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This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact

environment human health --- air quality --- marine environment --- circular bioeconomy --- remediation and restoration

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Microorganisms (bacteria, archaea, microeukaryotes) in marine environments secrete a diverse array of exopolymeric substances that facilitate attachment to surfaces, the formation of organic colloids and larger aggregations of cells (marine snow), and that can influence many ocean, as well as global, processes. The aim of this Research Topic is to highlight recent advances in the sources, chemistry and function of these microbial-produced macromolecules. We encouraged original research and reviews on exopolymeric substances, from their sources, chemico-physiological properties, functions and ecosystem effects, and including their role in the Gulf of Mexico following the Deepwater Horizon oil spill disaster.

marine oil snow (MOS) --- exopolymers --- marine environment --- biological pump --- phytoplankton --- marine snow --- oceans --- marine bacteria --- exopolysaccharide substances (EPS) --- organic carbon

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Marine pollution --- Marine environment pollution --- Marine water pollution --- Ocean pollution --- Offshore water pollution --- Sea pollution --- Seawater --- Coastal zone management --- Oceanography --- Pollution --- Water --- Marine resources conservation --- Research.

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This reprint focuses on the application of the combination of synthetic aperture radars and depth learning technology. It aims to further promote the development of SAR image intelligent interpretation technology. A synthetic aperture radar (SAR) is an important active microwave imaging sensor, whose all-day and all-weather working capacity give it an important place in the remote sensing community. Since the United States launched the first SAR satellite, SAR has received much attention in the remote sensing community, e.g., in geological exploration, topographic mapping, disaster forecast, and traffic monitoring. It is valuable and meaningful, therefore, to study SAR-based remote sensing applications. In recent years, deep learning represented by convolution neural networks has promoted significant progress in the computer vision community, e.g., in face recognition, the driverless field and Internet of things (IoT). Deep learning can enable computational models with multiple processing layers to learn data representations with multiple-level abstractions. This can greatly improve the performance of various applications. This reprint provides a platform for researchers to handle the above significant challenges and present their innovative and cutting-edge research results when applying deep learning to SAR in various manuscript types, e.g., articles, letters, reviews and technical reports.

Marine pollution. --- Marine environment pollution --- Marine water pollution --- Ocean pollution --- Offshore water pollution --- Sea pollution --- Seawater --- Coastal zone management --- Oceanography --- Pollution --- Water --- Marine resources conservation

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Marine accidents. --- Marine accidents --- Marine pollution --- Environmental aspects --- Mathematical models. --- Marine environment pollution --- Marine water pollution --- Ocean pollution --- Offshore water pollution --- Sea pollution --- Seawater --- Coastal zone management --- Oceanography --- Pollution --- Water --- Marine resources conservation --- Ships --- Accidents