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Special Issue "Urban Geospatial Analytics Based on Crowdsourced Data"
A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).
Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 26421
Special Issue Editors
Interests: crowd dynamic monitoring; travel mode classification; urban sensing; point cloud
Interests: urban mobility; geo-visualisation; spatio-temporal modelling; critical GIS
Special Issue Information
In recent years, geospatial knowledge extraction from massive crowdsourced datasets has become one of the main foci of geographic information science. However, factors such as the multiplicity of data formats, the variable and uncertain data quality, the often flexible data contribution guidelines, as well as issues related to data accessibility and sampling, are persistent challenges that the geospatial community needs to cope with in order to develop efficient technical solutions and advance geospatial theories based on this type of data.
Supported by advancements in ubiquitous sensing and computing, information and communication technologies, and location-based services, crowdsourced data on human mobility practices and daily activities, as well as on the structure and form of geographical space, have been extensively generated. The potential for spatial knowledge extraction from such data is highly relevant, particularly for urban studies. Given the challenges mentioned above, though, advanced tools and novel approaches need to be developed to harness big crowdsourced geospatial datasets towards effective geospatial knowledge extraction. The outcomes of that effort shall, in different ways, benefit the general public, researchers, and governments alike.
The aim of this Special Issue is to present state-of-the-art research on methods, theories, applications, and services developed based on crowdsourced geospatial datasets. Due to the multidisciplinary nature of the topic, contributions may be within different fields of research, including GIS, volunteered geographic information, big spatial data analytics, geospatial artificial intelligence, computer vision, machine learning, urban analytics, and many others.
Contributions may be conventional research articles focusing on technical solutions or theoretical developments as well as literature reviews. Keywords summarizing the scope of the Special Issue include:
- Urban mobility analyses;
- Data quality management;
- Data inequalities;
- Data conflation;
- Knowledge extraction.
Dr. Hangbin Wu
Dr. Tessio Novack
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- big spatial data
- geospatial knowledge
- spatial crowdsourcing
- social media
- trajectory analysis
- task allocation
- volunteered geographic information
- spatiotemporal modeling
- urban computing