Remote Sensing Retrievals of Optical Properties in Inland Waters and the Coastal Ocean
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: closed (31 March 2024) | Viewed by 33422
Special Issue Editors
Interests: algal blooms; chlorophyll a; phycocyanin; suspended particulate matter; secchi disk depth; total nitrogen; total phosphorus; turbidity
Interests: validation and vicarious calibration of satellite data; accuracy of satellite and in situ data (uncertainty and SI traceability); fiducial reference measurements; open ocean and coastal remote sensing of the Eastern Mediterranean; ocean color; sea surface temperature; albedo; BRDF; coastal zone; climate change
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Interests: inland water carbon cycle; remote sensing of greenhouse gases
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing of soil and water conservation; remote sensing of water environment; water resources management in response to climate change
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Special Issue Information
Dear Colleagues,
Inland waters and the coastal ocean are important components of the biosphere that contribute to atmospheric processes and the regulation of regional climates through primary production, carbon storage and greenhouse gas emissions. Inland waters also have economical functions and have been exploited as sources of water for agriculture, aquaculture, recreation and drinking water. The coastal ocean is the critical area for material exchange between land and ocean, and thus, has an extremely important ecological value. In recent decades, the pollution from industrialization and urbanization has negatively impacted inland waters and the coastal ocean, water transparency has decreased, eutrophication has intensified, and cyanobacteria blooms have frequently occurred. Given the opportunity for large-scale, synchronous observations and the availability of long-term datasets, satellite images have become a mainstream data source to research global and regional aquatic environments.
Water color remote sensing is one of the main topics in this journal. Our Special Issue fits very well with this topic. The optical or non-optical parameters of inland waters and the coastal ocean are estimated by using multispectral or hyperspectral radiance data, with these derived products based on bio-optical models that consist of empirical/semi-empirical, analytical/semi-analytical, quasi-analytical, machine learning and other algorithms. Furthermore, their spatiotemporal variation trends are evaluated, and the driving factors of water quality evolution are explored in combination with anthropogenic activities or climatic change factors in the basin. This represents the main research content of water color remote sensing.
This Special Issue invites manuscripts addressing the challenges in remote sensing retrievals of optical properties of inland waters and the coastal ocean, with a broad outline of its scope including, but not limited to, the following:
- Optical water quality parameter retrieval, such as for chlorophyll a, suspended particulate matter, phycocyanin, etc., in inland waters and the coastal ocean.
- Non-optical water quality parameter retrieval, such as for total phosphorus, total nitrogen, etc., in inland waters and the coastal ocean.
- Algal bloom detection, aquatic vegetation and water temperature retrieval in inland waters and the coastal ocean.
- Vertical water quality parameter retrieval, such as chlorophyll a, suspended particulate matter, etc., in inland waters and the coastal ocean using active Lidar or passive remote sensing.
- Vertical phytoplankton biomass and primary productivity retrieval in inland waters and the coastal ocean using active Lidar or passive remote sensing.
- Application of artificial intelligence (AI) or machine learning in the remote estimation of water quality in inland waters and the coastal ocean.
- Application of unmanned aerial vehicles (UAVs) in the remote estimation of water quality in inland waters and the coastal ocean.
- Climate change and spatiotemporal variation of water quality in inland waters and the coastal ocean.
- Anthropogenic factors and spatiotemporal variation of water quality in inland waters and the coastal ocean.
- Novel or improved bio-optical models in the retrieval of optical properties in inland waters and the coastal ocean.
Dr. Chong Fang
Dr. Andrew Clive Banks
Dr. Zhidan Wen
Dr. Shaohua Lei
Guest Editors
Manuscript Submission Information
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Keywords
- optical water quality parameter retrieval
- non-optical water quality parameter retrieval
- algal bloom
- aquatic vegetation
- water temperature retrieval
- machine learning
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