Sustainable Development of Our Oceans and Coastal Zones through AI and Remote Sensing

Dear Colleagues,

In 2021, we will enter the United Nations Decade of Ocean Science for Sustainable Development (2021–2030). The goal of this proclamation is to encourage efforts across the globe to reverse the decline in ocean health as climate change, fishing, pollution, and other human factors have damaged 96% of the world’s oceans, with more than 40% already seriously damaged. At the same time, other organizations, such as the European Union, are turning to the ocean and coastal environments as a source of economic growth in what is labeled “The Blue Economy”. Opportunities within areas such as energy, food, medicine, transportation, mining, and tourism abound. To reverse the decline while ensuring the sustainable development of the ocean and coastal zones is a considerable challenge, and many are increasingly looking to the application of artificial intelligence to ocean data as a potential solution. On the one hand, the amount of ocean remote sensing data is growing exponentially due to continuous developments in space, sensor, and robotics technologies and expanding data collection possibilities through an increasing number of sensors and arenas, such as deep ocean hydroacoustics. On the other hand, advances in artificial intelligence, in areas such as machine learning and neural networks, offer great promise in the ability to mine and sustainably leverage ocean data. However, data-driven marine and maritime research lags considerably behind land-based research.

To reduce this knowledge gap, we at Ocean Data Factory Sweden and SmartOcean Portugal would like to invite articles for a Special Issue on the “Sustainable Development of Our Oceans and Coastal Zones through AI and Remote Sensing”. Research topics include but are not limited to the collection, preparation, fusion, storage, streaming, and algorithm development and deployment for remote sensing ocean data using signals propagating through space, air, and water in the following areas:

• Monitoring and forecasting of ocean and coastal environments;
• Solutions for pollution and climate change in ocean and coastal environments;
• Sustainable development and management of ocean resources, e.g., renewables, seafood, raw materials;
• Coastal and maritime spatial planning;
• Ocean economics applied to marine and maritime activities;
• Organization of remote sensing data-driven ocean innovation, including open innovation and citizen science.

Prof. Dr. Robin Teigland
Dr. Torsten Linders
Dr. Sergio Leandro
Dr. Ivan Masmitja
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing 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 2700 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.