23.5.7 Water Quality, Turbidity, Water Areas

Chapter Contents (Back)
Classification. Water Quality. Turbidity.
See also Water Clarity.
See also Coastal Water Quality, Water Clarity.
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

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

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

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

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
BibRef

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
BibRef

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
BibRef

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
BibRef

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
BibRef

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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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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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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Liu, R.[Rong], Wen, J.[Jun], Wang, X.[Xin], Wang, Z.L.[Zuo-Liang], Li, Z.C.[Zhen-Chao], Xie, Y.[Yan], Zhu, L.[Li], Li, D.P.[Dong-Peng],
Derivation of Vegetation Optical Depth and Water Content in the Source Region of the Yellow River using the FY-3B Microwave Data,
RS(11), No. 13, 2019, pp. xx-yy.
DOI Link 1907
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Li, J.S.[Jun-Sheng], Yin, Z.Y.[Zi-Yao], Lu, Z.Y.[Zhao-Yi], Ye, Y.T.[Yun-Tao], Zhang, F.F.[Fang-Fang], Shen, Q.[Qian], Zhang, B.[Bing],
Regional Vicarious Calibration of the SWIR-Based Atmospheric Correction Approach for MODIS-Aqua Measurements of Highly Turbid Inland Water,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link 1908
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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,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link 1908
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Russell, B.J.[Brandon J.], Dierssen, H.M.[Heidi M.], Hochberg, E.J.[Eric J.],
Water Column Optical Properties of Pacific Coral Reefs Across Geomorphic Zones and in Comparison to Offshore Waters,
RS(11), No. 15, 2019, pp. xx-yy.
DOI Link 1908
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Chen, P.[Peng], Pan, D.[Delu],
Ocean Optical Profiling in South China Sea Using Airborne LiDAR,
RS(11), No. 15, 2019, pp. xx-yy.
DOI Link 1908
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Shen, Q.[Qian], Yao, Y.[Yue], Li, J.S.[Jun-Sheng], Zhang, F.F.[Fang-Fang], Wang, S.L.[Sheng-Lei], Wu, Y.H.[Yan-Hong], Ye, H.P.[Hu-Ping], Zhang, B.[Bing],
A CIE Color Purity Algorithm to Detect Black and Odorous Water in Urban Rivers Using High-Resolution Multispectral Remote Sensing Images,
GeoRS(57), No. 9, September 2019, pp. 6577-6590.
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],
A Secchi Depth Algorithm Considering the Residual Error in Satellite Remote Sensing Reflectance Data,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link 1909
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Xiong, J.F.[Jun-Feng], Lin, C.[Chen], Ma, R.H.[Rong-Hua], 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.
DOI Link 1909
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Laser radar, Optical attenuators, Oceans, Optical sensors, Optical scattering, Sea measurements, Attenuation, simulation BibRef

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Seidel, M.[Michael], Hutengs, C.[Christopher], Oertel, F.[Felix], Schwefel, D.[Daniel], Jung, A.[András], Vohland, M.[Michael],
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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],
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Kim, W.[Wonkook], Jung, S.[Sunghun], Moon, Y.[Yongseon], Mangum, S.C.[Stephen C.],
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PCA, Evolutionary algorithms, Sensors, Water contamination BibRef

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Yang, C.Y.[Chao-Yu], Ye, H.B.[Hai-Bin], Tang, S.L.[Shi-Lin],
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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.],
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Pavlík, J.[Jan], Hrncírová, M.[Markéta], Stoces, M.[Michal], Masner, J.[Jan], Vanek, J.[Jirí],
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Romano, G.[Giovanni], Ricci, G.F.[Giovanni Francesco], Gentile, F.[Francesco],
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Wójcik-Dlugoborska, K.A.[Kornelia Anna], Bialik, R.J.[Robert Józef],
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Citizen Science Tools Reveal Changes in Estuarine Water Quality Following Demolition of Buildings,
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DOI Link 2105
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Hu, M.Q.[Min-Qi], Ma, R.H.[Rong-Hua], 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
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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],
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Elsevier DOI 2106
Trophic Status, Meta-classification, Optical Water Types, Chla, Lakes BibRef

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
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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.
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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,
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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,
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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,
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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.
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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
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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.S.[Yi-Shao], Wu, Q.S.[Qiu-Sheng],
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
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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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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
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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,
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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.
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Sabatini, A.[Anna], Zompanti, A.[Alessandro], Grasso, S.[Simone], Vollero, L.[Luca], Pennazza, G.[Giorgio], Santonico, M.[Marco],
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DOI Link 2110
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Qiao, Z.[Zhi], Sun, S.Y.[Si-Yang], Jiang, Q.[Qun'ou], Xiao, L.[Ling], Wang, Y.Q.[Yun-Qi], Yan, H.M.[Hai-Ming],
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
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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
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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
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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
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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
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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),
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DOI Link 2112
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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,
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DOI Link 2112
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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],
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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,
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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
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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
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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
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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
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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
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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
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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,
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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,
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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
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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
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Curtarelli, M.[Marcelo], Neto, E.[Edmar], de Siqueira, F.[Fanny], Yopan, F.[Felipe], Soares, G.[Gilmar], Pauli, G.[Gilnei], de Souza, J.[Joăo], Silva, L.[Luana], Sagaz, M.[Marcio], Demay, M.[Miguel], Bortolas, N.[Natália], Yoshimura, R.[Ricardo], Guimarăes, V.[Vitor],
QDA-System: A Cloud-Based System for Monitoring Water Quality in Brazilian Hydroelectric Reservoirs from Space,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
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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.
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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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DOI Link 2205
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,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
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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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DOI Link 2205
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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,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
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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],
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PandRS(189), 2022, pp. 255-271.
Elsevier DOI 2206
Spectral diffuse attenuation coefficient, Optical water classification, Quality control, Clustering BibRef

Zhai, M.J.[Ming-Jian], Tao, Z.[Zui], Zhou, X.[Xiang], Lv, T.T.[Ting-Ting], Wang, J.[Jin], Li, R.[Ruoxi],
Water Multi-Parameter Sampling Design Method Based on Adaptive Sample Points Fusion in Weighted Space,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link 2206
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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
BibRef

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,
RS(14), No. 14, 2022, pp. xx-yy.
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.
DOI Link 2208
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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],
A New Method for Calculating Water Quality Parameters by Integrating Space-Ground Hyperspectral Data and Spectral-In Situ Assay Data,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
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Varotsos, C.A.[Costas A.], Mkrtchyan, F.A.[Ferdenant A.], Soldatov, V.Y.[Vladimir Y.],
Remote Monitoring of Atmospheric and Hydrophysical Characteristics of the Water Surface Based on Microwave Radiometric Measurements,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
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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
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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.
DOI Link 2209
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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
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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.Y.[Shu-Yao], 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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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,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212

See also Evaluation of Eco-Environmental Quality in Qaidam Basin Based on the Ecological Index (MRSEI) and GEE. BibRef

Zhang, Y.Y.[Yuan-Yuan], Jin, S.G.[Shuang-Gen], Wang, N.[Ning], Zhao, J.R.[Jia-Rui], Guo, H.W.[Hong-Wei], Pellikka, P.[Petri],
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.F.[Zhou-Feng], Liu, Y.Y.[Yu-Yang], Liu, X.[Xiao], Liu, H.[Hong], Liu, J.C.[Jia-Cheng], Wang, X.J.[Xue-Ji], Song, S.Y.[Shu-Yao],
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.
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Using Hyperspectral Remote Sensing to Monitor Water Quality in Drinking Water Reservoirs,
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Wei, Z.Y.[Ze-Yang], 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.J.[Yu-Jing], 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,
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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,
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Pose, S.[Sebastian], Reitmann, S.[Stefan], Licht, G.J.[Gero Jörn], Grab, T.[Thomas], Fieback, T.[Tobias],
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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),
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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,
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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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Zhang, X.Q.[Xian-Qing], Li, C.[Cai], Zhou, W.[Wen], Zheng, Y.N.[Yuan-Ning], Cao, W.X.[Wen-Xi], Liu, C.[Cong], Xu, Z.T.[Zhan-Tang], Yang, Y.Z.[Yue-Zhong], Yang, Z.[Zeming], Chen, F.[Fei],
Study of the Profile Distribution of the Diffuse Attenuation Coefficient and Secchi Disk Depth in the Northwestern South China Sea,
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Nagayama, K.[Kazutaka], Tonooka, H.[Hideyuki],
Prediction of the Area of High-Turbidity Water in the Yatsushiro Sea, Japan, Using Machine Learning with Satellite, Meteorological, and Oceanographic Data,
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Cardall, A.C.[Anna Catherine], Hales, R.C.[Riley Chad], Tanner, K.B.[Kaylee Brooke], Williams, G.P.[Gustavious Paul], Markert, K.N.[Kel N.],
LASSO (L1) Regularization for Development of Sparse Remote-Sensing Models with Applications in Optically Complex Waters Using GEE Tools,
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Adjovu, G.E.[Godson Ebenezer], Stephen, H.[Haroon], James, D.[David], Ahmad, S.[Sajjad],
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Wang, D.[Dian], Xiang, X.Y.[Xiang-Yu], Ma, R.H.[Rong-Hua], Guo, Y.Q.[Yong-Qin], Zhu, W.Y.[Wang-Yuan], Wu, Z.H.[Zhi-Hao],
A Novel Atmospheric Correction for Turbid Water Remote Sensing,
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Ren, J.H.[Jiang-Hua], Cui, J.Y.[Jian-Yong], Dong, W.[Wen], Xiao, Y.F.[Yan-Fang], Xu, M.M.[Ming-Ming], Liu, S.W.[Shan-Wei], Wan, J.H.[Jian-Hua], Li, Z.W.[Zhong-Wei], Zhang, J.[Jie],
Remote Sensing Inversion of Typical Offshore Water Quality Parameter Concentration Based on Improved SVR Algorithm,
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Zhao, J.R.[Jia-Rui], Jin, S.G.[Shuang-Gen], Zhang, Y.Y.[Yuan-Yuan],
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RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306
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Li, S.[Sijia], Kutser, T.[Tiit], Song, K.[Kaishan], Liu, G.[Ge], Li, Y.[Yong],
Lake Turbidity Mapping Using an OWTs-bp Based Framework and Sentinel-2 Imagery,
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Men, J.L.[Ji-Lin], Chen, X.[Xi], Hou, X.J.[Xue-Jiao], Tian, J.Y.[Jing-Yi], Song, Q.J.[Qing-Jun], Tian, L.Q.[Li-Qiao],
OC_3S: An optical classification and spectral scoring system for global waters using UV-visible remote sensing reflectance,
PandRS(200), 2023, pp. 153-172.
Elsevier DOI 2306
Water classification, Spectral quality, Ultraviolet, Hyperspectral dataset, Water optical properties, Remote sensing reflectance BibRef

Wang, Z.Y.[Zheng-Yi], Mao, Z.H.[Zhi-Hua], Zhang, L.W.[Long-Wei], Zhang, X.L.[Xian-Liang], Yuan, D.P.[Da-Peng], Li, Y.Z.[You-Zhi], Wu, Z.Q.[Zhong-Qiang], Huang, H.Q.[Hai-Qing], Zhu, Q.[Qiankun],
Observations of the Impacts of Hong Kong International Airport on Water Quality from 1986 to 2022 Using Landsat Satellite,
RS(15), No. 12, 2023, pp. xx-yy.
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Logan, R.D.[Riley D.], Torrey, M.A.[Madison A.], Feijó-Lima, R.[Rafael], Colman, B.P.[Benjamin P.], Valett, H.M.[H. Maurice], Shaw, J.A.[Joseph A.],
UAV-Based Hyperspectral Imaging for River Algae Pigment Estimation,
RS(15), No. 12, 2023, pp. xx-yy.
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Mouta, N.[Nuno], Silva, R.[Renato], Pinto, E.M.[Eva M.], Vaz, A.S.[Ana Sofia], Alonso, J.M.[Joaquim M.], Gonçalves, J.F.[Joăo F.], Honrado, J.[Joăo], Vicente, J.R.[Joana R.],
Sentinel-2 Time Series and Classifier Fusion to Map an Aquatic Invasive Plant Species along a River: The Case of Water-Hyacinth,
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Lin, C.[Chuan], Han, G.J.[Guang-Jie], Zhang, T.W.[Tong-Wei], Shah, S.B.H.[Syed Bilal Hussain], Peng, Y.[Yan],
Smart Underwater Pollution Detection Based on Graph-Based Multi-Agent Reinforcement Learning Towards AUV-Based Network ITS,
ITS(24), No. 7, July 2023, pp. 7494-7505.
IEEE DOI 2307
Pollution, Task analysis, Optimization, Systems architecture, Heuristic algorithms, Computer architecture, Routing, intelligent transportation systems BibRef

Faria, B.[Bruna], Mendes, R.[Renato], Lopes, C.L.[Carina Lurdes], Picado, A.[Ana], Sousa, M.[Magda], Dias, J.M.[Joăo Miguel],
Insights for Sea Outfall Turbid Plume Monitoring with High-Spatial-Resolution Satellite Imagery Application in Portugal,
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DOI Link 2307
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Zhang, Y.[Yu], Zhang, L.[Lifu], Huang, C.P.[Chang-Ping], Cen, Y.[Yi], Tong, Q.X.[Qing-Xi],
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Sedighkia, M.[Mahdi], Datta, B.[Bithin], Saeedipour, P.[Parisa], Abdoli, A.[Asghar],
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Li, B.[Bo], Peng, Z.[Zhan], Wang, S.L.[Shi-Lei], Guo, L.Y.[Lin-Yan],
Identification of Ballast Fouling Status and Mechanized Cleaning Efficiency Using FDTD Method,
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DOI Link 2307
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Huang, Z.K.[Zheng-Kai], Wu, X.[Xin], Wang, H.[Haihong], Hwang, C.[Cheinway], He, X.X.[Xiao-Xing],
Monitoring Inland Water Quantity Variations: A Comprehensive Analysis of Multi-Source Satellite Observation Technology Applications,
RS(15), No. 16, 2023, pp. 3945.
DOI Link 2309
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Yang, Z.[Zhe], Gong, C.[Cailan], Lu, Z.H.[Zhi-Hua], Wu, E.[Enuo], Huai, H.Y.[Hong-Yan], Hu, Y.[Yong], Li, L.[Lan], Dong, L.[Lei],
Combined Retrievals of Turbidity from Sentinel-2A/B and Landsat-8/9 in the Taihu Lake through Machine Learning,
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Efimova, T.[Tatiana], Churilova, T.[Tatiana], Skorokhod, E.[Elena], Suslin, V.[Vyacheslav], Buchelnikov, A.S.[Anatoly S.], Glukhovets, D.[Dmitry], Khrapko, A.[Aleksandr], Moiseeva, N.[Natalia],
Light Absorption by Optically Active Components in the Arctic Region (August 2020) and the Possibility of Application to Satellite Products for Water Quality Assessment,
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DOI Link 2310
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Zeng, F.[Fanxuan], Song, C.Q.[Chun-Qiao], Cao, Z.G.[Zhi-Gang], Xue, K.[Kun], Lu, S.[Shanlong], Chen, T.[Tan], Liu, K.[Kai],
Monitoring inland water via Sentinel satellite constellation: A review and perspective,
PandRS(204), 2023, pp. 340-361.
Elsevier DOI 2310
Remote sensing, Earth observation, Water quantity, Water quality, SDG 6, Satellite constellation BibRef

Dong, L.[Lei], Gong, C.[Cailan], Huai, H.Y.[Hong-Yan], Wu, E.[Enuo], Lu, Z.H.[Zhi-Hua], Hu, Y.[Yong], Li, L.[Lan], Yang, Z.[Zhe],
Retrieval of Water Quality Parameters in Dianshan Lake Based on Sentinel-2 MSI Imagery and Machine Learning: Algorithm Evaluation and Spatiotemporal Change Research,
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Jin, H.[Haohai], Fang, S.Y.[Shi-Yu], Chen, C.[Chao],
Mapping of the Spatial Scope and Water Quality of Surface Water Based on the Google Earth Engine Cloud Platform and Landsat Time Series,
RS(15), No. 20, 2023, pp. 4986.
DOI Link 2310
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Schulien, J.A.[Jennifer A.], Code, T.[Tessa], DeGasperi, C.[Curtis], Beauchamp, D.A.[David A.], Ellis, A.T.[Arielle Tonus], Litt, A.H.[Arni H.],
Annual and Interannual Variability in the Diffuse Attenuation Coefficient and Turbidity in Urbanized Washington Lake from 2013 to 2022 Assessed Using Landsat-8/9,
RS(15), No. 20, 2023, pp. 5055.
DOI Link 2310
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Praet, N.[Nore], Collart, T.[Tim], Ollevier, A.[Anouk], Roche, M.[Marc], Degrendele, K.[Koen], de Rijcke, M.[Maarten], Urban, P.[Peter], Vandorpe, T.[Thomas],
The Potential of Multibeam Sonars as 3D Turbidity and SPM Monitoring Tool in the North Sea,
RS(15), No. 20, 2023, pp. 4918.
DOI Link 2310
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Kanjin, K.[Kingsley], Adade, R.[Richard], Quaicoe, J.[Julia], Lan, M.[Minxuan],
Assessing Potable Water Access and Its Implications for Households' Livelihoods: The Case of Sibi in the Nkwanta North District, Ghana,
IJGI(12), No. 9, 2023, pp. 365.
DOI Link 2310
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Zhai, Y.H.[Ying-Hui], Zhong, P.[Pu], Duan, H.T.[Hong-Tao], Zhang, D.[Dan], Chen, X.[Xin], Guo, X.[Xingjian],
Modeling of Suspended Particulate Matter Concentration in an Extremely Turbid River Based on Multispectral Remote Sensing from an Unmanned Aerial Vehicle (UAV),
RS(15), No. 22, 2023, pp. 5398.
DOI Link 2311
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Villota-González, F.H.[Freddy Hernán], Sulbarán-Rangel, B.[Belkis], Zurita-Martínez, F.[Florentina], Gurubel-Tun, K.J.[Kelly Joel], Zúńiga-Grajeda, V.[Virgilio],
Assessment of Machine Learning Models for Remote Sensing of Water Quality in Lakes Cajititlán and Zapotlán, Jalisco—Mexico,
RS(15), No. 23, 2023, pp. 5505.
DOI Link 2312
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Lee, J.S.[Jong-Seok], Baek, J.Y.[Ji-Yeon], Shin, J.[Jisun], Kim, J.S.[Jae-Seong], Jo, Y.H.[Young-Heon],
Suspended Sediment Concentration Estimation along Turbid Water Outflow Using a Multispectral Camera on an Unmanned Aerial Vehicle,
RS(15), No. 23, 2023, pp. 5540.
DOI Link 2312
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Liu, J.X.[Jia-Xin], Qiu, Z.[Zhongfeng], Feng, J.J.[Jia-Jun], Wong, K.P.[Ka Po], Tsou, J.Y.[Jin Yeu], Wang, Y.[Yu], Zhang, Y.Z.[Yuan-Zhi],
Monitoring Total Suspended Solids and Chlorophyll-a Concentrations in Turbid Waters: A Case Study of the Pearl River Estuary and Coast Using Machine Learning,
RS(15), No. 23, 2023, pp. 5559.
DOI Link 2312
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Xia, X.[Xietian], Lu, H.[Hui], Xu, Z.[Zenghui], Li, X.[Xiang], Tian, Y.[Yu],
Research on the Characteristic Spectral Band Determination for Water Quality Parameters Retrieval Based on Satellite Hyperspectral Data,
RS(15), No. 23, 2023, pp. 5578.
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Marinho, G.C.[Giovanna Carreira], Júnior, W.E.M.[Wilson Estécio Marcílio], Dias, M.A.[Mauricio Araujo], Eler, D.M.[Danilo Medeiros], Artero, A.O.[Almir Olivette], Casaca, W.[Wallace], Negri, R.G.[Rogério Galante],
Associating Anomaly Detection Strategy Based on Kittler's Taxonomy with Image Editing to Extend the Mapping of Polluted Water Bodies,
RS(15), No. 24, 2023, pp. 5760.
DOI Link 2401
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Jakovljevic, G.[Gordana], Álvarez-Taboada, F.[Flor], Govedarica, M.[Miro],
Long-Term Monitoring of Inland Water Quality Parameters Using Landsat Time-Series and Back-Propagated ANN: Assessment and Usability in a Real-Case Scenario,
RS(16), No. 1, 2024, pp. xx-yy.
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Eljaiek-Urzola, M.[Monica], Sander-de Carvalho, L.A.[Lino Augusto], Betancur-Turizo, S.P.[Stella Patricia], Quińones-Bolańos, E.[Edgar], Castrillón-Ortiz, C.[Carlos],
Spatial Patterns of Turbidity in Cartagena Bay, Colombia, Using Sentinel-2 Imagery,
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Yépez, S.[Santiago], Velásquez, G.[Germán], Torres, D.[Daniel], Saavedra-Passache, R.[Rodrigo], Pincheira, M.[Martin], Cid, H.[Hayleen], Rodríguez-López, L.[Lien], Contreras, A.[Angela], Frappart, F.[Frédéric], Cristóbal, J.[Jordi], Pons, X.[Xavier], Flores, N.[Neftali], Bourrel, L.[Luc],
Spatiotemporal Variations in Biophysical Water Quality Parameters: An Integrated In Situ and Remote Sensing Analysis of an Urban Lake in Chile,
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Wang, Z.G.[Zhen-Guo], Xue, C.J.[Cun-Jin], Ping, B.[Bo],
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Gao, L.F.[Ling-Fang], Shangguan, Y.L.[Yu-Lin], Sun, Z.[Zhong], Shen, Q.[Qiaohui], Shi, Z.[Zhou],
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Pak, H.Y.[Hui Ying], Kieu, H.T.[Hieu Trung], Lin, W.S.[Wei-Si], Khoo, E.[Eugene], Law, A.W.K.[Adrian Wing-Keung],
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Toming, K.[Kaire], Liu, H.[Hui], Soomets, T.[Tuuli], Uuemaa, E.[Evelyn], Nőges, T.[Tiina], Kutser, T.[Tiit],
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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.],
An Edge-Based Computer Vision Approach for Determination of Sulfonamides in Water,
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Ahi, S., Eymen, A.,
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SmartCityApp21(15-20).
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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,
ISPRS21(B3-2021: 551-558).
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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,
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Toro Herrera, J.F., Carrion, D., Brovelli, M.A.,
A Collaborative Platform for Water Quality Monitoring: Simile Webgis,
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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.,
Fourier Transform based Features for Clean and Polluted Water Image Classification,
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,
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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

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.,
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Akbar, T.[Tahir], Hassan, Q.[Quazi], Achari, G.[Gopal],
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Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Coastal Water Quality, Water Clarity .


Last update:Feb 29, 2024 at 09:13:14