Remote Sensing Retrievals of Optical Properties in Inland Waters and the Coastal Ocean

Inland waters and the coastal ocean are vital components of the biosphere, underpinning atmospheric processes and regional climate regulation through primary production, carbon storage, and greenhouse gas emissions. Inland waters also serve economic roles, providing water for agriculture, aquacultur...

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_version_ 1869523023798730752
collection Directory of Open Access Books
description Inland waters and the coastal ocean are vital components of the biosphere, underpinning atmospheric processes and regional climate regulation through primary production, carbon storage, and greenhouse gas emissions. Inland waters also serve economic roles, providing water for agriculture, aquaculture, recreation, and drinking. As the key zone for land–ocean material exchange, the coastal ocean holds immense ecological value. In recent decades, industrial and urban pollution has had a catastrophic impact on these aquatic systems, reducing water transparency, intensifying eutrophication, and triggering frequent cyanobacteria blooms. With large-scale synchronous observation capabilities and long-term datasets, satellite imagery has become a mainstream data source for global and regional aquatic environment research. Water colour remote sensing is a core focus of this journal, and this Special Issue is in close alignment with this theme. The research contained herein primarily involves the retrieval of the optical/non-optical parameters of inland and coastal waters from multispectral or hyperspectral radiance data. These derived products rely on bio-optical models integrating empirical/semi-empirical, analytical/semi-analytical, quasi-analytical, and machine learning algorithms.
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publisher MDPI - Multidisciplinary Digital Publishing Institute
publisherStr MDPI - Multidisciplinary Digital Publishing Institute
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spelling doab-20.500.12854ir-1750822026-04-16T18:50:00Z Remote Sensing Retrievals of Optical Properties in Inland Waters and the Coastal Ocean Fang, Chong Banks, Andrew Clive Wen, Zhidan Lei, Shaohua Airborne drone UAV Optical water quality Automated drone image processing MapEO water Inland and coastal waters Georeferencing Sky glint ICOR Eutrophication Poyang Lake Basin (PLB) Landsat-8 OLI Spatio-temporal patterns Atmospheric correction Turbid water Ocean color Black pixel Water resources monitoring Republic of Ireland Remote sensing Landsat-8 Sentinel-2 Lake Xingkai Chla OLCI High solar zenith angle Turbidity Water quality Sentinel-2A B 9 Yangtze-Huaihe lakes Total phosphorus Machine learning Sentinel-3 OLCI Bohai Sea Total suspended particulate matter (TSM) Gaofen imagery Remote sensing inversion Yellow River estuary Consistency evaluation Random forest Temporal and spatial variations Water quality retrieval Hyperspectral data Multispectral data Characteristic spectral bands Artificial neural network CO2 flux CO2 budget Carbon cycle Chagan Lake Chromophoric dissolved organic matter Dissolved organic carbon Chemical oxygen demand Aquatic vegetation Deep learning Automatic extraction Lake Honghu Sentinel-2 MSI Artificial Ecosystem Optimization Chlorophyll-a Backpropagation neural network Hong Kong Google Earth Engine GOCI Algal blooms Water quality parameters PRISMA DESIS EnMAP Shallow lake Water reflectance Phytoplankton Bio-optical model thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general Inland waters and the coastal ocean are vital components of the biosphere, underpinning atmospheric processes and regional climate regulation through primary production, carbon storage, and greenhouse gas emissions. Inland waters also serve economic roles, providing water for agriculture, aquaculture, recreation, and drinking. As the key zone for land–ocean material exchange, the coastal ocean holds immense ecological value. In recent decades, industrial and urban pollution has had a catastrophic impact on these aquatic systems, reducing water transparency, intensifying eutrophication, and triggering frequent cyanobacteria blooms. With large-scale synchronous observation capabilities and long-term datasets, satellite imagery has become a mainstream data source for global and regional aquatic environment research. Water colour remote sensing is a core focus of this journal, and this Special Issue is in close alignment with this theme. The research contained herein primarily involves the retrieval of the optical/non-optical parameters of inland and coastal waters from multispectral or hyperspectral radiance data. These derived products rely on bio-optical models integrating empirical/semi-empirical, analytical/semi-analytical, quasi-analytical, and machine learning algorithms. 2026-04-16T18:49:51Z 2026-04-16T18:49:51Z 2025 book ONIX_20260416T142754_9783725859757_37 9783725859757 9783725859764 https://directory.doabooks.org/handle/20.500.12854/175082 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/ https://mdpi.com/books/pdfview/book/11986 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-5976-4 10.3390/books978-3-7258-5976-4 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725859757 9783725859764 342 CH open access
spellingShingle Airborne drone
UAV
Optical water quality
Automated drone image processing
MapEO water
Inland and coastal waters
Georeferencing
Sky glint
ICOR
Eutrophication
Poyang Lake Basin (PLB)
Landsat-8 OLI
Spatio-temporal patterns
Atmospheric correction
Turbid water
Ocean color
Black pixel
Water resources monitoring
Republic of Ireland
Remote sensing
Landsat-8
Sentinel-2
Lake Xingkai
Chla
OLCI
High solar zenith angle
Turbidity
Water quality
Sentinel-2A
B
9
Yangtze-Huaihe lakes
Total phosphorus
Machine learning
Sentinel-3 OLCI
Bohai Sea
Total suspended particulate matter (TSM)
Gaofen imagery
Remote sensing inversion
Yellow River estuary
Consistency evaluation
Random forest
Temporal and spatial variations
Water quality retrieval
Hyperspectral data
Multispectral data
Characteristic spectral bands
Artificial neural network
CO2 flux
CO2 budget
Carbon cycle
Chagan Lake
Chromophoric dissolved organic matter
Dissolved organic carbon
Chemical oxygen demand
Aquatic vegetation
Deep learning
Automatic extraction
Lake Honghu
Sentinel-2 MSI
Artificial Ecosystem Optimization
Chlorophyll-a
Backpropagation neural network
Hong Kong
Google Earth Engine
GOCI
Algal blooms
Water quality parameters
PRISMA
DESIS
EnMAP
Shallow lake
Water reflectance
Phytoplankton
Bio-optical model
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
Remote Sensing Retrievals of Optical Properties in Inland Waters and the Coastal Ocean
title Remote Sensing Retrievals of Optical Properties in Inland Waters and the Coastal Ocean
title_full Remote Sensing Retrievals of Optical Properties in Inland Waters and the Coastal Ocean
title_fullStr Remote Sensing Retrievals of Optical Properties in Inland Waters and the Coastal Ocean
title_full_unstemmed Remote Sensing Retrievals of Optical Properties in Inland Waters and the Coastal Ocean
title_short Remote Sensing Retrievals of Optical Properties in Inland Waters and the Coastal Ocean
title_sort remote sensing retrievals of optical properties in inland waters and the coastal ocean
topic Airborne drone
UAV
Optical water quality
Automated drone image processing
MapEO water
Inland and coastal waters
Georeferencing
Sky glint
ICOR
Eutrophication
Poyang Lake Basin (PLB)
Landsat-8 OLI
Spatio-temporal patterns
Atmospheric correction
Turbid water
Ocean color
Black pixel
Water resources monitoring
Republic of Ireland
Remote sensing
Landsat-8
Sentinel-2
Lake Xingkai
Chla
OLCI
High solar zenith angle
Turbidity
Water quality
Sentinel-2A
B
9
Yangtze-Huaihe lakes
Total phosphorus
Machine learning
Sentinel-3 OLCI
Bohai Sea
Total suspended particulate matter (TSM)
Gaofen imagery
Remote sensing inversion
Yellow River estuary
Consistency evaluation
Random forest
Temporal and spatial variations
Water quality retrieval
Hyperspectral data
Multispectral data
Characteristic spectral bands
Artificial neural network
CO2 flux
CO2 budget
Carbon cycle
Chagan Lake
Chromophoric dissolved organic matter
Dissolved organic carbon
Chemical oxygen demand
Aquatic vegetation
Deep learning
Automatic extraction
Lake Honghu
Sentinel-2 MSI
Artificial Ecosystem Optimization
Chlorophyll-a
Backpropagation neural network
Hong Kong
Google Earth Engine
GOCI
Algal blooms
Water quality parameters
PRISMA
DESIS
EnMAP
Shallow lake
Water reflectance
Phytoplankton
Bio-optical model
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
topic_facet Airborne drone
UAV
Optical water quality
Automated drone image processing
MapEO water
Inland and coastal waters
Georeferencing
Sky glint
ICOR
Eutrophication
Poyang Lake Basin (PLB)
Landsat-8 OLI
Spatio-temporal patterns
Atmospheric correction
Turbid water
Ocean color
Black pixel
Water resources monitoring
Republic of Ireland
Remote sensing
Landsat-8
Sentinel-2
Lake Xingkai
Chla
OLCI
High solar zenith angle
Turbidity
Water quality
Sentinel-2A
B
9
Yangtze-Huaihe lakes
Total phosphorus
Machine learning
Sentinel-3 OLCI
Bohai Sea
Total suspended particulate matter (TSM)
Gaofen imagery
Remote sensing inversion
Yellow River estuary
Consistency evaluation
Random forest
Temporal and spatial variations
Water quality retrieval
Hyperspectral data
Multispectral data
Characteristic spectral bands
Artificial neural network
CO2 flux
CO2 budget
Carbon cycle
Chagan Lake
Chromophoric dissolved organic matter
Dissolved organic carbon
Chemical oxygen demand
Aquatic vegetation
Deep learning
Automatic extraction
Lake Honghu
Sentinel-2 MSI
Artificial Ecosystem Optimization
Chlorophyll-a
Backpropagation neural network
Hong Kong
Google Earth Engine
GOCI
Algal blooms
Water quality parameters
PRISMA
DESIS
EnMAP
Shallow lake
Water reflectance
Phytoplankton
Bio-optical model
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
url ONIX_20260416T142754_9783725859757_37