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Remote Sensing in Monitoring Coastal and Inland Waters

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

Deadline for manuscript submissions: 31 July 2025 | Viewed by 793

Special Issue Editors


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Guest Editor
School of Land Science and Technology, China University of Geosciences (Beijing), Beijing 100083, China
Interests: satellite altimetry; hydrology; bathymetry; satellite gravity

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Guest Editor
State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Ningbo Research Institute, Zhejiang University, Hangzhou 310027, China
Interests: spaceborne oceanic lidar; remote sensing; hydrology; radiative transfer

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Guest Editor
School of Ocean Technology, Fisheries and Marine Institute, Memorial University of Newfoundland, St. John's, NL, Canada
Interests: LiDAR remote sensing; 3D point cloud processing; land cover classification; road features extraction; seafloor classification

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Guest Editor
National Satellite Ocean Application Service, Beijing 100081, China
Interests: sea level change; satellite altimetry; marine gravity; sea ice
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Special Issue Information

Dear Colleagues,

Water resources are crucial for human use, especially in coastal and inland water bodies. These also provide important and diverse habitats and ecosystem services, support high levels of biodiversity, and are critical components of global carbon and nutrient cycles. However, like many other ecosystems, coastal and inland waters are threatened by the synergistic effects of multiple, co-occurring environmental pressures, including nutrient enrichment and other forms of organic and inorganic pollution, climate change, acidification, the establishment and spread of invasive species, and the diversion or extraction of upstream source waters. Their importance, as well as their sensitivity to and capacity to reflect climate and environmental changes, has garnered increasing attention over recent years. Assessing and monitoring coastal and inland waters is crucial to understanding and disentangling the effects of environmental change on freshwater ecosystems and estimating ocean carbon cycles.

Whereas conventional monitoring approaches tend to be limited in terms of spatial coverage and temporal frequency, remote sensing has the potential to provide an invaluable complementary source of data at the local to global scales. In particular, satellite remote sensing, which is often used in open ocean observation, has played an increasingly significant role in coastal and inland water monitoring.

The objective of this Special Issue is to publish novel methods and views using satellite remote sensing techniques, including optical remote sensing, satellite gravity, and satellite altimetry, in the field of coastal and inland waters. We seek to discuss the issues related to water—such as storage distribution and temporal variation, water quality, and water depth—from different perspectives using various remote sensing data, especially new satellite data, such as the Surface Water and Ocean Topography (SWOT) mission. Topics including new algorithms, findings, explanations, and performance of the new data to monitor coastal and inland waters are all within the scope of this section. We also invite papers on new technology or missions for monitoring coastal and inland waters.

This special issue seeks relevant methods of coastal and inland water environmental monitoring, including but not limited to simulations, algorithms, instruments, and applications.

  • Monitoring coastal levels, quality,and variation;
  • Monitoring inland water levels, quality, and discharge;
  • Explanation and prediction of coastal and inland water variation;
  • Inversion or mapping of coastal and inland water bathymetry;
  • New technology for monitoring coastal and inland water.

Prof. Dr. Xiaoyun Wan
Dr. Qun Liu
Dr. Salem Morsy
Dr. Yongjun Jia
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

  • coastal and inland waters
  • satellite remote sensing
  • airborne/terrestrial/mobile LiDAR
  • water level/quality/depth
  • phytoplankton
  • carbon fluxes and stocks
  • Unmanned Aerial Vehicles (UAVs)

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Published Papers (1 paper)

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Research

27 pages, 8424 KiB  
Article
Research on the Algorithm of Lake Surface Height Inversion in Qinghai Lake Based on Sentinel-3A Altimeter
by Chuntao Chen, Xiaoqing Li, Jianhua Zhu, Hailong Peng, Youhua Xue, Wanlin Zhai, Mingsen Lin, Yufei Zhang, Jiajia Liu and Yili Zhao
Remote Sens. 2025, 17(4), 647; https://doi.org/10.3390/rs17040647 - 14 Feb 2025
Viewed by 489
Abstract
Lakes are a crucial component of inland water bodies, and changes in their water levels serve as key indicators of global climate change. Traditional methods of lake water level monitoring rely heavily on hydrological stations, but there are problems such as regional representativeness, [...] Read more.
Lakes are a crucial component of inland water bodies, and changes in their water levels serve as key indicators of global climate change. Traditional methods of lake water level monitoring rely heavily on hydrological stations, but there are problems such as regional representativeness, data stability, and high maintenance costs. The satellite altimeter is an essential tool in lake research, with the Synthetic Aperture Radar (SAR) altimeter offering a high spatial resolution. This enables precise and quantitative observations of lake water levels on a large scale. In this study, we used Sentinel-3A SAR Radar Altimeter (SRAL) data to establish a more reasonable lake height inversion algorithm for satellite-derived lake heights. Subsequently, using this technology, a systematic analysis study was conducted with Qinghai Lake as the case study area. By employing regional filtering, threshold filtering, and altimeter range filtering techniques, we obtained effective satellite altimeter height measurements of the lake surface height. To enhance the accuracy of the data, we combined these measurements with GPS buoy-based geoid data from Qinghai Lake, normalizing lake surface height data from different periods and locations to a fixed reference point. A dataset based on SAR altimeter data was then constructed to track lake surface height changes in Qinghai Lake. Using data from the Sentinel-3A altimeter’s 067 pass over Qinghai Lake, which has spanned 96 cycles since its launch in 2016, we analyzed over seven years of lake surface height variations. The results show that the lake surface height exhibits distinct seasonal patterns, peaking in September and October and reaching its lowest levels in April and May. From 2016 to 2023, Qinghai Lake showed a general upward trend, with an increase of 2.41 m in lake surface height, corresponding to a rate of 30.0 cm per year. Specifically, from 2016 to 2020, the lake surface height rose at a rate of 47.2 cm per year, while from 2020 to 2022, the height remained relatively stable. Full article
(This article belongs to the Special Issue Remote Sensing in Monitoring Coastal and Inland Waters)
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