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Monitoring and Mapping Inland and Coastal Water Dynamics Based on Landsat Data

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ecological Remote Sensing".

Deadline for manuscript submissions: closed (30 March 2024) | Viewed by 1206

Special Issue Editors


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Guest Editor
Department of Geological Engineering, Middle East Technical University, Ankara, Turkey
Interests: hydrology; remote sensing; hydrological models; floods/droughts; inland water dynamics

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Guest Editor
Fondazione Bruno Kessler (FBK), Trento, Italy
Interests: remote sensing; inland waters; coastal waters
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, UK
Interests: remote sensing; hydrological and hydraulic modelling; water resources sustainability

Special Issue Information

Dear Colleagues,

Monitoring and mapping inland water dynamics via remote sensing techniques provide critical support for hydrology, ecology, and climate change studies. Among the ever-increasing number of earth observation satellite platforms, the NASA/USGS Landsat program, first launched in 1972, stands out as providing the longest continuous space-based measurements with spectral, spatial, and temporal scales that are well suited to observe patterns, cycles, changes, and trends in a variety of natural and built environments, including inland and coastal waters. Marking the Landsat program’s 50th year anniversary, this Special Issue aims to archive a collection of original research articles and comprehensive reviews focusing on the utility of the Landsat program in monitoring and mapping inland and coastal water dynamics, with a specific focus on, but not limited to, the following topics:

  • Dynamics of water quantity and quality in coastal environments, lakes, rivers, and reservoirs at regional and global scales, and their relationships to anthropogenic and climatic drivers;
  • Dynamics of algal biomass, organic and inorganic suspended solids, and colored dissolved organic matter in inland and coastal waters;
  • Analysis of long-term trends focusing on the impact of land use/landcover change and climate change;
  • Use of Landsat data in cloud computing platforms such as Google Earth Engine, Amazon Web Services, etc.;
  • Utility of machine and deep learning algorithms;
  • Correction and fusion techniques to increase information content;
  • Challenges and limitations in spectral, spatial, and temporal coverage of Landsat platforms;
  • Comparison of Landsat dataset with other earth observation missions;
  • Bathymetric mapping of shallow waters.

Dr. Koray K. Yilmaz
Dr. Milad Niroumand-Jadidi
Dr. Belén Martí-Cardona
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.

Keywords

  • Landsat
  • inland and coastal waters
  • water extent
  • water quality
  • bathymetry
  • environmental impact assessment

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Published Papers (1 paper)

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Research

30 pages, 42903 KiB  
Article
Monitoring Chlorophyll-a Concentration Variation in Fish Ponds from 2013 to 2022 in the Guangdong-Hong Kong-Macao Greater Bay Area, China
by Zikang Li, Xiankun Yang, Tao Zhou, Shirong Cai, Wenxin Zhang, Keming Mao, Haidong Ou, Lishan Ran, Qianqian Yang and Yibo Wang
Remote Sens. 2024, 16(11), 2033; https://doi.org/10.3390/rs16112033 - 5 Jun 2024
Viewed by 714
Abstract
Aquaculture plays a vital role in global food production, with fish pond water quality directly impacting aquatic product quality. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) serves as a key producer of aquatic products in South China. Monitoring environmental changes in fish ponds [...] Read more.
Aquaculture plays a vital role in global food production, with fish pond water quality directly impacting aquatic product quality. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) serves as a key producer of aquatic products in South China. Monitoring environmental changes in fish ponds serves as an indicator of their health. This study employed the extreme gradient boosting tree (BST) model of machine learning, utilizing Landsat imagery data, to assess Chlorophyll-a (Chl-a) concentration in GBA fish ponds from 2013 to 2022. The study also examined the corresponding spatiotemporal variations in Chl-a concentration. Key findings include: (1) clear seasonal fluctuations in Chl-a concentration, peaking in summer (56.7 μg·L−1) and reaching lows in winter (43.5 μg·L−1); (2) a slight overall increase in Chl-a concentration over the study period, notably in regions with rapid economic development, posing a heightened risk of eutrophication; (3) influence from both human activities and natural factors such as water cycle and climate, with water temperature notably impacting summer Chl-a levels; (4) elevated Chl-a levels in fish ponds compared to surrounding natural water bodies, primarily attributed to human activities, indicating an urgent need to revise breeding practices and address eutrophication. These findings offer a quantitative assessment of fish pond water quality and contribute to sustainable aquaculture management in the GBA. Full article
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