Ocean Big Data Application - Engineering

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312).

Deadline for manuscript submissions: closed (31 May 2019) | Viewed by 4973

Special Issue Editors


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Guest Editor
Institute of Information Science and Technologies, Pisa, Italy
Interests: Image processing for marine environment; multi-source data fusion; environmental decision support systems; marine information systems; machine learning methods; multimedia data integration
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Signals and Images Laboratory, Institute of Information Science and Technologies, National Research Council of Italy, Pisa, Italy
Interests: ICT applied to underwater cultural heritage preservation and safeguard; image processing for scene understanding purposes; ICT applied to maritime surveillance purposes; multi-sensor multi-source data analysis and integration
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Ocean observation represents a crucial task for human communities. Above sea level, this entails the implementation of maritime surveillance platforms, typically addressing security and safety issues (vessel traffic monitoring, search and rescue) as well as environmental sustainability aspects (fishery, pollution). On the other hand, the submerged ocean environment poses equally hard challenges for what concerns oil and gas exploitation or biology and cultural heritage safeguard. Performing the mentioned activities operationally requires the collection of a huge amount of multi-source and multi-sensor data, typically including optical images, videos, sonograms, radar/synthetic aperture radar maps, hydrocarbon concentration measurements, and so on. Publications in this Special Issue will aim at composing a comprehensive overview of the several aspects that emerge in the implementation of ocean observation platforms through big data processing.

With these issues in mind, among the various subjects the authors are invited to discuss theoretical issues in big data processing for ocean observation, as well as methods for big data processing through high performance computing (such as cloud computing infrastructures, big data fusion, etc.), not excluding application case studies exploiting big data issues.

To this purpose, authors are invited to submit contributions that take into considerations the following topics:

  • Ocean data representation, analysis and learning
  • Deep learning applied to big data for ocean observation
  • Techniques for data processing applied to ocean observation and cultural heritage safeguard
  • Target detection, classification and identification in ocean data
  • Vessel traffic monitoring
  • Marine pollution monitoring along with sea environment monitoring issues

Dr. Gabriele Pieri
Dr. Marco Reggiannini
Guest Editors

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. Journal of Marine Science and Engineering 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 2600 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

  • Deep learning for ocean observation
  • Target detection and classification
  • Marine pollution monitoring
  • Multi-source multi-sensor ocean data processing
  • Vessel traffic monitoring
  • Underwater archeology

Published Papers (1 paper)

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Research

24 pages, 5423 KiB  
Article
Remote Sensing for Maritime Prompt Monitoring
by Marco Reggiannini, Marco Righi, Marco Tampucci, Angelica Lo Duca, Clara Bacciu, Luigi Bedini, Andrea D’Errico, Claudio Di Paola, Andrea Marchetti, Massimo Martinelli, Costanzo Mercurio, Emanuele Salerno and Bruno Zizi
J. Mar. Sci. Eng. 2019, 7(7), 202; https://doi.org/10.3390/jmse7070202 - 28 Jun 2019
Cited by 11 | Viewed by 4483
Abstract
The main purpose of this paper is to describe a software platform dedicated to sea surveillance, capable of detecting and identifying illegal maritime traffic. This platform results from the cascade pipeline of several image processing algorithms that input Radar or Optical imagery captured [...] Read more.
The main purpose of this paper is to describe a software platform dedicated to sea surveillance, capable of detecting and identifying illegal maritime traffic. This platform results from the cascade pipeline of several image processing algorithms that input Radar or Optical imagery captured by satellite-borne sensors and try to identify vessel targets in the scene and provide quantitative descriptors about their shape and motion. This platform is innovative since it integrates in its architecture heterogeneous data and data processing solutions with the goal of identifying navigating vessels in a unique and completely automatic processing streamline. More in detail, the processing chain consists of: (i) the detection of target vessels in an input map; (ii) the estimation of each vessel’s most descriptive geometrical and scatterometric (for radar images) features; (iii) the estimation of the kinematics of each vessel; (iv) the prediction of each vessel’s forthcoming route; and (v) the visualization of the results in a dedicated webGIS interface. The resulting platform represents a novel tool to counteract unauthorized fishing and tackle irregular migration and the related smuggling activities. Full article
(This article belongs to the Special Issue Ocean Big Data Application - Engineering)
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