Modeling, Prediction and Mapping with VGI
A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).
Deadline for manuscript submissions: closed (1 July 2020) | Viewed by 493
Special Issue Editors
Interests: environmental modeling; volunteered geographic information; geospatial big data; geo-computation; GIScience
Special Issues, Collections and Topics in MDPI journals
Interests: geographic information systems (GIS) and remote sensing (RS) techniques; artificial intelligence/machine learning; fuzzy logic; watershed system modeling and scenario analysis; intelligent geocomputing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Empowered by geospatial technologies, such as location-aware smart phones, many ordinary citizens are now acting as human sensors and voluntarily contributing geo-referenced ground observations regarding a broad array of geographic phenomena. Such geospatial data contributed by citizen volunteers are collectively referred to as volunteered geographic information (VGI), which broadly encompasses geographic information created through public participatory geographic information systems, citizen science, crowdsourcing, and social media, amongst other mechanisms. VGI has been revolutionizing the way geographic data, information, and knowledge are generated and disseminated. Moreover, VGI is an important source of geospatial big data that could potentially shift geographical research to a new “data-intensive” or “data-driven” paradigm.
VGI has a great potential for revealing the spatiotemporal dynamics of geographic phenomena, be they natural or social. This potential can be realized using VGI observations for the modeling, prediction, and mapping of geographic phenomena. Examples are species distribution, soil, land use and land cover, disaster, traffic congestion, and human mobility, to name only a few.
We invite research articles and reviews fitting the general theme of “Modeling, Prediction, and Mapping with VGI”, to be published in this Special Issue. Submissions to the SI are open to all scholars. Participants to the 2020 AAG session “Modeling, Prediction and Mapping with VGI” are especially encouranged to submit full papers extended from their presented abstracts.
Assis. Prof. Guiming ZhangProf. A-Xing Zhu
Guest Editor
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 1900 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.
Keywords
- volunteered geographic information (VGI)
- public participatory geographic information systems
- crowdsoucing geographic information
- citizen science
- socia media
- spatial analysis, modeling and prediction
- mapping
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