Satellite Monitoring of Ocean II

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Physical Oceanography".

Deadline for manuscript submissions: closed (20 August 2023) | Viewed by 3012

Special Issue Editors


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Guest Editor
Institute for Scientific Research of Aerospace Monitoring "AEROCOSMOS", Moscow, Russian Federation
Interests: physical fundamentals of satellite research of the Earth; ocean optics, sea surface radar studies, remote sensing of the aquatic environment; retrieval of wave spectra from the spectra of optical images of the sea surface; satellite monitoring of anomalous natural and anthropogenic processes and phenomena in the seas and oceans (environmental accidents, intense deep discharges, large-scale oil spills, etc.); remote diagnostics of deep processes in the seas and oceans by their manifestations on the surface and in the near-surface layer; satellite research of the Arctic and Antarctic; processing of large data flows from satellites for remote monitoring of seas and oceans
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Guest Editor
Oceans Graduate School & The UWA Oceans Institute, The University of Western Australia, Perth, WA 6009, Australia
Interests: coastal oceanography; mixing and circulation; physical processes; coastal observations; numerical modeling; sediment transport; remote sensing; estuaries; nearshore processes
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue of JMSE focuses on satellite monitoring of the ocean, which is a rapidly evolving technique with growing capabilities in the development of state-of-the-art systems for remote sensing of the Earth from space and methods for satellite information processing. The Issue contains articles dedicated to modern approaches to solving the problems of remote diagnostics of processes on the surface, in the near-surface layer, and in the deep layers of the ocean. Particular attention is paid to the use of satellite methods for the analysis of various anomalous phenomena in the seas and oceans. The physical features of the formation of signal fields in ocean remote sensing facilities and methods to retrieve significant parameters of the aquatic environment, which provide objective information about the state of the seas and oceans, are considered. The possibilities of using passive and active methods and means of operating in various ranges of the spectrum of electromagnetic waves for monitoring processes and phenomena in the ocean are shown. The results of a study of anthropogenic and natural impacts on sea areas, based on the analysis of satellite images obtained in the optical and microwave ranges of the spectrum, are presented. The capabilities of methods and assets for processing large flows of satellite information to solve problems of satellite oceanography, including in the waters of the Arctic and Southern Oceans, are analyzed. The issues of assimilation of remote sensing data in numerical ocean models are considered. Furthermore, the application of satellite monitoring techniques and facilities to study physical features of energy exchange between the agitated sea surface, the dynamic near-surface layer of the atmosphere, and deep processes, taking into account the nonlinear interaction of surface waves, are discussed.

Prof. Dr. Valery Bondur
Dr. Merv Fingas
Prof. Dr. Charitha Pattiaratchi
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. 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.

Keywords

  • satellite oceanography
  • satellite image processing
  • ocean remote sensing
  • sea surface spectra
  • retrieval of wave spectra
  • internal waves
  • ocean disasters
  • environmental monitoring
  • remote sensing data assimilation
  • numerical ocean models

Published Papers (1 paper)

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Research

22 pages, 4893 KiB  
Article
Improvement in Spatiotemporal Chl-a Data in the South China Sea Using the Random-Forest-Based Geo-Imputation Method and Ocean Dynamics Data
by Ao Li, Tiantai Shao, Zhen Zhang, Weiwei Fang, Wenjie Li, Jinrun Xu, Yujie Jiang and Chan Shu
J. Mar. Sci. Eng. 2024, 12(1), 13; https://doi.org/10.3390/jmse12010013 - 20 Dec 2023
Cited by 1 | Viewed by 796
Abstract
The accurate estimation of the spatial and temporal distribution of chlorophyll-a (Chl-a) concentrations in the South China Sea (SCS) is crucial for understanding marine ecosystem dynamics and water quality assessment. However, the challenge of missing values in satellite-derived Chl-a data has hindered obtaining [...] Read more.
The accurate estimation of the spatial and temporal distribution of chlorophyll-a (Chl-a) concentrations in the South China Sea (SCS) is crucial for understanding marine ecosystem dynamics and water quality assessment. However, the challenge of missing values in satellite-derived Chl-a data has hindered obtaining complete spatiotemporal information. Traditional methods for deriving Chl-a are based on the modeling of measured sensor data and in situ measurements. Spatiotemporal imputation of Chl-a is difficult due to the inaccessibility of the measured Chl-a. In this study, we introduce an innovative approach that incorporates an ocean dynamics dataset and utilizes the random forest algorithm for predicting the Chl-a concentration in the SCS. The method combines the spatiotemporal feature pattern of Chl-a and the main influencing factors, and it introduces ocean dynamics data, which has a high correlation with the spatiotemporal distribution of Chl-a, as the input data through feature engineering. Also, we compared Random Forest (RF) with other Machine Learning (ML) methods. The results show that (1) ocean dynamics datasets can provide important data support for Chl-a imputation by capturing the impact of dynamical processes on ecological roles in the South China Sea. (2) The RF method is the superior imputation method for the reconstruction of Chl-a in the South China Sea, with better model performance and smaller errors. This study provides valuable insight for researchers and practitioners in choosing suitable machine learning methods for the imputation of the Chl-a concentration in the SCS, facilitating a better understanding of the region’s marine ecosystems and supporting effective environmental management. Full article
(This article belongs to the Special Issue Satellite Monitoring of Ocean II)
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