3-3-3-3-3-3-3-3-3-3-3-3-3 From: Alessandro Bonforte <alessandro.bonforte@xxxxxxx> Dear colleagues, I would like to inform you about the Special Issue of Applied Sciences Journal (IF 2.217) on Data Processing and Modeling on Volcanic and Seismic Areas. Please, consider to contribute to this issue by submitting your manuscripts. The deadline is August 31, 2020. Follow this link to instructions and submission ( https://www.mdpi.com/journal/applsci/special_issues/volcanic_seismic) Summary: The recent growth of multi-sensor monitoring networks and satellites with the exponential increase of the spatiotemporal amount of data has revealed increasingly compelling the 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 identifying 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 the modeling for volcanic and seismic systems. The primary aspect 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 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 - Anomalies detection and precursor recognition in data 3-3-3-3-3-3-3-3-3-3-3-3-3 ============================================================== Volcano Listserv is a collaborative venture among Arizona State University (ASU), Portland State University (PSU), the Global Volcanism Program (GVP) of the Smithsonian Institution's National Museum of Natural History, and the International Association for Volcanology and Chemistry of the Earth's Interior (IAVCEI). ASU - http://www.asu.edu/ PSU - http://pdx.edu/ GVP - http://www.volcano.si.edu/ IAVCEI - https://www.iavceivolcano.org/ To unsubscribe from the volcano list, send the message: signoff volcano to: listserv@xxxxxxx, or write to: volcano-request@xxxxxxx. To contribute to the volcano list, send your message to: volcano@xxxxxxx. Please do not send attachments. ============================================================== ------------------------------
