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GIScience Blog

Category: Crowd Analyser

  • Understanding spatiotemporal trip purposes of urban micro-mobility from the lens of dockless e-scooter sharing

    Over the last two years, we have witnessed the ever-fast growth of micro-mobility services (e.g., e-bikes and e-scooters), which brings both challenges and innovations to the traditional urban transportation systems. For example, they provide an opportunity to better address the “last mile” problem due to their convenience, flexibility and zero emission. As such, it is…

  • Regional Variations of Context-based Association Rules in OpenStreetMap

    As a user‐generated map of the whole world, OpenStreetMap (OSM) provides valuable information about the natural and built environment. However, the spatial heterogeneity of the data due to cultural differences and the spatially varying mapping process makes the extraction of reliable information difficult. A newly published study investigates the variability of association rules extracted from…

  • LOKI – Video on UAV-based damage assessment combining automated methods with Micro-Mapping

    Interested in how earthquake-induced damage to critical infrastructures is assessed in the research project LOKI? Then check out this teaser below! Link to video In the LOKI project (Luftgestützte Observation Kritischer Infrastrukturen; Airborne Assessment of Critical Infrastructures), an interdisciplinary system that enables fast and reliable airborne situation assessments following an earthquake is being developed by…

  • Inferencing indoor room semantics using random forest and relational graph convolutional networks (deep learning)

    Semantically rich maps are the foundation of indoor location‐based services. Many map providers such as OpenStreetMap and automatic mapping solutions focus on the representation and detection of geometric information (e.g., shape of room) and a few semantics (e.g., stairs and furniture) but often still neglect room usage. To mitigate the issue, a new published paper…

  • Exploration of OpenStreetMap Missing Built-up Areas using Twitter Hierarchical Clustering and Deep Learning in Mozambique

    Accurate and detailed geographical information digitizing human activity patterns plays an essential role in response to natural disasters. Volunteered geographical information, in particular OpenStreetMap (OSM), shows great potential in providing the knowledge of human settlements to support humanitarian aid, while often the availability and quality of OSM remains a major concern. The majority of existing…

  • New project: LOKI – Airborne Observation of Critical Infrastructures

    On Feb 12, 2020, the kick-off meeting for the newly funded BMBF project LOKI – Airborne Observation of Critical Infrastructures (Luftgestützte Observation Kritischer Infrastrukturen) was hosted by the GIScience and 3DGeo research groups of Heidelberg University. The aim of the LOKI project is to develop an interdisciplinary system that enables fast and reliable airborne situation…

  • Prize for best PhD for Rene Westerholt “Förderpreis Runder Tisch GIS München”

    Recently our former team member Rene Westerholt (now at Warwick UK) received this years prize for the best PhD at “Förderpreis Runder Tisch GIS München 2019“. The PhD was done in Heidelberg within the graduate school “CrowdAnalyser – Spatio-temporal Analysis of User-generated Content”.  We concratulate cordially! The following papers are part of the cummulative PhD…

  • Towards the statistical analysis and visualization of places

    The concept of place recently gains momentum in GIScience. In some fields like human geography, spatial cognition or information theory, this topic already has a longer scholarly tradition. This is however not yet completely the case with statistical spatial analysis and cartography. Despite that, taking full advantage of the plethora of user-generated information that we…

  • Follow-up to study with mobile low-cost 3D camera crop height measurements

    The study “Mobile low-cost 3D camera maize crop height measurements under field conditions” (see the respective blog entry) is now available also as print version: The updated citation is: Hämmerle, M. & Höfle, B. (2018): Mobile low-cost 3D camera maize crop height measurements under field conditions. Precision Agriculture 19(4), pp. 630-647. doi: 10.1007/s11119-017-9544-3.

  • Successful PhD Defence by René Westerholt on The Analysis of Spatially Superimposed and Heterogeneous Random Variables Using the Example of Geosocial Media Data

    This week our GIScience Heidelberg team member Rene Westerholt most successfully defended his PhD! Congratulations! Very well deserved! The thesis is located at the interface between spatial analysis methodology and the characteristics of spatially superimposed random variables. Three types of contributions are presented: (i) the interactions of spatial analysis techniques with spatially superimposed random variables…

  • Successful DFG VGIscience Collaborative Research Week in Heidelberg

    Last week about 30 scientists from different insitutions from all across Germany came together in Heidelberg to conduct collaborative research. The research week is the result of an intense collaboration within the DFG Priority Programme VGIscience, which deals with the following topics Information Retrieval and Analysis of VGI: • information extraction (space, time, semantics) •…

  • PLATIAL’18 Workshop in September

    The recent availability of user-generated geographic datasets allows gaining novel insights into otherwise hardly observable societal phenomena. Geosocial media forms one important source of user-generated information, which partly describes the everyday lives of people. The analysis of these kinds of data, however, requires new approaches. Geosocial media data—like those extracted from Twitter, Flickr, Instagram, and…