European Handbook of Crowdsourced Geographic Information
Free

European Handbook of Crowdsourced Geographic Information

By Cristina Capineri (editor)
Free
Book Description

This book focuses on the study of the remarkable new source of geographic information that has become available in the form of user-generated content accessible over the Internet through mobile and Web applications. The exploitation, integration and application of these sources, termed volunteered geographic information (VGI) or crowdsourced geographic information (CGI), offer scientists an unprecedented opportunity to conduct research on a variety of topics at multiple scales and for diversified objectives.

The Handbook is organized in five parts, addressing the fundamental questions: What motivates citizens to provide such information in the public domain, and what factors govern/predict its validity?What methods might be used to validate such information? Can VGI be framed within the larger domain of sensor networks, in which inert and static sensors are replaced or combined by intelligent and mobile humans equipped with sensing devices? What limitations are imposed on VGI by differential access to broadband Internet, mobile phones, and other communication technologies, and by concerns over privacy? How do VGI and crowdsourcing enable innovation applications to benefit human society?

Chapters examine how crowdsourcing techniques and methods, and the VGI phenomenon, have motivated a multidisciplinary research community to identify both fields of applications and quality criteria depending on the use of VGI. Besides harvesting tools and storage of these data, research has paid remarkable attention to these information resources, in an age when information and participation is one of the most important drivers of development.

The collection opens questions and points to new research directions in addition to the findings that each of the authors demonstrates. Despite rapid progress in VGI research, this Handbook also shows that there are technical, social, political and methodological challenges that require further studies and research.

Table of Contents
  • Acknowledgements
  • Supporting institutions
  • Chapter 1. Introduction
  • Part I: Theoretical and social aspects
  • Chapter 2. The nature of volunteered geographic information (Cristina Capineri)
  • Chapter 3. Why is participation inequality important? (Mordechai (Muki) Haklay)
  • Chapter 4. Social Media Geographic Information: Why social is special when it goes spatial? (Michele Campagna)
  • Part II: Quality: Criteria and methodologies
  • Chapter 5. Handling quality in crowdsourced geographic information (Laura Criscuolo, Paola Carrara, Gloria Bordogna, Monica Pepe, Francesco Zucca, Roberto Seppi, Alessandro Oggioni and Anna Rampini)
  • Chapter 6. Data quality in crowdsourcing for biodiversity research: issues and examples (Clemens Jacobs)
  • Chapter 7. Semantic Challenges for Volunteered Geographic Information (Andrea Ballatore)
  • Chapter 8. Quality analysis of the Parisian OSM toponyms evolution (Vyron Antoniou, Guillaume Touya and Ana-Maria Raimond)
  • Chapter 9. Tackling the thematic accuracy of areal features in OpenStreetMap (Ahmed Loai Ali)
  • Chapter 10. Enhancing the management of quality of VGI: contributions from context and task modelling (Benedicte Bucher, Gilles Falquet, Claudine Metral and Rob Lemmens)
  • Part III: Data analytics
  • Chapter 11. A methodological toolbox for exploring collections of textually annotated georeferenced photographs (Ross S. Purves and William A. Mackaness)
  • Chapter 12. Gaining Knowledge from Georeferenced Social Media Data with Visual Analytics (Gennady Andrienko and Natalia Andrienko)
  • Chapter 13. Head/tail Breaks for Visualization of City Structure and Dynamics (Bin Jiang)
  • Chapter 14. Querying VGI by semantic enrichment (Rob Lemmens, Gilles Falquet, Stefano De Sabbata, Bin Jiang and Benedicte Bucher)
  • Chapter 15. Extracting Location Information from Crowd-sourced Social Network Data (Pinar Karagoz, Halit Oguztuzun, Ruket Cakici, Ozer Ozdikis, Kezban Dilek Onal and Meryem Sagcan)
  • Chapter 16. Spatial and Temporal Sentiment Analysis of Twitter data (Zhiwen Song and Jianhong (Cecilia) Xia)
  • Chapter 17. Social Networks VGI: Twitter Sentiment Analysis of Social Hotspots (Dario Stojanovski, Ivan Chorbev, Ivica Dimitrovski and Gjorgji Madjarov)
  • Chapter 18. Research on social media feeds – A GIScience perspective (Enrico Steiger, Rene Westerholt and Alexander Zipf)
  • Part IV: VGI and crowdsourcing in environmental monitoring
  • Chapter 19. Changing role of citizens in the national environmental monitoring (Juhani Kettunen, Jari Silander, Matti Lindholm, Maiju Lehtiniemi, Outi Setälä and Seppo Kaitala)
  • Chapter 20. On the contribution of Volunteered Geographic Information to land monitoring efforts (Jamal Jokar Arsanjani and Cidália C. Fonte)
  • Chapter 21. Discussing the potential of crowdsourced geographic information for urban areas monitoring using the panoramio initiative (Flavio Lupia and Jacinto Estima)
  • Chapter 22. AtrapaelTigre.com: enlisting citizen-scientists in the war on tiger mosquitoes (Aitana Oltra, John R.B. Palmer and Frederic Bartumeus)
  • Chapter 23. Crowdsourcing geographic information for disaster risk management and improving urban resilience: an overview of the lessons learned (João Porto de Albuquerque, Melanie Eckle, Benjamin Herfort and Alexander Zipf)
  • Part V: VGI in mobility
  • Chapter 24. Crowdsourcing for individual needs - the case of routing and navigation for mobility-impaired persons (Alexander Zipf, Amin Mobasheri, Adam Rousell and Stefan Hahmann)
  • Chapter 25. Smart Timetable Service Based on Crowdsensed Data (Károly Farkas)
  • Chapter 26. Mobile crowd-sensing in the Smart City (Imre Lendák)
  • Chapter 27. Mobile crowd sensing for smart urban mobility (Dragan Stojanovic, Bratislav Predic and Natalija Stojanovic)
  • Part VI: VGI in spatial planning
  • Chapter 28. Using mobile crowdsourcing and geotagged social media data to study people’s affective responses to environments (Haosheng Huang and Georg Gartner)
  • Chapter 29. Integrating Authoritative and Volunteered Geographic Information for spatial planning (Pierangelo Massa and Michele Campagna)
  • Chapter 30. A Proposed Crowdsourcing Cadastral Model: Taking Advantage of Previous Experience and Innovative Techniques (Sofia Basiouka and Chryssy Potsiou)
  • Chapter 31. Modelling the world in 3D from VGI/Crowdsourced data (Hongchao Fan and Alexander Zipf)
  • Glossary (Linda See, Cristina Capineri and Sofia Basiouka)
  • Glossary’s Bibliography
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