding human mobility and activity patterns. Multiple types of data have been used, of which crowdsourced [...]

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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 images [...]

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Our paper about Deep Learning from Multiple Crowds: A Case Study of Humanitarian Mapping is available online now.
Satellite images are widely applied in humanitarian mapping which labels buildings, roads and so on for humanitarian aid and economic development. However, the labeling now is mostly done by volunteers. In a recently accepted study, we utilize deep learning [...]

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The social functionality of places (e.g. school, restaurant) partly determines human behaviors and reflects a region’s functional configuration. Semantic descriptions of places are thus valuable to a range of studies of humans and geographic spaces. Assuming their potential impacts on human verbalization behaviors, one possibility is to link the functions of places to verbal representations [...]

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Airborne laser scanning (ALS) data of the Arctic permafrost research region Trail Valley Creek (TVC) has just been published for open access on the data library PANGAEA:
Anders, Katharina; Antonova, Sofia; Boike, Julia; Gehrmann, Martin; Hartmann, Jörg; Helm, Veit; Höfle, Bernhard; Marsh, Philip; Marx, Sabrina; Sachs, Torsten (2018): Airborne Laser Scanning (ALS) Point Clouds of Trail [...]

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Ecosystems provide many different services to mankind. Services provided depend on how the land is used – land use decisions lead to trade-offs that with respect to the ecosystem service provided by ecosystems and landscapes. This trade-offs vary in many situations in space and time. Therefore, it is essential to quantify and map service provisioning [...]

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GSIS Special Issue: Crowdsourcing for Urban Geoinformatics.
Geo-Spatial Information Science (GSIS), Volume 23, Issue 3. Taylor & Francis.
Guest Editors:
Hongchao Fan, Rene Westerholt, João Porto de Albuquerque, Bernd Resch and Alexander Zipf
TOC:

Do people communicate about their whereabouts? Investigating the relation between user-generated text messages and Foursquare check-in places

Ming Li, Rene Westerholt & Alexander Zipf

Pages: 159-172

Abstract|Full Text|References|PDF (2905 KB)

Description and [...]

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