Discovery and Prediction of Moving Objects in Databases using GIS-based Tools
A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).
Deadline for manuscript submissions: closed (28 February 2018) | Viewed by 76731
Special Issue Editors
Interests: GIS; navigation; modelling moving objects; pedestrian mobility and public transport
Interests: movement analytics; data mining; crowd sourced geodata; spatial databases; transportation
Special Issue Information
Dear Colleagues,
Recent advances in sensor and mobile technologies have led to the availability of massive amounts of data, representing the movement of entities, such as people, vehicles, and animals. These data, referred to as movement data, reflect the characteristics of a moving object and the movement context. The extraction of useful information hidden in movement data can support movement understanding and prediction. While important research work has been done regarding the representation, management and analysis of movement data, the discovery and prediction of movement of entities and other related aspects is not well explored. Advanced methods and tools that take into account different issues associated with movement data such as a large volume, uncertainty and heterogeneity are urgently needed. Different application domains such as transportation, urban planning and ecology can benefit from such methods and tools for understanding different phenomena, monitoring their evolution, and controlling their effects.
This Special Issue seeks original research contributions in frameworks, methods and good case studies of tackling key research challenges in discovering and predicting various aspects related to moving objects. Sample topics covered include:
- Knowledge discovery from movement data
- Prediction of locations or trajectories of moving objects
- Prediction of changes in movement context
- Discovery of characteristics of moving objects (e.g., activities, transportation mode, etc.)
- Machine learning methods for movement prediction
- Data integration for movement understanding and prediction
- Visualization of movement patterns
Prof. Dr. Sabine Timpf 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.
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Mr. Jean Damascène Mazimpaka
Guest Editors
Keywords
- Knowledge discovery
- Movement prediction
- Machine learning
- Prediction methods
- Data integration
- Movement patterns
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