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1305
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1411
hydrological techniques
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1601
Biological system modeling
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1604
Correlation
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1609
Quasi-analytical algorithm
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Spatial Distribution of Diffuse Attenuation of Photosynthetic Active
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1703
Absorption
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1704
lakes
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Jorge, D.S.F.[Daniel S.F.],
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Water Optics and Water Colour Remote Sensing,
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Huang, C.C.[Chang-Chun],
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Semi-Analytical Retrieval of the Diffuse Attenuation Coefficient in
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Shrestha, A.[Anil],
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Analysis of Groundwater Nitrate Contamination in the Central Valley:
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Shrestha, A.[Anil],
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1711
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Tracking of a Fluorescent Dye in a Freshwater Lake with an Unmanned
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1802
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1804
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Retrieval of Water Constituents from Hyperspectral In-Situ
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1804
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Kratzer, S.[Susanne],
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Inherent Optical Properties of the Baltic Sea in Comparison to Other
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1804
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Hue-Angle Product for Low to Medium Spatial Resolution Optical
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1804
Color for water quality analysis.
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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
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1809
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Lead Detection in Polar Oceans: A Comparison of Different
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Betancur-Turizo, S.P.[Stella Patricia],
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Evaluation of Semi-Analytical Algorithms to Retrieve Particulate and
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Decline in Transparency of Lake Hongze from Long-Term MODIS
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DOI Link
1902
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Rivaro, P.[Paola],
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Falco, P.[Pierpaolo],
Analysis of Physical and Biogeochemical Control Mechanisms on
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Sea (Antarctica) Using In Situ and Satellite Data,
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1902
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Vundo, A.[Augusto],
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Setiawan, F.[Fajar],
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An Overall Evaluation of Water Transparency in Lake Malawi from MERIS
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RS(11), No. 3, 2019, pp. xx-yy.
DOI Link
1902
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Cao, Y.Z.[Ying-Zhi],
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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
BibRef
Hafeez, S.[Sidrah],
Wong, M.S.[Man Sing],
Ho, H.C.[Hung Chak],
Nazeer, M.[Majid],
Nichol, J.[Janet],
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Lee, K.H.[Kwon Ho],
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Comparison of Machine Learning Algorithms for Retrieval of Water
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1903
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Batur, E.,
Maktav, D.,
Assessment of Surface Water Quality by Using Satellite Images Fusion
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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],
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An improved algorithm for estimating the Secchi disk depth from
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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],
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Effects of broad bandwidth on the remote sensing of inland waters:
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PandRS(153), 2019, pp. 110-122.
Elsevier DOI
1906
High spatial resolution, Optical sensors, Bandwidth,
Inland waters, Deep neural network
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Wicaksono, P.[Pramaditya],
Aryaguna, P.A.[Prama Ardha],
Lazuardi, W.[Wahyu],
Benthic Habitat Mapping Model and Cross Validation Using
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RS(11), No. 11, 2019, pp. xx-yy.
DOI Link
1906
BibRef
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
BibRef
Pu, F.L.[Fang-Ling],
Ding, C.J.[Chu-Jiang],
Chao, Z.Y.[Ze-Yi],
Yu, Y.[Yue],
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Water-Quality Classification of Inland Lakes Using Landsat8 Images by
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RS(11), No. 14, 2019, pp. xx-yy.
DOI Link
1908
BibRef
Russell, B.J.[Brandon J.],
Dierssen, H.M.[Heidi M.],
Hochberg, E.J.[Eric J.],
Water Column Optical Properties of Pacific Coral Reefs Across
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RS(11), No. 15, 2019, pp. xx-yy.
DOI Link
1908
BibRef
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
BibRef
Shen, Q.[Qian],
Yao, Y.[Yue],
Li, J.S.[Jun-Sheng],
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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
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RS(11), No. 17, 2019, pp. xx-yy.
DOI Link
1909
BibRef
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
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RS(11), No. 20, 2019, pp. xx-yy.
DOI Link
1910
BibRef
Lee, S.[Shihyan],
Meister, G.[Gerhard],
Franz, B.[Bryan],
MODIS Aqua Reflective Solar Band Calibration for NASA's R2018 Ocean
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RS(11), No. 19, 2019, pp. xx-yy.
DOI Link
1910
BibRef
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.G.[Shu-Guo],
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
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DOI Link
1911
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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],
Comparison of Lake Optical Water Types Derived from Sentinel-2 and
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RS(11), No. 23, 2019, pp. xx-yy.
DOI Link
1912
BibRef
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
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RS(11), No. 23, 2019, pp. xx-yy.
DOI Link
1912
BibRef
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,
GeoRS(57), No. 12, December 2019, pp. 10285-10300.
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,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link
1912
BibRef
Avdan, Z.Y.[Zehra Yigit],
Kaplan, G.[Gordana],
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Monitoring the Water Quality of Small Water Bodies Using
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1912
BibRef
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
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2001
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Elsevier DOI
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Water classification, Spectral quality, Ultraviolet,
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IEEE DOI
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Elsevier DOI
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Explainable machine learning, Water quality, Remote sensing,
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Water, Optical fibers, Absorption, Adsorption, Hafnium,
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Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Water Turbidity, Turbid Water Areas .