Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.8
3.0
Journals
Water
Special Issues
RS, GIS and Machine Learning Applied in Marine Science
water-logo
Submit to Water Review for Water Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

RS, GIS and Machine Learning Applied in Marine Science

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "New Sensors, New Technologies and Machine Learning in Water Sciences".

Deadline for manuscript submissions: closed (15 April 2023) | Viewed by 26825

Special Issue Editor

Dr. Ugur Avdan

E-Mail Website
Guest Editor
Research Institute of Earth and Space Sciences, Eskisehir Technical University, Iki Eylul Campus, 26470 Eskisehir, Turkey
Interests: remote sensing; geographic information science; machine learning algorithms; surveying

Special Issue Information

Dear Colleagues,

Remote sensing provides information about objects on earth by recording radiated or reflected radiation from objects. This information is usually recorded at a distance from above in the form of image data. The composition and nature of the earth’s surface can be monitored from local to global scales by using remote-sensing images; therefore, changes can be analyzed using images captured at different times. Remote-sensing data are extensively used to monitor coastlines by providing repeated and consistent statistics of coastal variations. On the other hand, Geographic Information Systems (GIS) are software tools used to store, analyze, process, manipulate, and update information in layers where geographic location is an important characteristic or critical to the analysis. GISs have the ability to collect, manage, analyze, and output a variety of geographic information with spatial and dynamic characteristics.

A computational concept called artificial intelligence (AI) enables computers to learn from data and approximatively solve difficult problems. Machine learning (ML), which is an application of AI, is a brand new area of study in the coastal sciences that provides effective and practical ways for simulating coastal morphodynamics. With the quantity, resolution, and availability of remote-sensing data, complex coastal issues can be solved effectively by ML. Additionally, GIS's ability to manage and analyze spatial data provides essential tools for marine science. This Special Issue intends to demonstrate how coastal dynamics can be used in combination with remote-sensing data, Geographic Information Systems, and machine learning to provide an attractive solution for coastal management problems.

Dr. Ugur Avdan
Guest Editor

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. Water 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 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

  • remote sensing
  • geographic information systems
  • machine learning
  • artificial intelligence
  • marine science

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Review

58 pages, 5780 KiB  
Review
Ocean Remote Sensing Techniques and Applications: A Review (Part II)
by Meisam Amani, Soroosh Mehravar, Reza Mohammadi Asiyabi, Armin Moghimi, Arsalan Ghorbanian, Seyed Ali Ahmadi, Hamid Ebrahimy, Sayyed Hamed Alizadeh Moghaddam, Amin Naboureh, Babak Ranjgar, Farzane Mohseni, Mohsen Eslami Nazari, Sahel Mahdavi, S. Mohammad Mirmazloumi, Saeid Ojaghi and Shuanggen Jin
Water 2022, 14(21), 3401; https://doi.org/10.3390/w14213401 - 26 Oct 2022
Cited by 22 | Viewed by 10926
Abstract
As discussed in the first part of this review paper, Remote Sensing (RS) systems are great tools to study various oceanographic parameters. Part I of this study described different passive and active RS systems and six applications of RS in ocean studies, including [...] Read more.
As discussed in the first part of this review paper, Remote Sensing (RS) systems are great tools to study various oceanographic parameters. Part I of this study described different passive and active RS systems and six applications of RS in ocean studies, including Ocean Surface Wind (OSW), Ocean Surface Current (OSC), Ocean Wave Height (OWH), Sea Level (SL), Ocean Tide (OT), and Ship Detection (SD). In Part II, the remaining nine important applications of RS systems for ocean environments, including Iceberg, Sea Ice (SI), Sea Surface temperature (SST), Ocean Surface Salinity (OSS), Ocean Color (OC), Ocean Chlorophyll (OCh), Ocean Oil Spill (OOS), Underwater Ocean, and Fishery are comprehensively reviewed and discussed. For each application, the applicable RS systems, their advantages and disadvantages, various RS and Machine Learning (ML) techniques, and several case studies are discussed. Full article
(This article belongs to the Special Issue RS, GIS and Machine Learning Applied in Marine Science)
►▼ Show Figures

Figure 1

51 pages, 5269 KiB  
Review
Ocean Remote Sensing Techniques and Applications: A Review (Part I)
by Meisam Amani, Armin Moghimi, S. Mohammad Mirmazloumi, Babak Ranjgar, Arsalan Ghorbanian, Saeid Ojaghi, Hamid Ebrahimy, Amin Naboureh, Mohsen Eslami Nazari, Sahel Mahdavi, Sayyed Hamed Alizadeh Moghaddam, Reza Mohammadi Asiyabi, Seyed Ali Ahmadi, Soroosh Mehravar, Farzane Mohseni and Shuanggen Jin
Water 2022, 14(21), 3400; https://doi.org/10.3390/w14213400 - 26 Oct 2022
Cited by 34 | Viewed by 14969
Abstract
Oceans cover over 70% of the Earth’s surface and provide numerous services to humans and the environment. Therefore, it is crucial to monitor these valuable assets using advanced technologies. In this regard, Remote Sensing (RS) provides a great opportunity to study different oceanographic [...] Read more.
Oceans cover over 70% of the Earth’s surface and provide numerous services to humans and the environment. Therefore, it is crucial to monitor these valuable assets using advanced technologies. In this regard, Remote Sensing (RS) provides a great opportunity to study different oceanographic parameters using archived consistent multitemporal datasets in a cost-efficient approach. So far, various types of RS techniques have been developed and utilized for different oceanographic applications. In this study, 15 applications of RS in the ocean using different RS techniques and systems are comprehensively reviewed and discussed. This study is divided into two parts to supply more detailed information about each application. The first part briefly discusses 12 different RS systems that are often employed for ocean studies. Then, six applications of these systems in the ocean, including Ocean Surface Wind (OSW), Ocean Surface Current (OSC), Ocean Wave Height (OWH), Sea Level (SL), Ocean Tide (OT), and Ship Detection (SD), are provided. For each application, the applicable RS systems, their advantages and disadvantages, various RS and Machine Learning (ML) techniques, and several case studies are discussed. The other nine applications, including Iceberg, Sea Ice (SI), Sea Surface temperature (SST), Ocean Surface Salinity (OSS), Ocean Color (OC), Ocean Chlorophyll (OCh), Ocean Oil Spill (OOS), Underwater Ocean, and Fishery, are provided in Part II of this study. Full article
(This article belongs to the Special Issue RS, GIS and Machine Learning Applied in Marine Science)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop