Special Issue "Data Processing and Modeling on Volcanic and Seismic Areas"
Deadline for manuscript submissions: 31 August 2020.
Interests: ground deformation; volcano geodesy; volcano-tectonics; volcanology; active tectonics
Special Issues and Collections in MDPI journals
Interests: time series analysis; signal processing; data modelling; inverse problems; pattern recognition; machine learning; volcano geodesy; volcano modelling
The recent growth of multi-sensor monitoring networks and satellites with the exponential increase of the amount of spatiotemporal data has revealed an increasingly compelling need to develop data processing, analysis, and modeling tools capable of handling large amounts of data and synthesizing the useful information.
Data processing, analysis, and modeling techniques may allow the identification of significant information to be integrated into volcanic/seismological monitoring systems. The new developed technology is expected to improve operational hazard detection, alerting, and management capabilities.
Technological evolution, as well as the increasing availability of new sensors and platforms and freely available data, pose a new challenge to the scientific community for developing new tools and methods able to integrate and process different information. Emergencies and crises evidence how the rapid response in processing all the available information is also crucial in helping decision makers to mitigate the risk to the exposed population. Prompt data analysis requires a variety of tools, such as event detection, phenomenon recognition and classification, hazard assessment, and episode forecast.
This Special Issue intends to collect new ideas and contributions at the frontier between the fields of data handling, processing, and modeling for volcanic and seismic systems. The primary aspects of any contribution should be novelty and originality.
Specific topics of interest for this Special Issue include, but are not limited to:
- Modeling volcano and earthquake deformation;
- Spatiotemporal data analysis;
- Tools for the diagnosis of unrest patterns using statistical analytics and current advancement of machine learning techniques;
- Automatic procedures for data processing, standardization, and rapid integration into a centralized monitoring platform;
- Anomaly detection and precursor recognition in data.
Dr. Alessandro Bonforte
Dr. Flavio Cannavò
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 papers will be 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. Applied Sciences is an international peer-reviewed open access semimonthly 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 1800 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.
- data management
- data handling
- big data
- time series
- machine learning
- data fusion