Remote Sensing of Phytoplankton Ecology

Dear Colleagues,

Phytoplankton are a fundamental component of the marine ecosystem, and play an important role in global biogeochemical cycling, as well as climate change. Knowledge of marine phytoplankton ecology, such as phytoplankton biomass, primary productivity, and community, is essential for understanding the marine food web, the carbon storage capacity of the ocean, and material exchange at the air–sea interface. With the development of remote sensing, the goal of the simultaneous large-area observation of phytoplankton distribution on the sea surface has been achieved.

A variety of remote-sensing algorithms have been established to detect marine phytoplankton biomass, functional type, and primary productivity. For example, the series of OC algorithms continue to be improved for retrieving chlorophyll-a concentration more accurately. In addition, phytoplankton functional type algorithms are also developing, such as the three-component model of phytoplankton size class. In the context of climate change and global warming, the phytoplankton carbon algorithms are also gradually being established. However, the performances of these algorithms are unsatisfactory in complicated coastal seawater; regional re-parameterization, as well as algorithm validation, requires the joint efforts of scientists around the world. With more reliable algorithms, the study of the temporal and spatial variabilities of phytoplankton will be more credible, and provide more useful information to researchers of marine ecology, global biogeochemical cycling, climate change, and marine physical-ecosystem coupling models.

In this Special Issue, topics include, but are not limited to:

• Establishment of new remote-sensing algorithms of phytoplankton biomass (i.e., chlorophyll-a concentration, phytoplankton carbon biomass), function type, primary production, and harmful algal blooms;
• Improvement, re-parameterization, validation, or contrast of current remote-sensing algorithms of phytoplankton;
• Evaluation of the applicability of current algorithms for phytoplankton ecology to remote-sensing data from different satellites;
• Studying the response of marine phytoplankton to hydro-physical processes and climate change based on remote sensing;
• Studying the role of phytoplankton in global carbon circulation based on remote sensing.

Prof. Dr. Shilin Tang
Prof. Dr. Jun Chen
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.