Volunteered geographic information: interpretation, visualization and social context
Part I: Representation and Analysis of VGI -- 1. WorldKG: World-Scale Completion of Geographic Information -- 2. Analyzing and Improving the Quality and Fitness for Purpose of OpenStreetMap as Labels in Remote Sensing Applications -- 3. Efficient Mining of Volunteered Trajectory Data Sets -- 4. Unce...
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| Other Authors: | , , |
|---|---|
| Format: | Book/Monograph |
| Language: | English |
| Published: |
Cham
Springer Nature Switzerland
2024.
Cham Imprint: Springer 2024. |
| Edition: | 1st ed. 2024. |
| Volumes / Articles: | Show Volumes / Articles. |
| DOI: | 10.1007/978-3-031-35374-1 |
| Online Access: | Resolving-System, kostenfrei: https://doi.org/10.1007/978-3-031-35374-1
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| Author Notes: | edited by Dirk Burghardt, Elena Demidova, Daniel A. Keim |
MARC
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| 520 | |a Part I: Representation and Analysis of VGI -- 1. WorldKG: World-Scale Completion of Geographic Information -- 2. Analyzing and Improving the Quality and Fitness for Purpose of OpenStreetMap as Labels in Remote Sensing Applications -- 3. Efficient Mining of Volunteered Trajectory Data Sets -- 4. Uncertainty-Aware Enrichment of Animal Movement Trajectories by VGI -- 5. Two Worlds in One Network: Fusing Deep Learning and Random Forests for Classification and Object Detection -- Part II: Geovisualization and User Interactions Related to VGI -- 6. Toward Visually Analyzing Dynamic Social Messages and News Articles Containing Geo-Referenced Information -- 7. Visually Reporting Geographic Data Insights as Integrated Visual and Textual Representations -- 8. Effects of Landmark Position and Design in VGI Based Maps on Visual Attention and Cognitive Processing -- 9. Addressing Landmark Uncertainty in VGI-based Maps: Approaches to Improve Orientation and Navigation Performance -- 10. Improvement of Task-Oriented Visual Interpretation of VGI Point Data -- Part III: Active Participation, Social Context and Privacy Awareness -- 11. Environmental Tracking for Healthy Mobility -- 12. Extraction and Visually Driven Analysis of VGI for Understanding People’s Behavior in Relation to Multi-Faceted Context -- 13. Digital Volunteers in Disaster Management -- 14. Protecting Privacy in Volunteered Geographic Information Processing. | ||
| 520 | |a This open access book includes methods for retrieval, semantic representation, and analysis of Volunteered Geographic Information (VGI), geovisualization and user interactions related to VGI, and discusses selected topics in active participation, social context, and privacy awareness. It presents the results of the DFG-funded priority program "VGI: Interpretation, Visualization, and Social Computing" (2016-2023). The book includes three parts representing the principal research pillars within the program. Part I "Representation and Analysis of VGI" discusses recent approaches to enhance the representation and analysis of VGI. It includes semantic representation of VGI data in knowledge graphs; machine-learning approaches to VGI mining, completion, and enrichment as well as to the improvement of data quality and fitness for purpose. Part II "Geovisualization and User Interactions related to VGI" book explores geovisualizations and user interactions supporting the analysis and presentation of VGI data. When designing these visualizations and user interactions, the specific properties of VGI data, the knowledge and abilities of different target users, and technical viability of solutions need to be considered. Part III "Active Participation, Social Context and Privacy Awareness" of the book addresses the human impact associated with VGI. It includes chapters on the use of wearable sensors worn by volunteers to record their exposure to environmental stressors on their daily journeys, on the collective behavior of people using location-based social media and movement data from football matches, and on the motivation of volunteers who provide important support in information gathering, filtering and analysis of social media in disaster situations. The book is of interest to researchers and advanced professionals in geoinformation, cartography, visual analytics, data science and machine learning. | ||
| 650 | 0 | |a Application software. | |
| 650 | 0 | |a Geographic information systems. | |
| 650 | 0 | |a Data mining. | |
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| SRT | |a VOLUNTEERE2024 | ||