Crowdsourcing for Urban Geoinformatics
Aims and Scope
Modern mobile devices are pervasively equipped with embedded sensors and cameras, and allow the positioning of media contents within geographic space. In combination with the Web 2.0 paradigm, this has led to the crowdsourcing approach, which in turn has become an important data acquisition technique. It is now possible to collect large amounts of geospatial data in a timely fashion and at low costs, especially in urban areas that feature vast numbers of contributors.
Crowdsourcing thus opens up new possibilities for the disclosure of social processes, and for tackling a range of societal and environmental issues related to urban conurbations. For instance, crowdsourcing allows the integration of user-generated information into urban planning and management workflows—and is thus a crucial step towards the design of smarter and more sustainable cities.
At the same time, crowdsourcing brings new issues to the research agendas: (a) huge amounts of data need to be processed, (b) more thorough interdisciplinary collaboration is needed, and (c) we are facing a general absence of theorizing on crowdsourced geodata and underlying related processes. Further, researchers as well as practitioners are often sceptical about the suitability of crowdsourced data. This is mostly caused by potential quality issues, heterogeneous data characteristics and a lack of user credibility, semantic ambiguities, and potential positional inaccuracies, among others.
Topics
In order to foster the overcoming of the outlined gaps, we call for the submission of papers that address the analysis and application of crowdsourced geographic data, with a specific emphasis on urban research and issues.
We welcome contributions on the following topics:
- Reviews of the state-of-the-art in using crowdsourced geographic information in urban research, planning, and management.
- Applications and empirical case studies that investigate urban issues by using crowdsourced geographic data such as OSM, social media data, floating car data, and other types.
- Data enrichment through crowdsourced geographic data.
- Extraction of 3D information from crowdsourced geographic data (e.g., from Kinect data, OSM data).
- The analysis of human behaviours for emergency (disaster) management, tourism, or urban planning and management.
- Quality assessment for crowdsourcing geographic data.
- Further topics are welcome if they fit the overall theme.
Submission Guidelines
Manuscripts should be submitted online: here.
Submitted articles should not have been published previously, or be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. All accepted manuscripts will be published open access in GSIS.
All article publishing charges (APC) will be covered by Wuhan University, so you can enjoy the benefits of publishing open access at no cost. Authors are recommended to prepare their manuscript by following the full instructions for authors: here.
Important Dates:
Submission deadline of finalized manuscripts: November 20, 2017
Deadline of print-ready version: April 30, 2018
Expected inclusion in an issue: June−August, 2018
Editorial information
- Special Issue Guest Editor: Hongchao Fan, Wuhan University (hongchao.fan@whu.edu.cn)
- Special Issue Guest Editor: João Porto de Albuquerque, University of Warwick(J.Porto@warwick.ac.uk)
- Special Issue Guest Editor: Rene Westerholt, Heidelberg University (westerholt@uni-heidelberg.de)
- Special Issue Guest Editor: Alexander Zipf, Heidelberg University (zipf@uni-heidelberg.de)
- Special Issue Guest Editor: Bernd Resch, University of Salzburg (bernd.resch@sbg.ac.at)
