Dear Colleagues,

Machine learning is a field of computational science which first emerged in the 1950s. However, our ability to effectively harness the power of machine learning techniques was only truly realised in the 1990s. In ecology, the earliest adoption of machine learning came about in the early 2000s, when regression tree algorithms were applied to spatial data to predict species distributions. This was quickly adapted in the field of marine ecology to study the distribution of many pelagic species. Since that time, machine learning algorithms have been adapted and applied in various studies in the marine environment, from population models, image recognition, and experimental studies. Because they are non-parametric in nature and able to incorporate complex information, machine learning techniques are ideal for application to ecological problems. Furthermore, machine learning and its sub-field, deep learning, allow researchers to extend their ability to monitor populations of difficult-to-access marine species using automated techniques, which will greatly enhance conservation efforts globally.

The purpose of this Special Issue is to highlight the use of machine learning algorithms for studying marine ecosystems. Topics may range from applications of machine learning in species distribution modelling, to image or vocal recognition. Studies focusing on any marine species, including those in the coastal environment, are welcome. Articles may address, but are not limited to, the following topics:

• Species distribution modelling;
• Marine protected area planning;
• Machine learning for experimental research;
• Image recognition for marine conservation;
• Audio recognition;
• Machine learning tools and tag development;
• Sustainability planning using machine learning.

Dr. Grant R.W. Humphries
Dr. Marianna Chimienti
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. 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.

• Machine learning
• Deep learning
• Marine ecology
• Predictive analysis
• Conservation
• Sustainability