22.5.6 Water Quality, Turbidity, Water Areas

Chapter Contents (Back)
Classification. Water Quality. Turbidity.
See also Organic Carbon, Dissolved Organic Matter, Water Quality.
See also Sediment, Suspended Sediment, Silt, Water Quality.
See also Suspended Particulates, Suspended Matter, Water Quality.
See also Chlorophyll Estimation in Water. Color basis for ocean analysis:
See also Ocean Color Analysis, Ocean Colour Analysis, Water Quality.
See also Plankton Analysis, Extraction, Features, Small Scale and Large Scale.
See also Cyanobacteria, Analysis, Detection.

Yang, W.[Wei], Matsushita, B., Chen, J.[Jin], Yoshimura, K., Fukushima, T.,
Retrieval of Inherent Optical Properties for Turbid Inland Waters From Remote-Sensing Reflectance,
GeoRS(51), No. 6, 2013, pp. 3761-3773.
IEEE DOI 1307
lakes; water quality BibRef

Palmer, S.C.J.[Stephanie C.J.], Pelevin, V.V.[Vadim V.], Goncharenko, I.[Igor], Kovács, A.W.[Attila W.], Zlinszky, A.[András], Présing, M.[Mátyás], Horváth, H.[Hajnalka], Nicolás-Perea, V.[Virginia], Balzter, H.[Heiko], Tóth, V.R.[Viktor R.],
Ultraviolet Fluorescence LiDAR (UFL) as a Measurement Tool for Water Quality Parameters in Turbid Lake Conditions,
RS(5), No. 9, 2013, pp. 4405-4422.
DOI Link 1310
BibRef

Lee, Z., Weidemann, A., Arnone, R.,
Combined Effect of Reduced Band Number and Increased Bandwidth on Shallow Water Remote Sensing: The Case of WorldView 2,
GeoRS(51), No. 5, May 2013, pp. 2577-2586.
IEEE DOI 1305
BibRef

Ogashawara, I.[Igor], Moreno-Madrińán, M.J.[Max J.],
Improving Inland Water Quality Monitoring through Remote Sensing Techniques,
IJGI(3), No. 4, 2014, pp. 1234-1255.
DOI Link 1412
BibRef

Liu, X.H.[Xiao-Han], Zhang, Y.L.[Yun-Lin], Shi, K.[Kun], Zhou, Y.Q.[Yong-Qiang], Tang, X.M.[Xiang-Ming], Zhu, G.W.[Guang-Wei], Qin, B.Q.[Bo-Qiang],
Mapping Aquatic Vegetation in a Large, Shallow Eutrophic Lake: A Frequency-Based Approach Using Multiple Years of MODIS Data,
RS(7), No. 8, 2015, pp. 10295.
DOI Link 1509
BibRef

Baughman, C.A.[Carson A.], Jones, B.M.[Benjamin M.], Bartz, K.K.[Krista K.], Young, D.B.[Daniel B.], Zimmerman, C.E.[Christian E.],
Reconstructing Turbidity in a Glacially Influenced Lake Using the Landsat TM and ETM+ Surface Reflectance Climate Data Record Archive, Lake Clark, Alaska,
RS(7), No. 10, 2015, pp. 13692.
DOI Link 1511
BibRef

Shen, Q.[Qian], Li, J.S.[Jun-Sheng], Zhang, F.F.[Fang-Fang], Sun, X.[Xu], Li, J.[Jun], Li, W.[Wei], Zhang, B.[Bing],
Classification of Several Optically Complex Waters in China Using in Situ Remote Sensing Reflectance,
RS(7), No. 11, 2015, pp. 14731.
DOI Link 1512
BibRef

Bramante, J.F.[James F.], Sin, T.M.[Tsai Min],
Optimization of a Semi-Analytical Algorithm for Multi-Temporal Water Quality Monitoring in Inland Waters with Wide Natural Variability,
RS(7), No. 12, 2015, pp. 15845.
DOI Link 1601
BibRef

Ampe, E.M., Raymaekers, D., Hestir, E.L., Jansen, M., Knaeps, E., Batelaan, O.,
A Wavelet-Enhanced Inversion Method for Water Quality Retrieval From High Spectral Resolution Data for Complex Waters,
GeoRS(53), No. 2, February 2015, pp. 869-882.
IEEE DOI 1411
hydrological techniques BibRef

Feng, Y., Liu, Q., Qu, Y., Liang, S.,
Estimation of the Ocean Water Albedo From Remote Sensing and Meteorological Reanalysis Data,
GeoRS(54), No. 2, February 2016, pp. 850-868.
IEEE DOI 1601
Biological system modeling BibRef

Lu, H.M.[Hui-Min], Li, Y.J.[Yu-Jie], Nakashima, S.[Shota], Serikawa, S.[Seiichi],
Turbidity Underwater Image Restoration Using Spectral Properties and Light Compensation,
IEICE(E99-D), No. 1, January 2016, pp. 219-227.
WWW Link. 1601
BibRef

Starr, S.M.[Scott M.], Heintzman, L.J.[Lucas J.], Mulligan, K.R.[Kevin R.], Barbato, L.S.[Lucia S.], McIntyre, N.E.[Nancy E.],
Using Remotely Sensed Imagery to Document How Land Use Drives Turbidity of Playa Waters in Texas,
RS(8), No. 3, 2016, pp. 192.
DOI Link 1604
BibRef

Poupardin, A., Idier, D., de Michele, M., Raucoules, D.,
Water Depth Inversion From a Single SPOT-5 Dataset,
GeoRS(54), No. 4, April 2016, pp. 2329-2342.
IEEE DOI 1604
Correlation BibRef

Kaabi, M.R.A.[Muna. R. Al], Zhao, J.[Jun], Ghedira, H.[Hosni],
MODIS-Based Mapping of Secchi Disk Depth Using a Qualitative Algorithm in the Shallow Arabian Gulf,
RS(8), No. 5, 2016, pp. 423.
DOI Link 1606
BibRef

Ko, D.S.[Dong S.], Gould, R.W.[Richard W.], Penta, B.[Bradley], Lehrter, J.C.[John C.],
Impact of Satellite Remote Sensing Data on Simulations of Coastal Circulation and Hypoxia on the Louisiana Continental Shelf,
RS(8), No. 5, 2016, pp. 435.
DOI Link 1606
BibRef

Kutser, T.[Tiit], Paavel, B.[Birgot], Verpoorter, C.[Charles], Ligi, M.[Martin], Soomets, T.[Tuuli], Toming, K.[Kaire], Casal, G.[Gema],
Remote Sensing of Black Lakes and Using 810 nm Reflectance Peak for Retrieving Water Quality Parameters of Optically Complex Waters,
RS(8), No. 6, 2016, pp. 497.
DOI Link 1608
BibRef

Kutser, T.[Tiit], Paavel, B.[Birgot], Verpoorter, C.[Charles], Kauer, T., Vahtmäe, E.,
Remote Sensing Of Water Quality In Optically Complex Lakes,
ISPRS12(XXXIX-B8:165-169).
DOI Link 1209
BibRef

Zolfaghari, K.[Kiana], Duguay, C.R.[Claude R.],
Estimation of Water Quality Parameters in Lake Erie from MERIS Using Linear Mixed Effect Models,
RS(8), No. 6, 2016, pp. 473.
DOI Link 1608
BibRef

Tan, J.[Jing], Cherkauer, K.A.[Keith A.], Chaubey, I.[Indrajeet],
Developing a Comprehensive Spectral-Biogeochemical Database of Midwestern Rivers for Water Quality Retrieval Using Remote Sensing Data: A Case Study of the Wabash River and Its Tributary, Indiana,
RS(8), No. 6, 2016, pp. 517.
DOI Link 1608
BibRef

Toming, K.[Kaire], Kutser, T.[Tiit], Laas, A.[Alo], Sepp, M.[Margot], Paavel, B.[Birgot], Nőges, T.[Tiina],
First Experiences in Mapping Lake Water Quality Parameters with Sentinel-2 MSI Imagery,
RS(8), No. 8, 2016, pp. 640.
DOI Link 1609
BibRef

Watanabe, F.[Fernanda], Mishra, D.R.[Deepak R.], Astuti, I.[Ike], Rodrigues, T.[Thanan], Alcântara, E.H.[Enner Heręnio], Imai, N.N.[Nilton N.], Barbosa, C.[Cláudio],
Parametrization and calibration of a quasi-analytical algorithm for tropical eutrophic waters,
PandRS(121), No. 1, 2016, pp. 28-47.
Elsevier DOI 1609
Quasi-analytical algorithm BibRef

di Polito, C.[Carmine], Ciancia, E.[Emanuele], Coviello, I.[Irina], Doxaran, D.[David], Lacava, T.[Teodosio], Pergola, N.[Nicola], Satriano, V.[Valeria], Tramutoli, V.[Valerio],
On the Potential of Robust Satellite Techniques Approach for SPM Monitoring in Coastal Waters: Implementation and Application over the Basilicata Ionian Coastal Waters Using MODIS-Aqua,
RS(8), No. 11, 2016, pp. 922.
DOI Link 1612
BibRef

Ma, J.H.[Jian-Hang], Song, K.S.[Kai-Shan], Wen, Z.D.[Zhi-Dan], Zhao, Y.[Ying], Shang, Y.X.[Ying-Xin], Fang, C.[Chong], Du, J.[Jia],
Spatial Distribution of Diffuse Attenuation of Photosynthetic Active Radiation and Its Main Regulating Factors in Inland Waters of Northeast China,
RS(8), No. 11, 2016, pp. 964.
DOI Link 1612
BibRef

Tamari, S.[Serge], Guerrero-Meza, V.[Vicente], Rifad, Y.[Younčs], Bravo-Inclán, L.[Luis], Sánchez-Chávez, J.J.[José Javier],
Stage Monitoring in Turbid Reservoirs with an Inclined Terrestrial Near-Infrared Lidar,
RS(8), No. 12, 2016, pp. 999.
DOI Link 1612
BibRef

Song, K.S.[Kai-Shan], Ma, J.H.[Jian-Hang], Wen, Z.D.[Zhi-Dan], Fang, C.[Chong], Shang, Y.X.[Ying-Xin], Zhao, Y.[Ying], Wang, M.[Ming], Du, J.[Jia],
Remote estimation of Kd (PAR) using MODIS and Landsat imagery for turbid inland waters in Northeast China,
PandRS(123), No. 1, 2017, pp. 159-172.
Elsevier DOI 1612
Light attenuation coefficients BibRef

Markelin, L.[Lauri], Simis, S.G.H.[Stefan G. H.], Hunter, P.D.[Peter D.], Spyrakos, E.[Evangelos], Tyler, A.N.[Andrew N.], Clewley, D.[Daniel], Groom, S.[Steve],
Atmospheric Correction Performance of Hyperspectral Airborne Imagery over a Small Eutrophic Lake under Changing Cloud Cover,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702
BibRef

Vadakke-Chanat, S., Shanmugam, P., Ahn, Y.H.,
A Model for Deriving the Spectral Backscattering Properties of Particles in Inland and Marine Waters From In Situ and Remote Sensing Data,
GeoRS(55), No. 3, March 2017, pp. 1461-1476.
IEEE DOI 1703
Absorption BibRef

Li, C., Li, X., Zhang, G., Boswell, K.M., Kimball, M.E., Shen, D., Lin, J.,
Estuarine Plume: A Case Study by Satellite SAR Observations and In Situ Measurements,
GeoRS(55), No. 4, April 2017, pp. 2276-2287.
IEEE DOI 1704
lakes BibRef

Joshi, I.D.[Ishan D.], d'Sa, E.J.[Eurico J.], Osburn, C.L.[Christopher L.], Bianchi, T.S.[Thomas S.],
Turbidity in Apalachicola Bay, Florida from Landsat 5 TM and Field Data: Seasonal Patterns and Response to Extreme Events,
RS(9), No. 4, 2017, pp. xx-yy.
DOI Link 1705
BibRef

Hansen, C.H.[Carly Hyatt], Burian, S.J.[Steven J.], Dennison, P.E.[Philip E.], Williams, G.P.[Gustavious P.],
Spatiotemporal Variability of Lake Water Quality in the Context of Remote Sensing Models,
RS(9), No. 5, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Wei, J.A., Wang, D., Gong, F., He, X., Bai, Y.,
The Influence of Increasing Water Turbidity on Sea Surface Emissivity,
GeoRS(55), No. 6, June 2017, pp. 3501-3515.
IEEE DOI 1706
Atmospheric measurements, Ocean temperature, Optical surface waves, Radiometry, Sea measurements, Sea surface, Emissivity, remote sensing, sea surface temperature (SST), water turbidity BibRef

Zhao, J.H.[Jian-Hu], Zhao, X.L.[Xing-Lei], Zhang, H.M.[Hong-Mei], Zhou, F.N.[Feng-Nian],
Shallow Water Measurements Using a Single Green Laser Corrected by Building a Near Water Surface Penetration Model,
RS(9), No. 5, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Moknatian, M.[Mahrokh], Piasecki, M.[Michael], Gonzalez, J.[Jorge],
Development of Geospatial and Temporal Characteristics for Hispaniola's Lake Azuei and Enriquillo Using Landsat Imagery,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Jorge, D.S.F.[Daniel S.F.], Barbosa, C.C.F.[Claudio C.F.], de Carvalho, L.A.S.[Lino A. S.], Affonso, A.G.[Adriana G.], de Lucia Lobo, F.[Felipe], de Moraes Novo, E.M.L.[Evlyn Márcia Leăo],
SNR (Signal-To-Noise Ratio) Impact on Water Constituent Retrieval from Simulated Images of Optically Complex Amazon Lakes,
RS(9), No. 7, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Zhang, Y.L.[Yun-Lin], Giardino, C.[Claudia], Li, L.H.[Lin-Hai],
Water Optics and Water Colour Remote Sensing,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Ni, S.N.[Sheng-Nan], Chen, J.L.[Jian-Li], Wilson, C.R.[Clark R.], Hu, X.G.[Xiao-Gong],
Long-Term Water Storage Changes of Lake Volta from GRACE and Satellite Altimetry and Connections with Regional Climate,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Huang, C.C.[Chang-Chun], Yao, L.[Ling],
Semi-Analytical Retrieval of the Diffuse Attenuation Coefficient in Large and Shallow Lakes from GOCI, a High Temporal-Resolution Satellite,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Shrestha, A.[Anil], Luo, W.[Wei],
Analysis of Groundwater Nitrate Contamination in the Central Valley: Comparison of the Geodetector Method, Principal Component Analysis and Geographically Weighted Regression,
IJGI(6), No. 10, 2017, pp. xx-yy.
DOI Link 1710
BibRef

Shrestha, A.[Anil], Luo, W.[Wei],
Assessment of Groundwater Nitrate Pollution Potential in Central Valley Aquifer Using Geodetector-Based Frequency Ratio (GFR) and Optimized-DRASTIC Methods,
IJGI(7), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Toming, K.[Kaire], Kutser, T.[Tiit], Uiboupin, R.[Rivo], Arikas, A.[Age], Vahter, K.[Kaimo], Paavel, B.[Birgot],
Mapping Water Quality Parameters with Sentinel-3 Ocean and Land Colour Instrument imagery in the Baltic Sea,
RS(9), No. 10, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Fischer, A.M.[Andrew M.], Pang, D.[Daniel], Kidd, I.M.[Ian M.], Moreno-Madrińán, M.J.[Max J.],
Spatio-Temporal Variability in a Turbid and Dynamic Tidal Estuarine Environment (Tasmania, Australia): An Assessment of MODIS Band 1 Reflectance,
IJGI(6), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Nazeer, M.[Majid], Waqas, A.[Ahmad], Bilal, M.[Muhammad], Shahzad, M.I.[Muhammad Imran], Alsahli, M.M.M.[Mohammad M. M.],
Evaluation of Empirical and Machine Learning Algorithms for Estimation of Coastal Water Quality Parameters,
IJGI(6), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Wang, Y.C.[Yong-Chao], Shen, F.[Fang], Sokoletsky, L.[Leonid], Sun, X.R.[Xue-Rong],
Validation and Calibration of QAA Algorithm for CDOM Absorption Retrieval in the Changjiang (Yangtze) Estuarine and Coastal Waters,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Gunaalan, K.[Kuddithamby], Ranagalage, M.[Manjula], Gunarathna, M.H.J.P.[M. H. J. P.], Kumari, M.K.N., Vithanage, M.[Meththika], Srivaratharasan, T.[Tharmalingam], Saravanan, S.[Suntharalingam], Warnasuriya, T.W.S.,
Application of Geospatial Techniques for Groundwater Quality and Availability Assessment: A Case Study in Jaffna Peninsula, Sri Lanka,
IJGI(7), No. 1, 2018, pp. xx-yy.
DOI Link 1801
BibRef

Miralha, L.[Lorrayne], Kim, D.[Daehyun],
Accounting for and Predicting the Influence of Spatial Autocorrelation in Water Quality Modeling,
IJGI(7), No. 2, 2018, pp. xx-yy.
DOI Link 1802
BibRef

Powers, C.[Craig], Hanlon, R.[Regina], Schmale, D.G.[David G.],
Tracking of a Fluorescent Dye in a Freshwater Lake with an Unmanned Surface Vehicle and an Unmanned Aircraft System,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link 1802
BibRef

Larnicol, M.[Morgane], Launeau, P.[Patrick], Gernez, P.[Pierre],
Using High-Resolution Airborne Data to Evaluate MERIS Atmospheric Correction and Intra-Pixel Variability in Nearshore Turbid Waters,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
BibRef

McCarthy, M.J.[Matthew J.], Otis, D.B.[Daniel B.], Méndez-Lázaro, P.[Pablo], Muller-Karger, F.E.[Frank E.],
Water Quality Drivers in 11 Gulf of Mexico Estuaries,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Göritz, A.[Anna], Berger, S.A.[Stella A.], Gege, P.[Peter], Grossart, H.P.[Hans-Peter], Nejstgaard, J.C.[Jens C.], Riedel, S.[Sebastian], Röttgers, R.[Rüdiger], Utschig, C.[Christian],
Retrieval of Water Constituents from Hyperspectral In-Situ Measurements under Variable Cloud Cover: A Case Study at Lake Stechlin (Germany),
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Kratzer, S.[Susanne], Moore, G.[Gerald],
Inherent Optical Properties of the Baltic Sea in Comparison to Other Seas and Oceans,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804
BibRef

van der Woerd, H.J.[Hendrik Jan], Wernand, M.R.[Marcel Robert],
Hue-Angle Product for Low to Medium Spatial Resolution Optical Satellite Sensors,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
Color for water quality analysis. BibRef

Yang, G.[Gang], Wang, X.H.[Xiao-Hua], Ritchie, E.A.[Elizabeth A.], Qiao, L.[Lulu], Li, G.X.[Guang-Xue], Cheng, Z.X.[Zhi-Xin],
Using 250-M Surface Reflectance MODIS Aqua/Terra Product to Estimate Turbidity in a Macro-Tidal Harbour: Darwin Harbour, Australia,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
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Bi, S.[Shun], Li, Y.M.[Yun-Mei], Wang, Q.[Qiao], Lyu, H.[Heng], Liu, G.[Ge], Zheng, Z.B.[Zhu-Bin], Du, C.G.[Cheng-Gong], Mu, M.[Meng], Xu, J.[Jie], Lei, S.H.[Shao-Hua], Miao, S.[Song],
Inland Water Atmospheric Correction Based on Turbidity Classification Using OLCI and SLSTR Synergistic Observations,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
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Li, H.X.[Hui-Xuan], Wang, C.Z.[Cui-Zhen], Huang, X.[Xiao], Hug, A.[Andrew],
Spatial Assessment of Water Quality with Urbanization in 2007-2015, Shanghai, China,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
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Hilton, A.E.[Annette E.], Bausell, J.T.[Jesse T.], Kudela, R.M.[Raphael M.],
Quantification of Polychlorinated Biphenyl (PCB) Concentration in San Francisco Bay Using Satellite Imagery,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
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Lehmann, M.K.[Moritz K.], Nguyen, U.[Uyen], Allan, M.[Mathew], van der Woerd, H.J.[Hendrik Jan],
Colour Classification of 1486 Lakes across a Wide Range of Optical Water Types,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809
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Dettmering, D.[Denise], Wynne, A.[Alan], Müller, F.L.[Felix L.], Passaro, M.[Marcello], Seitz, F.[Florian],
Lead Detection in Polar Oceans: A Comparison of Different Classification Methods for Cryosat-2 SAR Data,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809
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Betancur-Turizo, S.P.[Stella Patricia], González-Silvera, A.[Adriana], Santamaría-del-Ángel, E.[Eduardo], Tan, J.[Jing], Frouin, R.[Robert],
Evaluation of Semi-Analytical Algorithms to Retrieve Particulate and Dissolved Absorption Coefficients in Gulf of California Optically Complex Waters,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810
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Xu, X.[Xuan], Huang, X.L.[Xiao-Long], Zhang, Y.L.[Yun-Lin], Yu, D.[Dan],
Long-Term Changes in Water Clarity in Lake Liangzi Determined by Remote Sensing,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810
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Pahlevan, N.[Nima], Balasubramanian, S.V.[Sundarabalan V.], Sarkar, S.[Sudipta], Franz, B.A.[Bryan A.],
Toward Long-Term Aquatic Science Products from Heritage Landsat Missions,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810
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Rudorff, N.[Natalia], Rudorff, C.M.[Conrado M.], Kampel, M.[Milton], Ortiz, G.[Gustavo],
Remote sensing monitoring of the impact of a major mining wastewater disaster on the turbidity of the Doce River plume off the eastern Brazilian coast,
PandRS(145), 2018, pp. 349-361.
Elsevier DOI 1811
Mining wastewater disaster, River plume, Turbidity, Landsat, MODIS, Coastal remote sensing BibRef

Wang, D.F.[Di-Feng], Cui, Q.Y.[Qi-Yuan], Gong, F.[Fang], Wang, L.F.[Li-Fang], He, X.Q.[Xian-Qiang], Bai, Y.[Yan],
Satellite Retrieval of Surface Water Nutrients in the Coastal Regions of the East China Sea,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901
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Huang, M.[Mutao], Tian, Y.[Yong],
An Integrated Graphic Modeling System for Three-Dimensional Hydrodynamic and Water Quality Simulation in Lakes,
IJGI(8), No. 1, 2019, pp. xx-yy.
DOI Link 1901
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Launeau, P.[Patrick], Giraud, M.[Manuel], Robin, M.[Marc], Baltzer, A.[Agnčs],
Full-Waveform LiDAR Fast Analysis of a Moderately Turbid Bay in Western France,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link 1902
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Li, N.[Na], Shi, K.[Kun], Zhang, Y.[Yunlin], Gong, Z.J.[Zhi-Jun], Peng, K.[Kai], Zhang, Y.[Yibo], Zha, Y.[Yong],
Decline in Transparency of Lake Hongze from Long-Term MODIS Observations: Possible Causes and Potential Significance,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link 1902
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Rivaro, P.[Paola], Ianni, C.[Carmela], Raimondi, L.[Lorenza], Manno, C.[Clara], Sandrini, S.[Silvia], Castagno, P.[Pasquale], Cotroneo, Y.[Yuri], Falco, P.[Pierpaolo],
Analysis of Physical and Biogeochemical Control Mechanisms on Summertime Surface Carbonate System Variability in the Western Ross Sea (Antarctica) Using In Situ and Satellite Data,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link 1902
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Vundo, A.[Augusto], Matsushita, B.[Bunkei], Jiang, D.[Dalin], Gondwe, M.[Mangaliso], Hamzah, R.[Rossi], Setiawan, F.[Fajar], Fukushima, T.[Takehiko],
An Overall Evaluation of Water Transparency in Lake Malawi from MERIS Data,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link 1902
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Cao, Y.Z.[Ying-Zhi], Wu, Y.C.[Yi-Chen], Fang, Z.X.[Zhi-Xiang], Cui, X.J.[Xiao-Jian], Liang, J.F.[Jian-Feng], Song, X.[Xiao],
Spatiotemporal Patterns and Morphological Characteristics of Ulva prolifera Distribution in the Yellow Sea, China in 2016-2018,
RS(11), No. 4, 2019, pp. xx-yy.
DOI Link 1903
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Hafeez, S.[Sidrah], Wong, M.S.[Man Sing], Ho, H.C.[Hung Chak], Nazeer, M.[Majid], Nichol, J.[Janet], Abbas, S.[Sawaid], Tang, D.[Danling], Lee, K.H.[Kwon Ho], Pun, L.[Lilian],
Comparison of Machine Learning Algorithms for Retrieval of Water Quality Indicators in Case-II Waters: A Case Study of Hong Kong,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link 1903
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Cherif, E.K.[El Khalil], Salmoun, F.[Farida], Mesas-Carrascosa, F.J.[Francisco Javier],
Determination of Bathing Water Quality Using Thermal Images Landsat 8 on the West Coast of Tangier: Preliminary Results,
RS(11), No. 8, 2019, pp. xx-yy.
DOI Link 1905
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Batur, E., Maktav, D.,
Assessment of Surface Water Quality by Using Satellite Images Fusion Based on PCA Method in the Lake Gala, Turkey,
GeoRS(57), No. 5, May 2019, pp. 2983-2989.
IEEE DOI 1905
data mining, geophysical image processing, image fusion, lakes, mean square error methods, neural nets, water quality BibRef

Jiang, D.[Dalin], Matsushita, B.[Bunkei], Setiawan, F.[Fajar], Vundo, A.[Augusto],
An improved algorithm for estimating the Secchi disk depth from remote sensing data based on the new underwater visibility theory,
PandRS(152), 2019, pp. 13-23.
Elsevier DOI 1905
Secchi disk depth, Quasi-analytical algorithm, Remote sensing, Various waters, Hybrid BibRef

Cao, Z.G.[Zhi-Gang], Ma, R.H.[Rong-Hua], Duan, H.T.[Hong-Tao], Xue, K.[Kun],
Effects of broad bandwidth on the remote sensing of inland waters: Implications for high spatial resolution satellite data applications,
PandRS(153), 2019, pp. 110-122.
Elsevier DOI 1906
High spatial resolution, Optical sensors, Bandwidth, Inland waters, Deep neural network BibRef

Wicaksono, P.[Pramaditya], Aryaguna, P.A.[Prama Ardha], Lazuardi, W.[Wahyu],
Benthic Habitat Mapping Model and Cross Validation Using Machine-Learning Classification Algorithms,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906
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Son, S.H.[Seung-Hyun], Wang, M.[Menghua],
VIIRS-Derived Water Turbidity in the Great Lakes,
RS(11), No. 12, 2019, pp. xx-yy.
DOI Link 1907
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Regional Vicarious Calibration of the SWIR-Based Atmospheric Correction Approach for MODIS-Aqua Measurements of Highly Turbid Inland Water,
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Pu, F.L.[Fang-Ling], Ding, C.J.[Chu-Jiang], Chao, Z.Y.[Ze-Yi], Yu, Y.[Yue], Xu, X.[Xin],
Water-Quality Classification of Inland Lakes Using Landsat8 Images by Convolutional Neural Networks,
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Russell, B.J.[Brandon J.], Dierssen, H.M.[Heidi M.], Hochberg, E.J.[Eric J.],
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A CIE Color Purity Algorithm to Detect Black and Odorous Water in Urban Rivers Using High-Resolution Multispectral Remote Sensing Images,
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IEEE DOI 1909
Rivers, Image color analysis, Satellites, Remote sensing, Atmospheric measurements, Water pollution, Urban areas, water color BibRef

Chen, J.[Jun], Han, Q.J.[Qi-Jin], Chen, Y.L.[Yan-Long], Li, Y.D.[Yong-Dong],
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Kratzer, S.[Susanne], Kyryliuk, D.[Dmytro], Edman, M.[Moa], Philipson, P.[Petra], Lyon, S.W.[Steve W.],
Synergy of Satellite, In Situ and Modelled Data for Addressing the Scarcity of Water Quality Information for Eutrophication Assessment and Monitoring of Swedish Coastal Waters,
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Kudela, R.M.[Raphael M.], Hooker, S.B.[Stanford B.], Houskeeper, H.F.[Henry F.], McPherson, M.[Meredith],
The Influence of Signal to Noise Ratio of Legacy Airborne and Satellite Sensors for Simulating Next-Generation Coastal and Inland Water Products,
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Xiong, J.F.[Jun-Feng], Lin, C.[Chen], Ma, R.[Ronghua], Cao, Z.G.[Zhi-Gang],
Remote Sensing Estimation of Lake Total Phosphorus Concentration Based on MODIS: A Case Study of Lake Hongze,
RS(11), No. 17, 2019, pp. xx-yy.
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Liu, X.H.[Xiao-Han], Lee, Z.P.[Zhong-Ping], Zhang, Y.L.[Yun-Lin], Lin, J.F.[Jun-Fang], Shi, K.[Kun], Zhou, Y.Q.[Yong-Qiang], Qin, B.Q.[Bo-Qiang], Sun, Z.H.[Zhao-Hua],
Remote Sensing of Secchi Depth in Highly Turbid Lake Waters and Its Application with MERIS Data,
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Uudeberg, K.[Kristi], Ansko, I.[Ilmar], Pőru, G.[Getter], Ansper, A.[Ave], Reinart, A.[Anu],
Using Optical Water Types to Monitor Changes in Optically Complex Inland and Coastal Waters,
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Wei, L.F.[Li-Fei], Huang, C.[Can], Wang, Z.X.[Zheng-Xiang], Wang, Z.[Zhou], Zhou, X.C.[Xiao-Cheng], Cao, L.Q.[Li-Qin],
Monitoring of Urban Black-Odor Water Based on Nemerow Index and Gradient Boosting Decision Tree Regression Using UAV-Borne Hyperspectral Imagery,
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Lee, S.[Shihyan], Meister, G.[Gerhard], Franz, B.[Bryan],
MODIS Aqua Reflective Solar Band Calibration for NASA's R2018 Ocean Color Products,
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Liu, D., Xu, P., Zhou, Y., Chen, W., Han, B., Zhu, X., He, Y., Mao, Z., Le, C., Chen, P., Che, H., Liu, Z., Liu, Q., Song, Q., Chen, S.,
Lidar Remote Sensing of Seawater Optical Properties: Experiment and Monte Carlo Simulation,
GeoRS(57), No. 11, November 2019, pp. 9489-9498.
IEEE DOI 1911
Laser radar, Optical attenuators, Oceans, Optical sensors, Optical scattering, Sea measurements, Attenuation, simulation BibRef

Chen, S.[Shuguo], Xue, C.[Cheng], Zhang, T.[Tinglu], Hu, L.[Lianbo], Chen, G.[Ge], Tang, J.[Junwu],
Analysis of the Optimal Wavelength for Oceanographic Lidar at the Global Scale Based on the Inherent Optical Properties of Water,
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Soomets, T.[Tuuli], Uudeberg, K.[Kristi], Jakovels, D.[Dainis], Zagars, M.[Matiss], Reinart, A.[Anu], Brauns, A.[Agris], Kutser, T.[Tiit],
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Setiawan, F.[Fajar], Matsushita, B.[Bunkei], Hamzah, R.[Rossi], Jiang, D.[Dalin], Fukushima, T.[Takehiko],
Long-Term Change of the Secchi Disk Depth in Lake Maninjau, Indonesia Shown by Landsat TM and ETM+ Data,
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Niroumand-Jadidi, M., Bovolo, F., Bruzzone, L.,
Novel Spectra-Derived Features for Empirical Retrieval of Water Quality Parameters: Demonstrations for OLI, MSI, and OLCI Sensors,
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IEEE DOI 1912
Water, Optical sensors, Feature extraction, Optical imaging, Optical variables measurement, Image color analysis, water quality BibRef

Racault, M.F.[Marie-Fanny], Abdulaziz, A.[Anas], George, G.[Grinson], Menon, N.[Nandini], Jasmin, C., Punathil, M.[Minu], McConville, K.[Kristian], Loveday, B.[Ben], Platt, T.[Trevor], Sathyendranath, S.[Shubha], Vijayan, V.[Vijitha],
Environmental Reservoirs of Vibrio cholerae: Challenges and Opportunities for Ocean-Color Remote Sensing,
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Transmission point spread function of a turbid slab,
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Modulation transfer function, Multiple scattering, Photons, Point spread function, Spatial frequency, Turbid media imaging BibRef

Sebastiá-Frasquet, M.T.[María-Teresa], Aguilar-Maldonado, J.A.[Jesús A.], Santamaría-Del-Ángel, E.[Eduardo], Estornell, J.[Javier],
Sentinel 2 Analysis of Turbidity Patterns in a Coastal Lagoon,
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DOI Link 1912
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Liu, W.H.[Wei-Hua], Wang, S.Y.[Si-Yuan], Yang, R.X.[Rui-Xia], Ma, Y.X.[Yuan-Xu], Shen, M.[Ming], You, Y.F.[Yong-Fa], Hai, K.[Kai], Baqa, M.F.[Muhammad Fahad],
Remote Sensing Retrieval of Turbidity in Alpine Rivers based on high Spatial Resolution Satellites,
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Avdan, Z.Y.[Zehra Yigit], Kaplan, G.[Gordana], Goncu, S.[Serdar], Avdan, U.[Ugur],
Monitoring the Water Quality of Small Water Bodies Using High-Resolution Remote Sensing Data,
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Zhang, Y.S.[Yi-Shan], Wu, L.[Lun], Ren, H.Z.[Hua-Zhong], Liu, Y.[Yu], Zheng, Y.Q.[Yong-Qian], Liu, Y.W.[Yao-Wen], Dong, J.J.[Jia-Ji],
Mapping Water Quality Parameters in Urban Rivers from Hyperspectral Images Using a New Self-Adapting Selection of Multiple Artificial Neural Networks,
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Zhang, Y.S.[Yi-Shan], Wu, L.[Lun], Ren, H.Z.[Hua-Zhong], Deng, L.C.[Li-Cui], Zhang, P.C.[Peng-Cheng],
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Eugenio, F.[Francisco], Marcello, J.[Javier], Martín, J.[Javier],
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Bai, S.Y.[Shu-Ying], Gao, J.X.[Ji-Xi], Sun, D.Y.[De-Yong], Tian, M.R.[Mei-Rong],
Monitoring Water Transparency in Shallow and Eutrophic Lake Waters Based on GOCI Observations,
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Dias, M.A.[Maurício Araújo], da Silva, E.A.[Erivaldo Antônio], de Azevedo, S.C.[Samara Calçado], Casaca, W.[Wallace], Statella, T.[Thiago], Negri, R.G.[Rogério Galante],
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Wu, J.[Jie], Chen, C.Q.[Chu-Qun], Nukapothula, S.[Sravanthi],
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Legleiter, C.J.[Carl J.], Manley, P.V.[Paul V.], Erwin, S.O.[Susannah O.], Bulliner, E.A.[Edward A.],
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Otto, P.[Peter], Vallejo-Rodríguez, R.[Ramiro], Keesstra, S.[Saskia], León-Becerril, E.[Elizabeth], de Anda, J.[José], Hernández-Mena, L.[Leonel], del Real-Olvera, J.[Jorge], de Jesús Díaz-Torres, J.[José],
Time Delay Evaluation on the Water-Leaving Irradiance Retrieved from Empirical Models and Satellite Imagery,
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Ground observations are not always the same schedule as satellite images. BibRef

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de Keukelaere, L.[Liesbeth], Sterckx, S.[Sindy], Adriaensen, S.[Stefan], Bhatia, N.[Nitin], Monbaliu, J.[Jaak], Toorman, E.[Erik], Cattrijsse, A.[André], Lebreton, C.[Carole], van der Zande, D.[Dimitry], Knaeps, E.[Els],
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Caballero, I.[Isabel], Stumpf, R.P.[Richard P.],
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Castagna, A.[Alexandre], Simis, S.[Stefan], Dierssen, H.[Heidi], Vanhellemont, Q.[Quinten], Sabbe, K.[Koen], Vyverman, W.[Wim],
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Li, X.J.[Xiao-Juan], Huang, M.[Mutao], Wang, R.H.[Rong-Hui],
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Uudeberg, K.[Kristi], Aavaste, A.[Age], Kőks, K.L.[Kerttu-Liis], Ansper, A.[Ave], Uusőue, M.[Mirjam], Kangro, K.[Kersti], Ansko, I.[Ilmar], Ligi, M.[Martin], Toming, K.[Kaire], Reinart, A.[Anu],
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Matysik, M.[Magdalena], Absalon, D.[Damian], Habel, M.[Michal], Maerker, M.[Michael],
Surface Water Quality Analysis Using CORINE Data: An Application to Assess Reservoirs in Poland,
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Xi, Y.X.[Yan-Xin], Ji, L.Y.[Lu-Yan], Geng, X.R.[Xiu-Rui],
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Peppa, M.[Maria], Vasilakos, C.[Christos], Kavroudakis, D.[Dimitris],
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Pereira, O.J.R.[Osvaldo J. R.], Merino, E.R.[Eder R.], Montes, C.R.[Célia R.], Barbiero, L.[Laurent], Rezende-Filho, A.T.[Ary T.], Lucas, Y.[Yves], Melfi, A.J.[Adolpho J.],
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Renosh, P.R.[Pannimpullath Remanan], Doxaran, D.[David], de Keukelaere, L.[Liesbeth], Gossn, J.I.[Juan Ignacio],
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Lu, S.J.[Shi-Jun], Deng, R.[Ruru], Liang, Y.H.[Ye-Heng], Xiong, L.H.[Long-Hai], Ai, X.J.[Xian-Jun], Qin, Y.[Yan],
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Rangzan, K.[Kazem], Kabolizadeh, M.[Mostafa], Karimi, D.[Danya],
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Castro, C.C.[Carmen Cillero], Gómez, J.A.D.[Jose Antonio Domínguez], Martín, J.D.[Jordi Delgado], Sánchez, B.A.H.[Boris Alejandro Hinojo], Arango, J.L.C.[Jose Luis Cereijo], Tuya, F.A.C.[Federico Andrés Cheda], Díaz-Varela, R.[Ramon],
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Leal-Junior, A.G.[Arnaldo G.], Frizera, A.[Anselmo], Marques, C.[Carlos],
Low-cost Fiberoptic Probe for Ammonia Early Detection in Fish Farms,
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Arias-Rodriguez, L.F.[Leonardo F.], Duan, Z.[Zheng], Sepúlveda, R.[Rodrigo], Martinez-Martinez, S.I.[Sergio I.], Disse, M.[Markus],
Monitoring Water Quality of Valle de Bravo Reservoir, Mexico, Using Entire Lifespan of MERIS Data and Machine Learning Approaches,
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Pan, F.F.[Fei-Fei], Xi, X.H.[Xiao-Huan], Wang, C.[Cheng],
A Comparative Study of Water Indices and Image Classification Algorithms for Mapping Inland Surface Water Bodies Using Landsat Imagery,
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Malthus, T.J.[Tim J.], Ohmsen, R.[Renee], van der Woerd, H.J.[Hendrik J.],
An Evaluation of Citizen Science Smartphone Apps for Inland Water Quality Assessment,
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Son, S.H.[Seung-Hyun], Wang, M.[Menghua],
Water Quality Properties Derived from VIIRS Measurements in the Great Lakes,
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Seidel, M.[Michael], Hutengs, C.[Christopher], Oertel, F.[Felix], Schwefel, D.[Daniel], Jung, A.[András], Vohland, M.[Michael],
Underwater Use of a Hyperspectral Camera to Estimate Optically Active Substances in the Water Column of Freshwater Lakes,
RS(12), No. 11, 2020, pp. xx-yy.
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Liu, Y.[Yao], Xiao, C.C.[Chen-Chao], Li, J.S.[Jun-Sheng], Zhang, F.F.[Fang-Fang], Wang, S.L.[Sheng-Lei],
Secchi Disk Depth Estimation from China's New Generation of GF-5 Hyperspectral Observations Using a Semi-Analytical Scheme,
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Kim, W.[Wonkook], Jung, S.[Sunghun], Moon, Y.[Yongseon], Mangum, S.C.[Stephen C.],
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Rosero-Montalvo, P.D.[Paul D.], López-Batista, V.F.[Vivian F.], Riascos, J.A.[Jaime A.], Peluffo-Ordóńez, D.H.[Diego H.],
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Bria, A., Cerro, G., Ferdinandi, M., Marrocco, C., Molinara, M.,
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Sensors, Machine learning, Pattern recognition, Water monitoring, Classification, Pollutant detection BibRef

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PCA, Evolutionary algorithms, Sensors, Water contamination BibRef

Chu, Q.[Qiao], Zhang, Y.C.[Yu-Chao], Ma, R.H.[Rong-Hua], Hu, M.Q.[Min-Qi], Jing, Y.Y.[Yuan-Yuan],
MODIS-Based Remote Estimation of Absorption Coefficients of an Inland Turbid Lake in China,
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Abascal-Zorrilla, N.[Noelia], Vantrepotte, V.[Vincent], Huybrechts, N.[Nicolas], Ngoc, D.D.[Dat Dinh], Anthony, E.J.[Edward J.], Gardel, A.[Antoine],
Dynamics of the Estuarine Turbidity Maximum Zone from Landsat-8 Data: The Case of the Maroni River Estuary, French Guiana,
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McEliece, R.[Ryan], Hinz, S.[Shawn], Guarini, J.M.[Jean-Marc], Coston-Guarini, J.[Jennifer],
Evaluation of Nearshore and Offshore Water Quality Assessment Using UAV Multispectral Imagery,
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DOI Link 2007
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Yang, C.Y.[Chao-Yu], Ye, H.B.[Hai-Bin], Tang, S.L.[Shi-Lin],
Seasonal Variability of Diffuse Attenuation Coefficient in the Pearl River Estuary from Long-Term Remote Sensing Imagery,
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Botha, E.J.[Elizabeth J.], Anstee, J.M.[Janet M.], Sagar, S.[Stephen], Lehmann, E.[Eric], Medeiros, T.A.G.[Thais A. G.],
Classification of Australian Waterbodies across a Wide Range of Optical Water Types,
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Pavlík, J.[Jan], Hrncírová, M.[Markéta], Stoces, M.[Michal], Masner, J.[Jan], Vanek, J.[Jirí],
Usability of IoT and Open Data Repositories for Analyzing Water Pollution. A Case Study in the Czech Republic,
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Romano, G.[Giovanni], Ricci, G.F.[Giovanni Francesco], Gentile, F.[Francesco],
Influence of Different Satellite Imagery on the Analysis of Riparian Leaf Density in a Mountain Stream,
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Ortiz-Rosa, S.[Suhey], Hernández, W.J.[William J.], Williams, S.M.[Stacey M.], Armstrong, R.A.[Roy A.],
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Maciel, D.A.[Daniel Andrade], Barbosa, C.C.F.[Claudio Clemente Faria], de Moraes Novo, E.M.L.[Evlyn Márcia Leăo], Cherukuru, N.[Nagur], Martins, V.S.[Vitor Souza], Flores Júnior, R.[Rogério], Jorge, D.S.[Daniel Schaffer], Sander de Carvalho, L.A.[Lino Augusto], Carlos, F.M.[Felipe Menino],
Mapping of Diffuse Attenuation Coefficient in Optically Complex Waters of Amazon Floodplain Lakes,
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Elsevier DOI 2011
Turbid waters, Diffuse attenuation coefficient, Sentinel-2, Complex waters, Atmospheric correction BibRef

Pi, X.H.[Xue-Hui], Feng, L.[Lian], Li, W.F.[Wei-Feng], Zhao, D.[Dan], Kuang, X.X.[Xing-Xing], Li, J.S.[Jun-Sheng],
Water clarity changes in 64 large alpine lakes on the Tibetan Plateau and the potential responses to lake expansion,
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Elsevier DOI 2011
Secchi disk depth, Inland water, Tibetan Plateau, MODIS, Alpine lake, Water clarity BibRef

Ahn, J.H.[Jae-Hyun], Park, Y.J.[Young-Je],
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DOI Link 2011
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Solakian, J.[Jennifer], Maggioni, V.[Viviana], Godrej, A.[Adil],
Investigating the Error Propagation from Satellite-Based Input Precipitation to Output Water Quality Indicators Simulated by a Hydrologic Model,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011
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Feng, J.G.[Jian-Gang], Chen, H.R.[Huang-Rong], Zhang, H.L.[Hai-Long], Li, Z.X.[Zhao-Xin], Yu, Y.[Yang], Zhang, Y.Z.[Yuan-Zhi], Bilal, M.[Muhammad], Qiu, Z.F.[Zhong-Feng],
Turbidity Estimation from GOCI Satellite Data in the Turbid Estuaries of China's Coast,
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Niroumand-Jadidi, M.[Milad], Bovolo, F.[Francesca], Bruzzone, L.[Lorenzo],
Water Quality Retrieval from PRISMA Hyperspectral Images: First Experience in a Turbid Lake and Comparison with Sentinel-2,
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DOI Link 2012
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Olmedo-Masat, O.M.[O. Magalí], Raffo, M.P.[M. Paula], Rodríguez-Pérez, D.[Daniel], Arijón, M.[Marianela], Sánchez-Carnero, N.[Noela],
How Far Can We Classify Macroalgae Remotely? An Example Using a New Spectral Library of Species from the South West Atlantic (Argentine Patagonia),
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012
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Wójcik-Dlugoborska, K.A.[Kornelia Anna], Bialik, R.J.[Robert Józef],
The Influence of Shadow Effects on the Spectral Characteristics of Glacial Meltwater,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link 2101
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Shen, M.[Ming], Wang, S.Y.[Si-Yuan], Li, Y.K.[Ying-Kui], Tang, M.F.[Mao-Feng], Ma, Y.X.[Yuan-Xu],
Pattern of Turbidity Change in the Middle Reaches of the Yarlung Zangbo River, Southern Tibetan Plateau, from 2007 to 2017,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101
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Ansper-Toomsalu, A.[Ave], Alikas, K.[Krista], Nielsen, K.[Karina], Tuvikene, L.[Lea], Kangro, K.[Kersti],
Synergy between Satellite Altimetry and Optical Water Quality Data towards Improved Estimation of Lakes Ecological Status,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
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Pyo, J.C.[Jong-Cheol], Kwon, Y.S.[Yong Sung], Ahn, J.H.[Jae-Hyun], Baek, S.S.[Sang-Soo], Kwon, Y.H.[Yong-Hwan], Cho, K.H.[Kyung Hwa],
Sensitivity Analysis and Optimization of a Radiative Transfer Numerical Model for Turbid Lake Water,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
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Sent, G.[Giulia], Biguino, B.[Beatriz], Favareto, L.[Luciane], Cruz, J.[Joana], Sá, C.[Carolina], Dogliotti, A.I.[Ana Inés], Palma, C.[Carla], Brotas, V.[Vanda], Brito, A.C.[Ana C.],
Deriving Water Quality Parameters Using Sentinel-2 Imagery: A Case Study in the Sado Estuary, Portugal,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103
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Anas, A.[Abdulaziz], Krishna, K.[Kiran], Vijayakumar, S.[Syamkumar], George, G.[Grinson], Menon, N.[Nandini], Kulk, G.[Gemma], Chekidhenkuzhiyil, J.[Jasmin], Ciambelli, A.[Angelo], Vikraman, H.K.[Hridya Kuttiyilmemuriyil], Tharakan, B.[Balu], Useph, A.J.K.[Abdul Jaleel Koovapurath], Goult, E.[Elizabeth], Vengalil, J.[Jithin], Platt, T.[Trevor], Sathyendranath, S.[Shubha],
Dynamics of Vibrio cholerae in a Typical Tropical Lake and Estuarine System: Potential of Remote Sensing for Risk Mapping,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103
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Chen, J.[Junde], Zhang, D.[Defu], Yang, S.[Shuangyuan], Nanehkaran, Y.A.[Yaser Ahangari],
Intelligent monitoring method of water quality based on image processing and RVFL-GMDH model,
IET-IPR(14), No. 17, 24 December 2020, pp. 4646-4656.
DOI Link 2104
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Gossn, J.I.[Juan Ignacio], Frouin, R.[Robert], Dogliotti, A.I.[Ana Inés],
Atmospheric Correction of Satellite Optical Imagery over the Río de la Plata Highly Turbid Waters Using a SWIR-Based Principal Component Decomposition Technique,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
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Deutsch, E.S.[Eliza S.], Cardille, J.A.[Jeffrey A.], Koll-Egyed, T.[Talia], Fortin, M.J.[Marie-Josée],
Landsat 8 Lake Water Clarity Empirical Algorithms: Large-Scale Calibration and Validation Using Government and Citizen Science Data from across Canada,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
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Rubin, H.J.[Hannah J.], Lutz, D.A.[David A.], Steele, B.G.[Bethel G.], Cottingham, K.L.[Kathryn L.], Weathers, K.C.[Kathleen C.], Ducey, M.J.[Mark J.], Palace, M.[Michael], Johnson, K.M.[Kenneth M.], Chipman, J.W.[Jonathan W.],
Remote Sensing of Lake Water Clarity: Performance and Transferability of Both Historical Algorithms and Machine Learning,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
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Gray, A.[Annie], Robertson, C.[Colin], Feick, R.[Rob],
CWDAT: An Open-Source Tool for the Visualization and Analysis of Community-Generated Water Quality Data,
IJGI(10), No. 4, 2021, pp. xx-yy.
DOI Link 2104
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Al-Shaibah, B.[Bazel], Liu, X.P.[Xing-Peng], Zhang, J.[Jiquan], Tong, Z.J.[Zhi-Jun], Zhang, M.X.[Ming-Xi], El-Zeiny, A.[Ahmed], Faichia, C.[Cheechouyang], Hussain, M.[Muhammad], Tayyab, M.[Muhammad],
Modeling Water Quality Parameters Using Landsat Multispectral Images: A Case Study of Erlong Lake, Northeast China,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Kulk, G.[Gemma], George, G.[Grinson], Abdulaziz, A.[Anas], Menon, N.[Nandini], Theenathayalan, V.[Varunan], Jayaram, C.[Chiranjivi], Brewin, R.J.W.[Robert J. W.], Sathyendranath, S.[Shubha],
Effect of Reduced Anthropogenic Activities on Water Quality in Lake Vembanad, India,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Menon, N.[Nandini], George, G.[Grinson], Ranith, R.[Rajamohananpillai], Sajin, V.[Velakandy], Murali, S.[Shreya], Abdulaziz, A.[Anas], Brewin, R.J.W.[Robert J. W.], Sathyendranath, S.[Shubha],
Citizen Science Tools Reveal Changes in Estuarine Water Quality Following Demolition of Buildings,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
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Hu, M.Q.[Min-Qi], Ma, R.[Ronghua], Cao, Z.G.[Zhi-Gang], Xiong, J.F.[Jun-Feng], Xue, K.[Kun],
Remote Estimation of Trophic State Index for Inland Waters Using Landsat-8 OLI Imagery,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Werther, M.[Mortimer], Spyrakos, E.[Evangelos], Simis, S.G.H.[Stefan G.H.], Odermatt, D.[Daniel], Stelzer, K.[Kerstin], Krawczyk, H.[Harald], Berlage, O.[Oberon], Hunter, P.[Peter], Tyler, A.[Andrew],
Meta-classification of remote sensing reflectance to estimate trophic status of inland and nearshore waters,
PandRS(176), 2021, pp. 109-126.
Elsevier DOI 2106
Trophic Status, Meta-classification, Optical Water Types, Chla, Lakes BibRef

Zhao, Y.L.[Ye-Long], Wang, S.L.[Sheng-Lei], Zhang, F.F.[Fang-Fang], Shen, Q.[Qian], Li, J.S.[Jun-Sheng],
Retrieval and Spatio-Temporal Variations Analysis of Yangtze River Water Clarity from 2017 to 2020 Based on Sentinel-2 Images,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link 2106
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He, Y.[Yang], Jin, S.G.[Shuang-Gen], Shang, W.[Wei],
Water Quality Variability and Related Factors along the Yangtze River Using Landsat-8,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link 2106
BibRef

DiNapoli, R.J.[Robert J.], Lipo, C.P.[Carl P.], de Smet, T.S.[Timothy S.], Hunt, T.L.[Terry L.],
Thermal Imaging Shows Submarine Groundwater Discharge Plumes Associated with Ancient Settlements on Rapa Nui (Easter Island, Chile),
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Li, T.[Teng], Zhu, B.Z.[Bo-Zhong], Cao, F.[Fei], Sun, H.[Hao], He, X.Q.[Xian-Qiang], Liu, M.L.[Ming-Liang], Gong, F.[Fang], Bai, Y.[Yan],
Monitoring Changes in the Transparency of the Largest Reservoir in Eastern China in the Past Decade, 2013-2020,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
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Zhu, S.J.[Shi-Jie], Mao, J.Q.[Jing-Qiao],
A Machine Learning Approach for Estimating the Trophic State of Urban Waters Based on Remote Sensing and Environmental Factors,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
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Lu, S.M.[Shi-Ming], He, M.J.[Ming-Jun], He, S.Y.[Shuang-Yan], He, S.[Shuo], Pan, Y.H.[Yun-He], Yin, W.B.[Wen-Bin], Li, P.L.[Pei-Liang],
An Improved Cloud Masking Method for GOCI Data over Turbid Coastal Waters,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107
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El Serafy, G.Y.H.[Ghada Y.H.], Schaeffer, B.A.[Blake A.], Neely, M.B.[Merrie-Beth], Spinosa, A.[Anna], Odermatt, D.[Daniel], Weathers, K.C.[Kathleen C.], Baracchini, T.[Theo], Bouffard, D.[Damien], Carvalho, L.[Laurence], Conmy, R.N.[Robyn N.], de Keukelaere, L.[Liesbeth], Hunter, P.D.[Peter D.], Jamet, C.[Cédric], Joehnk, K.D.[Klaus D.], Johnston, J.M.[John M.], Knudby, A.[Anders], Minaudo, C.[Camille], Pahlevan, N.[Nima], Reusen, I.[Ils], Rose, K.C.[Kevin C.], Schalles, J.[John], Tzortziou, M.[Maria],
Integrating Inland and Coastal Water Quality Data for Actionable Knowledge,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Rodríguez-López, L.[Lien], Duran-Llacer, I.[Iongel], González-Rodríguez, L.[Lisdelys], Cardenas, R.[Rolando], Urrutia, R.[Roberto],
Retrieving Water Turbidity in Araucanian Lakes (South-Central Chile) Based on Multispectral Landsat Imagery,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

de M. Valerio, A.[Aline], Kampel, M.[Milton], Vantrepotte, V.[Vincent], Ward, N.D.[Nicholas D.], Richey, J.E.[Jeffrey E.],
Optical Classification of Lower Amazon Waters Based on In Situ Data and Sentinel-3 Ocean and Land Color Instrument Imagery,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
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Wu, J.[Jian], Zeng, S.D.[Si-Dong], Yang, L.H.[Lin-Han], Ren, Y.X.[Yuan-Xin], Xia, J.[Jun],
Spatiotemporal Characteristics of the Water Quality and Its Multiscale Relationship with Land Use in the Yangtze River Basin,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Nam, G.[Gibeom], Shin, H.[Hyunjoo], Ha, R.[Rim], Song, H.[Hyunoh], Yoo, J.[Jaehyun], Lee, H.[Hyuk], Park, S.[Sanghyun], Kang, T.[Taegu], Kim, K.[Kyunghyun],
Quantification of Phycocyanin in Inland Waters through Remote Measurement of Ratios and Shifts in Reflection Spectral Peaks,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
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Shi, D.H.[Dong-Hui], Shi, Y.[Yishao], Wu, Q.[Qiusheng],
Multidimensional Assessment of Lake Water Ecosystem Services Using Remote Sensing,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109

See also Multidimensional Assessment of Food Provisioning Ecosystem Services Using Remote Sensing and Agricultural Statistics. BibRef

Huang, J.J.[Jing-Jing], Wang, D.F.[Di-Feng], Gong, F.[Fang], Bai, Y.[Yan], He, X.Q.[Xian-Qiang],
Changes in Nutrient Concentrations in Shenzhen Bay Detected Using Landsat Imagery between 1988 and 2020,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Cartwright, P.J.[Paula J.], Fearns, P.R.C.S.[Peter R. C. S.], Branson, P.[Paul], Cuttler, M.V.W.[Michael V. W.], O'Leary, M.[Michael], Browne, N.K.[Nicola K.], Lowe, R.J.[Ryan J.],
Identifying Metocean Drivers of Turbidity Using 18 Years of MODIS Satellite Data: Implications for Marine Ecosystems under Climate Change,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
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Azad Hossain, A.K.M., Mathias, C.[Caleb], Blanton, R.[Richard],
Remote Sensing of Turbidity in the Tennessee River Using Landsat 8 Satellite,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
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Li, M.J.[Meng-Jun], Sun, Y.H.[Yong-Hua], Li, X.J.[Xiao-Juan], Cui, M.Y.[Meng-Ying], Huang, C.[Chen],
An Improved Eutrophication Assessment Algorithm of Estuaries and Coastal Waters in Liaodong Bay,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Lu, Q.K.[Qi-Kai], Si, W.[Wei], Wei, L.F.[Li-Fei], Li, Z.Q.[Zhong-Qiang], Xia, Z.H.[Zhi-Hong], Ye, S.[Song], Xia, Y.[Yu],
Retrieval of Water Quality from UAV-Borne Hyperspectral Imagery: A Comparative Study of Machine Learning Algorithms,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Cai, X.L.[Xiao-Lan], Li, Y.M.[Yun-Mei], Bi, S.[Shun], Lei, S.H.[Shao-Hua], Xu, J.[Jie], Wang, H.J.[Huai-Jing], Dong, X.Z.[Xian-Zhang], Li, J.D.[Jun-Da], Zeng, S.[Shuai], Lyu, H.[Heng],
Urban Water Quality Assessment Based on Remote Sensing Reflectance Optical Classification,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link 2110
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Liu, H.[Hong], Yu, T.[Tao], Hu, B.L.[Bing-Liang], Hou, X.S.[Xing-Song], Zhang, Z.F.[Zhou-Feng], Liu, X.[Xiao], Liu, J.C.[Jia-Cheng], Wang, X.J.[Xue-Ji], Zhong, J.J.[Jing-Jing], Tan, Z.X.[Zheng-Xuan], Xia, S.X.[Shao-Xia], Qian, B.[Bao],
UAV-Borne Hyperspectral Imaging Remote Sensing System Based on Acousto-Optic Tunable Filter for Water Quality Monitoring,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Sabatini, A.[Anna], Zompanti, A.[Alessandro], Grasso, S.[Simone], Vollero, L.[Luca], Pennazza, G.[Giorgio], Santonico, M.[Marco],
Proof of Concept Study of an Electrochemical Sensor for Inland Water Monitoring with a Network Approach,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Gancheva, I.[Irina], Peneva, E.[Elisaveta], Slabakova, V.[Violeta],
Detecting the Surface Signature of Riverine and Effluent Plumes along the Bulgarian Black Sea Coast Using Satellite Data,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Qiao, Z.[Zhi], Sun, S.[Siyang], Jiang, Q.[Qun'ou], Xiao, L.[Ling], Wang, Y.Q.[Yun-Qi], Yan, H.[Haiming],
Retrieval of Total Phosphorus Concentration in the Surface Water of Miyun Reservoir Based on Remote Sensing Data and Machine Learning Algorithms,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Zhou, X.T.[Xiao-Teng], Liu, C.[Chun], Akbar, A.[Akram], Xue, Y.[Yun], Zhou, Y.[Yuan],
Spectral and Spatial Feature Integrated Ensemble Learning Method for Grading Urban River Network Water Quality,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Maciel, D.A.[Daniel Andrade], Barbosa, C.C.F.[Claudio Clemente Faria], de Moraes Novo, E.M.L.[Evlyn Márcia Leăo], Flores Júnior, R.[Rogério], Begliomini, F.N.[Felipe Nincao],
Water clarity in Brazilian water assessed using Sentinel-2 and machine learning methods,
PandRS(182), 2021, pp. 134-152.
Elsevier DOI 2112
Secchi disk depth, Atmospheric correction, Water quality, Google earth engine, Remote sensing, Water transparency BibRef

Dallosch, M.A.[Michael A.], Creed, I.F.[Irena F.],
Optimization of Landsat Chl-a Retrieval Algorithms in Freshwater Lakes through Classification of Optical Water Types,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Liu, J.H.[Jin-Hua], Ding, J.[Jianli], Ge, X.Y.[Xiang-Yu], Wang, J.Z.[Jing-Zhe],
Evaluation of Total Nitrogen in Water via Airborne Hyperspectral Data: Potential of Fractional Order Discretization Algorithm and Discrete Wavelet Transform Analysis,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Bian, Y.C.[Ying-Chun], Zhao, Y.[Ying], Lyu, H.[Heng], Guo, F.[Fei], Li, Y.M.[Yun-Mei], Xu, J.F.[Jia-Feng], Liu, H.Q.[Huai-Qing], Ni, S.[Shang],
Nineteen Years of Trophic State Variation in Large Lakes of the Yangtze River Delta Region Derived from MODIS Images,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Filippi, M.[Margaux], Hanlon, R.[Regina], Rypina, I.I.[Irina I.], Hodges, B.A.[Benjamin A.], Peacock, T.[Thomas], Schmale, D.G.[David G.],
Tracking a Surrogate Hazardous Agent (Rhodamine Dye) in a Coastal Ocean Environment Using In Situ Measurements and Concentration Estimates Derived from Drone Images,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Xu, Y.Z.[Yu-Zhuang], He, X.Q.[Xian-Qiang], Bai, Y.[Yan], Wang, D.F.[Di-Feng], Zhu, Q.K.[Qian-Kun], Ding, X.S.[Xiao-Song],
Evaluation of Remote-Sensing Reflectance Products from Multiple Ocean Color Missions in Highly Turbid Water (Hangzhou Bay),
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Ma, Y.[Yue], Rose, F.[Francis], Wong, L.[Leslie], Vien, B.S.[Benjamin Steven], Kuen, T.[Thomas], Rajic, N.[Nik], Kodikara, J.[Jayantha], Chiu, W.K.[Wing Kong],
Thermographic Monitoring of Scum Accumulation beneath Floating Covers,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Xu, M.[Min], Liu, H.X.[Hong-Xing], Beck, R.A.[Richard Allan], Lekki, J.[John], Yang, B.[Bo], Liu, Y.[Yang], Shu, S.[Song], Wang, S.[Shujie], Tokars, R.[Roger], Anderson, R.[Robert], Reif, M.[Molly], Emery, E.[Erich],
Implementation Strategy and Spatiotemporal Extensibility of Multipredictor Ensemble Model for Water Quality Parameter Retrieval With Multispectral Remote Sensing Data,
GeoRS(60), 2022, pp. 1-16.
IEEE DOI 2112
Lakes, Water quality, Data models, Remote sensing, Spatiotemporal phenomena, Optical sensors, Image color analysis, water quality BibRef

Guo, H.W.[Hong-Wei], Tian, S.[Shang], Huang, J.H.J.[Jin-Hui Jeanne], Zhu, X.T.[Xiao-Tong], Wang, B.[Bo], Zhang, Z.J.[Zi-Jie],
Performance of deep learning in mapping water quality of Lake Simcoe with long-term Landsat archive,
PandRS(183), 2022, pp. 451-469.
Elsevier DOI 2201
Deep learning, Remote sensing, Water quality, Chlorophyll-, Total phosphorous, Total nitrogen BibRef

Gerlach, M.E.[Mary E.], Rains, K.C.[Kai C.], Guerrón-Orejuela, E.J.[Edgar J.], Kleindl, W.J.[William J.], Downs, J.[Joni], Landry, S.M.[Shawn M.], Rains, M.C.[Mark C.],
Using Remote Sensing and Machine Learning to Locate Groundwater Discharge to Salmon-Bearing Streams,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Wang, L.J.[Ling-Jun], Bie, W.J.[Wan-Juan], Li, H.C.[Hao-Cheng], Liao, T.H.[Tang-Hong], Ding, X.X.[Xing-Xing], Wu, G.F.[Guo-Feng], Fei, T.[Teng],
Small Water Body Detection and Water Quality Variations with Changing Human Activity Intensity in Wuhan,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Zhou, X.Y.[Xue-Ying], Huang, Z.Q.[Zhao-Qiang], Wan, Y.C.[You-Chuan], Ni, B.[Bin], Zhang, Y.L.[Ya-Long], Li, S.W.[Si-Wei], Wang, M.W.[Ming-Wei], Wu, T.[Tong],
A New Method for Continuous Monitoring of Black and Odorous Water Body Using Evaluation Parameters: A Case Study in Baoding,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Zhu, B.Z.[Bo-Zhong], Bai, Y.[Yan], Zhang, Z.[Zhao], He, X.Q.[Xian-Qiang], Wang, Z.H.[Zhi-Hong], Zhang, S.[Shugang], Dai, Q.[Qian],
Satellite Remote Sensing of Water Quality Variation in a Semi-Enclosed Bay (Yueqing Bay) under Strong Anthropogenic Impact,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Markogianni, V.[Vassiliki], Kalivas, D.[Dionissios], Petropoulos, G.P.[George P.], Dimitriou, E.[Elias],
Modelling of Greek Lakes Water Quality Using Earth Observation in the Framework of the Water Framework Directive (WFD),
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Bonetti, J.[Jarbas], del Bianco, F.[Fabrizio], Schippa, L.[Leonardo], Polonia, A.[Alina], Stanghellini, G.[Giuseppe], Cenni, N.[Nicola], Draghetti, S.[Stefano], Marabini, F.[Francesco], Gasperini, L.[Luca],
Anatomy of Anthropically Controlled Natural Lagoons through Geophysical, Geological, and Remote Sensing Observations: The Valli Di Comacchio (NE Italy) Case Study,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Liang, M.C.[Min-Chih], Tfwala, S.S.[Samkele S.], Chen, S.C.[Su-Chin],
The Evaluation of Color Spaces for Large Woody Debris Detection in Rivers Using XGBoost Algorithm,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Mezni, H.[Haithem], Driss, M.[Maha], Boulila, W.[Wadii], Ben Atitallah, S.[Safa], Sellami, M.[Mokhtar], Alharbi, N.[Nouf],
SmartWater: A Service-Oriented and Sensor Cloud-Based Framework for Smart Monitoring of Water Environments,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Soriano-González, J.[Jesús], Urrego, E.P.[Esther Patricia], Sňria-Perpinyŕ, X.[Xavier], Angelats, E.[Eduard], Alcaraz, C.[Carles], Delegido, J.[Jesús], Ruíz-Verdú, A.[Antonio], Tenjo, C.[Carolina], Vicente, E.[Eduardo], Moreno, J.[José],
Towards the Combination of C2RCC Processors for Improving Water Quality Retrieval in Inland and Coastal Areas,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
BibRef

Gao, M.[Min], Li, J.S.[Jun-Sheng], Wang, S.L.[Sheng-Lei], Zhang, F.F.[Fang-Fang], Yan, K.[Kai], Yin, Z.Y.[Zi-Yao], Xie, Y.[Ya], Shen, W.[Wei],
Smartphone-Camera-Based Water Reflectance Measurement and Typical Water Quality Parameter Inversion,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Soomets, T.[Tuuli], Toming, K.[Kaire], Jefimova, J.[Jekaterina], Jaanus, A.[Andres], Pőllumäe, A.[Arno], Kutser, T.[Tiit],
Deriving Nutrient Concentrations from Sentinel-3 OLCI Data in North-Eastern Baltic Sea,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204
BibRef

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QDA-System: A Cloud-Based System for Monitoring Water Quality in Brazilian Hydroelectric Reservoirs from Space,
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Du, Y.[Yunxia], Song, K.[Kaishan], Liu, G.[Ge],
Monitoring Optical Variability in Complex Inland Waters Using Satellite Remote Sensing Data,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205
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Yang, Z.Z.[Zhi-Zhou], Zou, L.[Lei], Xia, J.[Jun], Qiao, Y.F.[Yun-Feng], Cai, D.[Diwen],
Inner Dynamic Detection and Prediction of Water Quality Based on CEEMDAN and GA-SVM Models,
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Yang, H.B.[Hai-Bo], Kong, J.L.[Jia-Lin], Hu, H.H.[Hui-Hui], Du, Y.[Yao], Gao, M.[Meiyan], Chen, F.[Fei],
A Review of Remote Sensing for Water Quality Retrieval: Progress and Challenges,
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Survey, Water Quality. BibRef

Zheng, Y.X.[Yue-Xin], Wang, Q.Y.[Qian-Yang], Zhang, X.[Xuan], Yu, J.S.[Jing-Shan], Li, C.[Chong], Chen, L.W.[Li-Wen], Liu, Y.[Yuan],
Nitrogen and Phosphorus Retention Risk Assessment in a Drinking Water Source Area under Anthropogenic Activities,
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Rodrigues, G.[Gonçalo], Potes, M.[Miguel], Penha, A.M.[Alexandra Marchă], Costa, M.J.[Maria Joăo], Morais, M.M.[Maria Manuela],
The Use of Sentinel-3/OLCI for Monitoring the Water Quality and Optical Water Types in the Largest Portuguese Reservoir,
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Petus, C.[Caroline], Waterhouse, J.[Jane], Tracey, D.[Dieter], Wolanski, E.[Eric], Brodie, J.[Jon],
Using Optical Water-Type Classification in Data-Poor Water Quality Assessment: A Case Study in the Torres Strait,
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Fronkova, L.[Lenka], Greenwood, N.[Naomi], Martinez, R.[Roi], Graham, J.A.[Jennifer A.], Harrod, R.[Richard], Graves, C.A.[Carolyn A.], Devlin, M.J.[Michelle J.], Petus, C.[Caroline],
Can Forel-Ule Index Act as a Proxy of Water Quality in Temperate Waters? Application of Plume Mapping in Liverpool Bay, UK,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link 2206
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Qing, S.[Song], Cui, T.W.[Ting-Wei], Tang, J.[Junwu], Song, Q.J.[Qing-Jun], Liu, R.J.[Rong-Jie], Bao, Y.[Yuhai],
An optical water classification and quality control model (OC_QC model) for spectral diffuse attenuation coefficient,
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Elsevier DOI 2206
Spectral diffuse attenuation coefficient, Optical water classification, Quality control, Clustering BibRef

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Zhai, M.J.[Ming-Jian], Tao, Z.[Zui], Zhou, X.[Xiang], Lv, T.T.[Ting-Ting], Wang, J.[Jin], Li, R.[Ruoxi],
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Hafeez, S.[Sidrah], Wong, M.S.[Man Sing], Abbas, S.[Sawaid], Asim, M.[Muhammad],
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Xiao, Y.[Yi], Guo, Y.H.[Ya-Hui], Yin, G.D.[Guo-Dong], Zhang, X.[Xuan], Shi, Y.[Yu], Hao, F.H.[Fang-Hua], Fu, Y.S.[Yong-Shuo],
UAV Multispectral Image-Based Urban River Water Quality Monitoring Using Stacked Ensemble Machine Learning Algorithms: A Case Study of the Zhanghe River, China,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208
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Coladello, L.F.[Leandro Fernandes], de Lourdes Bueno Trindade Galo, M.[Maria], Shimabukuro, M.H.[Milton Hirokazu], Ivánová, I.[Ivana], Awange, J.[Joseph],
Assessing Climate Influence on Spatiotemporal Dynamics of Macrophytes in Eutrophicated Reservoirs by Remotely Sensed Time Series,
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DOI Link 2208
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Chang, M.X.[Mao-Xiang], Li, P.[Peng], Sun, Y.[Yue], Wang, H.J.[Hou-Jie], Li, Z.H.[Zhen-Hong],
Mapping Dynamic Turbidity Maximum Zone of the Yellow River Estuary from 38 Years of Landsat Imagery,
RS(14), No. 15, 2022, pp. xx-yy.
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Zhang, D.H.[Dong-Hui], Zhang, L.[Lifu], Sun, X.J.[Xue-Jian], Gao, Y.[Yu], Lan, Z.Y.[Zi-Yue], Wang, Y.N.[Yi-Ning], Zhai, H.R.[Hao-Ran], Li, J.R.[Jing-Ru], Wang, W.[Wei], Chen, M.[Maming], Li, X.S.[Xu-Sheng], Hou, L.[Liang], Li, H.L.[Hong-Liang],
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Chen, M.M.[Miao-Miao], Xiao, F.[Fei], Wang, Z.[Zhou], Feng, Q.[Qi], Ban, X.[Xuan], Zhou, Y.D.[Ya-Dong], Hu, Z.Z.[Zheng-Zheng],
An Improved QAA-Based Method for Monitoring Water Clarity of Honghu Lake Using Landsat TM, ETM+ and OLI Data,
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DOI Link 2208
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Varotsos, C.A.[Costas A.], Mkrtchyan, F.A.[Ferdenant A.], Soldatov, V.Y.[Vladimir Y.],
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Li, H.Y.[Han-Yu], Zhang, G.Z.[Guang-Zong], Zhu, Y.Y.[Yu-Yan], Kaufmann, H.[Hermann], Xu, G.C.[Guo-Chang],
Inversion and Driving Force Analysis of Nutrient Concentrations in the Ecosystem of the Shenzhen-Hong Kong Bay Area,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
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Isgró, M.A.[Melisa A.], Basallote, M.D.[M. Dolores], Caballero, I.[Isabel], Barbero, L.[Luis],
Comparison of UAS and Sentinel-2 Multispectral Imagery for Water Quality Monitoring: A Case Study for Acid Mine Drainage Affected Areas (SW Spain),
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link 2208
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Zhang, H.W.[Han-Wen], Xue, B.L.[Bao-Lin], Wang, G.Q.[Guo-Qiang], Zhang, X.J.[Xiao-Jing], Zhang, Q.Z.[Qing-Zhu],
Deep Learning-Based Water Quality Retrieval in an Impounded Lake Using Landsat 8 Imagery: An Application in Dongping Lake,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Niroumand-Jadidi, M.[Milad], Bovolo, F.[Francesca], Bresciani, M.[Mariano], Gege, P.[Peter], Giardino, C.[Claudia],
Water Quality Retrieval from Landsat-9 (OLI-2) Imagery and Comparison to Sentinel-2,
RS(14), No. 18, 2022, pp. xx-yy.
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Yang, Z.[Zhe], Gong, C.[Cailan], Ji, T.[Tiemei], Hu, Y.[Yong], Li, L.[Lan],
Water Quality Retrieval from ZY1-02D Hyperspectral Imagery in Urban Water Bodies and Comparison with Sentinel-2,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
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Mucheye, T.[Tadesse], Haro, S.[Sara], Papaspyrou, S.[Sokratis], Caballero, I.[Isabel],
Water Quality and Water Hyacinth Monitoring with the Sentinel-2A/B Satellites in Lake Tana (Ethiopia),
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Sňria-Perpinyŕ, X.[Xavier], Delegido, J.[Jesús], Urrego, E.P.[Esther Patricia], Ruíz-Verdú, A.[Antonio], Soria, J.M.[Juan Miguel], Vicente, E.[Eduardo], Moreno, J.[José],
Assessment of Sentinel-2-MSI Atmospheric Correction Processors and In Situ Spectrometry Waters Quality Algorithms,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
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Liu, Y.Y.[Yu-Yang], Liu, J.C.[Jia-Cheng], Zhao, Y.[Yubo], Wang, X.J.[Xue-Ji], Song, S.[Shuyao], Liu, H.[Hong], Yu, T.[Tao],
Retrieving Water Quality Parameters from Noisy-Label Data Based on Instance Selection,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
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Tao, H.[Hui], Song, K.[Kaishan], Liu, G.[Ge], Wang, Q.[Qiang], Wen, Z.D.[Zhi-Dan], Hou, J.B.[Jun-Bin], Shang, Y.X.[Ying-Xin], Li, S.[Sijia],
Analysis of Spatio-Temporal Dynamics of Chinese Inland Water Clarity at Multiple Spatial Scales between 1984 and 2018,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211
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Wang, J.W.[Jun-Wei], Wang, Y.C.[Yong-Chao], Lee, Z.P.[Zhong-Ping], Wang, D.[Daosheng], Chen, S.[Shuguo], Lai, W.[Wendian],
A revision of NASA SeaDAS atmospheric correction algorithm over turbid waters with artificial Neural Networks estimated remote-sensing reflectance in the near-infrared,
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Elsevier DOI 2212
Ocean color remote sensing, Atmospheric correction, Artificial Neural Network, Near-infrared, Coastal turbid waters BibRef

Xu, H.Q.[Han-Qiu], Duan, W.F.[Wei-Fang], Deng, W.H.[Wen-Hui], Lin, M.[Mengjing],
RSEI or MRSEI? Comment on Jia et al. Evaluation of Eco-Environmental Quality in Qaidam Basin Based on the Ecological Index (MRSEI) and GEE. Remote Sens. 2021, 13, 4543,
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Total Phosphorus and Nitrogen Dynamics and Influencing Factors in Dongting Lake Using Landsat Data,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
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Zhao, Y.[Yubo], Yu, T.[Tao], Hu, B.L.[Bing-Liang], Zhang, Z.[Zhoufeng], Liu, Y.Y.[Yu-Yang], Liu, X.[Xiao], Liu, H.[Hong], Liu, J.C.[Jia-Cheng], Wang, X.J.[Xue-Ji], Song, S.[Shuyao],
Retrieval of Water Quality Parameters Based on Near-Surface Remote Sensing and Machine Learning Algorithm,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
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Li, N.[Ning], Ning, Z.Y.[Zi-Yu], Chen, M.[Miao], Wu, D.M.[Dong-Ming], Hao, C.Z.[Cheng-Zhi], Zhang, D.H.[Dong-Hui], Bai, R.[Rui], Liu, H.[Huiran], Chen, X.[Xin], Li, W.[Wei], Zhang, W.[Wen], Chen, Y.C.[Yi-Cheng], Li, Q.F.[Qin-Fen], Zhang, L.[Lifu],
Satellite and Machine Learning Monitoring of Optically Inactive Water Quality Variability in a Tropical River,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
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Pereira-Sandoval, M.[Marcela], Ruescas, A.B.[Ana B.], García-Jimenez, J.[Jorge], Blix, K.[Katalin], Delegido, J.[Jesús], Moreno, J.[José],
Supervised Classifications of Optical Water Types in Spanish Inland Waters,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Goyens, C.[Clémence], Lavigne, H.[Héloďse], Dille, A.[Antoine], Vervaeren, H.[Han],
Using Hyperspectral Remote Sensing to Monitor Water Quality in Drinking Water Reservoirs,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Wang, Q.[Qiang], Song, K.[Kaishan], Xiao, X.M.[Xiang-Ming], Jacinthe, P.A.[Pierre-Andre], Wen, Z.D.[Zhi-Dan], Zhao, F.[Fangrui], Tao, H.[Hui], Li, S.[Sijia], Shang, Y.X.[Ying-Xin], Wang, Y.[Yu], Liu, G.[Ge],
Mapping water clarity in North American lakes and reservoirs using Landsat images on the GEE platform with the RGRB model,
PandRS(194), 2022, pp. 39-57.
Elsevier DOI 2212
Water clarity, Landsat imagery, Google Earth Engine, Top-of-atmosphere reflectance BibRef

Wei, Z.[Zeyang], Wei, L.F.[Li-Fei], Yang, H.[Hong], Wang, Z.X.[Zheng-Xiang], Xiao, Z.W.[Zhi-Wei], Li, Z.Q.[Zhong-Qiang], Yang, Y.[Yujing], Xu, G.B.[Guo-Bin],
Water Quality Grade Identification for Lakes in Middle Reaches of Yangtze River Using Landsat-8 Data with Deep Neural Networks (DNN) Model,
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Liu, X.P.[Xing-Peng], Al-Shaibah, B.[Bazel], Zhao, C.L.[Chun-Li], Tong, Z.J.[Zhi-Jun], Bian, H.F.[Hong-Feng], Zhang, F.[Feng], Zhang, J.[Jiquan], Pei, X.J.[Xiang-Jun],
Estimation of the Key Water Quality Parameters in the Surface Water, Middle of Northeast China, Based on Gaussian Process Regression,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link 2212
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Román, A.[Alejandro], Tovar-Sánchez, A.[Antonio], Gauci, A.[Adam], Deidun, A.[Alan], Caballero, I.[Isabel], Colica, E.[Emanuele], d'Amico, S.[Sebastiano], Navarro, G.[Gabriel],
Water-Quality Monitoring with a UAV-Mounted Multispectral Camera in Coastal Waters,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Shao, Z.[Zhanchao], Bryan, K.R.[Karin R.], Lehmann, M.K.[Moritz K.], Pilditch, C.A.[Conrad A.],
Extracting Remotely Sensed Water Quality Parameters from Shallow Intertidal Estuaries,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
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Tu, M.C.[Min-Cheng], Huang, Y.C.[Yu-Chieh],
Impact of Land Reclamation on Coastal Water in a Semi-Enclosed Bay,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link 2301
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Pose, S.[Sebastian], Reitmann, S.[Stefan], Licht, G.J.[Gero Jörn], Grab, T.[Thomas], Fieback, T.[Tobias],
AI-Prepared Autonomous Freshwater Monitoring and Sea Ground Detection by an Autonomous Surface Vehicle,
RS(15), No. 3, 2023, pp. xx-yy.
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Martín-Crespo, T.[Tomás], Gomez-Ortiz, D.[David], Pryimak, V.[Vladyslava], Martín-Velázquez, S.[Silvia], Rodríguez-Santalla, I.[Inmaculada], Ropero-Szymańska, N.[Nikoletta], de Ignacio-San José, C.[Cristina],
Quantification of Pollutants in Mining Ponds Using a Combination of LiDAR and Geochemical Methods: Mining District of Hiendelaencina, Guadalajara (Spain),
RS(15), No. 5, 2023, pp. xx-yy.
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Assegide, E.[Endaweke], Shiferaw, H.[Hailu], Tibebe, D.[Degefie], Peppa, M.V.[Maria V.], Walsh, C.L.[Claire L.], Alamirew, T.[Tena], Zeleke, G.[Gete],
Spatiotemporal Dynamics of Water Quality Indicators in Koka Reservoir, Ethiopia,
RS(15), No. 4, 2023, pp. xx-yy.
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Arias-Rodriguez, L.F.[Leonardo F.], Tüzün, U.F.[Ulas Firat], Duan, Z.[Zheng], Huang, J.[Jingshui], Tuo, Y.[Ye], Disse, M.[Markus],
Global Water Quality of Inland Waters with Harmonized Landsat-8 and Sentinel-2 Using Cloud-Computed Machine Learning,
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Deng, L.[Li], Li, W.[Wanshu], Liu, X.J.[Xiao-Jie], Wang, Y.Z.[Ya-Zhu], Wang, L.Q.[Ling-Qing],
Landscape Patterns and Topographic Features Affect Seasonal River Water Quality at Catchment and Buffer Scales,
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DOI Link 2303
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Shiling, Z.[Zhang],
Research on On-line Detection Method and Device Development of HF and Micro Water Content with Optical Image Processing,
ICIVC22(741-748)
IEEE DOI 2301
Water, Optical fibers, Absorption, Adsorption, Hafnium, Optical saturation, Optical variables measurement, Detection limit BibRef

Rocha, I.[Inęs], Azevedo, F.[Fábio], Carvalho, P.H.[Pedro H.], Peixoto, P.S.[Patrícia S.], Segundo, M.A.[Marcela A.], Oliveira, H.P.[Hélder P.],
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Springer DOI 2205
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Ahi, S., Eymen, A.,
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Biraghi, C.A., Lotfian, M., Carrion, D., Brovelli, M.A.,
AI in Support to Water Quality Monitoring,
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Gerosa, C., Bresciani, M., Luciani, G., Biraghi, C.A., Carrion, D., Rogora, M., Brovelli, M.A.,
Zonation of Subalpine Lakes Based on Remotely Sensed Water Quality Parameters,
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Fattah, G., Ghrissi, F., Mabrouki, J., Al-Jadabi, N.,
Modeling and Assessment of the Impact of Land Use in the Western Rif Region, Morocco, on Water Quality,
SmartCityApp21(225-230).
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Toro Herrera, J.F., Carrion, D., Brovelli, M.A.,
A Collaborative Platform for Water Quality Monitoring: Simile Webgis,
ISPRS21(B4-2021: 201-207).
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Richter, K., Mader, D., Westfeld, P., Maas, H.G.,
Water Turbidity Estimation From Lidar Bathymetry Data By Full-waveform Analysis - Comparison of Two Approaches,
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Baek, J.Y.[Ji Yeon], Krishna de Guzman, M.[Maria], Park, H.M.[Ho-Min], Park, S.[Sanghyeon], Shin, B.[Boyeon], Velickovic, T.C.[Tanja Cirkovic], van Messem, A.[Arnout], de Neve, W.[Wesley],
Developing a Segmentation Model for Microscopic Images of Microplastics Isolated from Clams,
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Ech-Chafay, H., Najy, M., Talbi, F.Z., El Ghazouany, A., Lachhab, M., Belghyti, D.,
Study of the Purification Performance of the Natural Lagunating Technique of the Purification Station of the City of Outat El Haj - Morocco,
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Liu, C., Zhou, X., Zhou, Y., Akbar, A.,
Multi-temporal Monitoring of Urban River Water Quality Using UAV-borne Multi-spectral Remote Sensing,
ISPRS20(B3:1469-1475).
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Carrion, D., Pessina, E., Biraghi, C.A., Bratic, G.,
Crowdsourcing Water Quality with the Simile App,
ISPRS20(B4:245-251).
DOI Link 2012
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Šádek, P., Struhár, J.,
The Evaluation of Water Pollution With The Help of Remote Sensing Tools,
Gi4DM19(403-408).
DOI Link 1912
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Yagmur, N., Musaoglu, N., Taskin, G.,
Detection of Shallow Water Area With Machine Learning Algorithms,
ISSDQ19(1269-1273).
DOI Link 1912
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Jalbuena, R.L., Blanco, A.C., Manuel, A., Santa Ana, R.R., Santos, J.A.,
Bio Optical Modelling of Laguna Lake Using Bomber Tool and Wasi-derived Inverted Parameters,
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Carvalho, P.H.[Pedro H.], Bessa, S.[Sílvia], Silva, A.R.M.[Ana Rosa M.], Peixoto, P.S.[Patrícia S.], Segundo, M.A.[Marcela A.], Oliveira, H.P.[Hélder P.],
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Wu, X., Shivakumara, P., Zhu, L., Zhang, H., Shi, J., Lu, T., Pal, U., Blumenstein, M.,
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ICPR18(1707-1712)
IEEE DOI 1812
Water pollution, Feature extraction, Image color analysis, Support vector machines, Image classification, Surface cleaning, SVM classifier and Water image detection BibRef

Dong, J.Y.[Jun-Yu], Dong, X.H.[Xing-Hui],
Oceanic Scene Recognition Using Graph-of-Words (GoW),
CEFR-LCV17(1122-1130)
IEEE DOI 1802
Feature extraction, Flickr, Histograms, Image recognition, Layout, Roads, Sea measurements BibRef

Teja, K.T.[K. Tarun], Rajan, K.S.,
Understanding The Behaviour Of Contamination Spread In Nagarjuna Sagar Reservoir Using Temporal Landsat Data,
ISPRS16(B8: 343-348).
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Chengfang, H., Xiao, X., Dingtao, S., Bo, C., Xiongfei, W.,
Study Of Water Pollution Early Warning Framework Based On Internet Of Things,
ISPRS16(B8: 335-338).
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Pásler, M., Komárková, J.,
Utilization of Landsat Data for Water Quality Observation in Small Inland Water Bodies,
ISPRS16(B8: 373-377).
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Codevilla, F.[Felipe], Gaya, J.D.O.[Joel De O.], Filho, N.D.[Nelson Duarte], Botelho, S.S.C.C.[Silvia S. C. Costa],
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Tormos, T., Harmel, T., Danis, P.A., Chami, M.,
Exploiting satelitte image time series for monitoring ecological quality parameters of french reservoirs,
MultiTemp15(1-4)
IEEE DOI 1511
ecology BibRef

Liew, S.C., Chang, C.W., Kwoh, L.K.,
Sensitivity Analysis In The Retrieval Of Turbid Coastal Water Bathymetry Using Worldview-2 Satellite Data,
ISPRS12(XXXIX-B7:13-16).
DOI Link 1209
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Liu, Y., Zhang, W., Yan, C.,
The Huaihe Basin Water Resource And Water Quality Management Platform Implemented With A Spatio-temporal Data Model,
ISPRS12(XXXIX-B6:135-140).
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Campbell, G., Phinn, S.R.,
Measuring The Particulate Backscattering Of Inland Waters: A Comparison Of Techniques,
AnnalsPRS(I-7), No. 2012, pp. 7-12.
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Akbar, T.[Tahir], Hassan, Q.[Quazi], Achari, G.[Gopal],
A remote sensing based framework for predicting water quality of different source waters,
CGC10(117).
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Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Suspended Particulates, Suspended Matter, Water Quality .

Last update:Mar 27, 2023 at 09:32:08