Maritime Big Data for Fisheries Management and Spatial Planning

Dear Colleagues,

The growing number of ship reporting technologies and remote sensing systems (e.g. Vessel monitoring System, Automatic Identification System, Long-Range Identification and Tracking, Earth Observation by SAR and other sensors) are generating an overwhelming amount of spatio-temporal and geographically distributed data related to large-scale vessels and their movements. Moreover, the rapid development of low-cost and easily deployable technologies and processes suggests that data collection from Small-Scale Fisheries (SSF) will become soon automated, helping fill knowledge gaps in fisheries monitoring.

The data-driven knowledge discovery approach has proved its worth in fields that go beyond the original expectations for such data. They include mapping human activities at sea, fisheries management, maritime spatial planning (MSP), risk assessment of offshore platforms, assessment of impact on marine habitats, monitoring of compliance to regulation, and trade indicators. The extraction of spatial-explicit information from maritime big data, together with the use of machine learning techniques, is thus a key element to offer operational authorities, policy-makers, and scientists a better picture of what is happening at sea and improve maritime knowledge. Moreover, the use of this information layers to feed MSP tools provides a substantial opportunity for planners to develop a long-term strategy and support sustainable growth in the marine and maritime sectors as a whole.

In this context, this Special Issue invites original scientific contributions on topics including—without being limited to:

• Vessel detection, classification, and identification of fishing activities

• Multi-sensor data fusion for integrated maritime surveillance
• Low-cost electronic systems allowing tracking of small-scale fishing vessels

• Big-Data analytics for improving maritime knowledge and fisheries management
• MSP applications using vessel identification data
• Spatio-temporal patterns of fishing pressure and their implications for spatial planning and management
• Experiences with technologies to monitor and/or improve fishery compliance

Dr. Anna Nora Tassetti
Guest Editor

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.

• fisheries
• spatial fishery data
• fisheries management
• data mining and information fusion
• machine learning
• integrated Maritime Surveillance
• maritime Spatial Planning (MSP)
• integrated coastal management
• MSP tool