Spatial–Temporal Data Analysis and Its Applications
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Signal and Data Analysis".
Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 18436
Special Issue Editors
Interests: statistical machine learning; spatial and temporal modelling; speech and image processing; environmental data analysis; epidemiological data analysis
Interests: modelling extreme events; dependence modelling; state–space models; Monte Carlo methods; optimal stochastic control; machine learning methods
Special Issues, Collections and Topics in MDPI journals
Interests: financial risk management and insurance; actuarial machine learning methodology; time series and state-space modelling; spatial statistics; stochastic processes in financial applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The objective of this Special Issue is to bring together an interdisciplinary selection of works that relate to the topics of spatial and temporal modelling with a methodology and application focus. The interface of spatial modelling and time-series analysis has emerged as an important field of research on the boundary of many disciplines, including computational statistics; machine learning and big data analytics; signal processing; environmental science; risk and insurance analytics in actuarial practice disciplines, such as catastrophe modelling, green finance, and demographic statistics; agricultural science; and network science, to list a few.
However, to date, these disciplines have largely formed somewhat independent views on best practices to develop methodology and implement practical solutions to spatial–temporal problems that arise in each of these disciplines. As research becomes increasingly interdisciplinary, the Guest Editors of this Special Issue see an opportunity to encourage a multidisciplinary selection of papers on topics in spatial–temporal analysis that provide perspectives on emerging trends and problems in these disciplines to learn and leverage experiences across these communities.
We encourage submissions that focus on but are not limited to one of the following sub-categories:
- Recent methodological advances in spatial–temporal modelling;
- Computational solutions to large scale estimation and simulation in big data spatial–temporal settings;
- Application topics in global warming and environmental modelling;
- Spatial–temporal risk modeling for decision making under uncertainty, which could include catastrophe and insurance applications, environmental–economic modelling, stress-testing, and scenario analysis models for integrated climate economic models;
- Spatial–temporal demographic statistics for population planning and analysis with applications including, but not limited to, retirement planning, pensions, and aged care;
- Spatial–temporal epidemiological solutions, especially with a focus on epidemics such as COVID-19 data analysis;
- In particular, analysis and interpretation with the help of statistical tools based on entropy and information theory are included in this Special Issue.
Prof. Dr. Tomoko Matsui
Prof. Dr. Pavel Shevchenko
Prof. Dr. Gareth W. Peters
Prof. Dr. Francois Septier
Guest Editors
Manuscript Submission Information
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Keywords
- spatial and temporal modelling
- statistical machine learning
- environmental data analysis
- epidemiological data analysis
- natural language processing
- speech and image processing
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