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1907
Lakes, Adaptation models, Hyperspectral imaging,
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A New Algorithm to Estimate Chlorophyll-A Concentrations in Turbid
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1911
Rivers, Sea measurements, Oceans, Satellites, Image color analysis,
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2001
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IEEE DOI
2001
Sea measurements, Optical variables measurement, Oceans,
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Elsevier DOI
2005
Chlorophyll concentration (Chla), Retrieval algorithm,
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2004
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Daily Variation of Chlorophyll-A Concentration Increased by Typhoon
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Effects of Spring-Neap Tidal Cycle on Spatial and Temporal
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2006
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Park, J.[Jinku],
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Corredor-Acosta, A.[Andrea],
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2007
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Markogianni, V.[Vassiliki],
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2007
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2008
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Spatial Variability and Detection Levels for Chlorophyll-a Estimates
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2009
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Chen, Y.T.[Ya-Tong],
Liu, Q.[Qun],
Chen, W.B.[Wei-Biao],
Tang, J.W.[Jun-Wu],
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2009
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2010
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2011
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Fischer, J.[Jürgen],
A New Retrieval of Sun-Induced Chlorophyll Fluorescence in Water from
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Sammartino, M.[Michela],
Nardelli, B.B.[Bruno Buongiorno],
Marullo, S.[Salvatore],
Santoleri, R.[Rosalia],
An Artificial Neural Network to Infer the Mediterranean 3D
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Tenjo, C.[Carolina],
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2101
BibRef
Yang, M.M.[Meng-Meng],
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Tian, H.Z.[Hong-Zhen],
Liu, Q.P.[Qin-Ping],
Analysis of the Monthly and Spring-Neap Tidal Variability of
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DOI Link
2103
BibRef
Maier, P.M.[Philipp M.],
Keller, S.[Sina],
Hinz, S.[Stefan],
Deep Learning with WASI Simulation Data for Estimating Chlorophyll a
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RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Su, H.[Hua],
Lu, X.M.[Xue-Mei],
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Lu, W.F.[Wen-Fang],
Wu, W.T.[Wen-Ting],
Estimating Coastal Chlorophyll-A Concentration from Time-Series OLCI
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RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Tavares, M.H.[Matheus Henrique],
Lins, R.C.[Regina Camara],
Harmel, T.[Tristan],
Fragoso, Jr., C.R.[Carlos Ruberto],
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Motta-Marques, D.[David],
Atmospheric and sunglint correction for retrieving chlorophyll-a in a
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PandRS(174), 2021, pp. 215-236.
Elsevier DOI
2103
Chlorophyll- (chl-), Sentinel-2 MSI, Turbid productive waters,
Algorithm validation, Optical water type, Water quality
BibRef
Vásquez, S.I.[Sebastián I.],
de la Torre, M.B.[María Belén],
Saldías, G.S.[Gonzalo S.],
Montecinos, A.[Aldo],
Meridional Changes in Satellite Chlorophyll and Fluorescence in
Optically-Complex Coastal Waters of Northern Patagonia,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link
2103
BibRef
El-Alem, A.[Anas],
Chokmani, K.[Karem],
Venkatesan, A.[Aarthi],
Rachid, L.[Lhissou],
Agili, H.[Hachem],
Dedieu, J.P.[Jean-Pierre],
How Accurate Is an Unmanned Aerial Vehicle Data-Based Model Applied
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RS(13), No. 6, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Liu, S.H.[Shu-Hong],
Tang, D.[Danling],
Yan, H.[Hong],
Ning, G.[Guicai],
Liu, C.C.[Cheng-Cheng],
Yang, Y.J.[Yuan-Jian],
Potential Associations between Low-Level Jets and Intraseasonal and
Semi-Diurnal Variations in Coastal Chlorophyll:
A over the Beibuwan Gulf, South China Sea,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Rousseaux, C.S.[Cecile S.],
Gregg, W.W.[Watson W.],
Ott, L.[Lesley],
Assessing the Skills of a Seasonal Forecast of Chlorophyll in the
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RS(13), No. 6, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Hu, C.M.[Chuan-Min],
Feng, L.[Lian],
Guan, Q.[Qi],
A Machine Learning Approach to Estimate Surface Chlorophyll a
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GeoRS(59), No. 6, June 2021, pp. 4590-4607.
IEEE DOI
2106
Oceans, Machine learning algorithms, Water, Machine learning,
Image color analysis, Sea measurements, Sensors, Algorithm,
Visible Infrared Imaging Radiometer Suite (VIIRS)
BibRef
Mamun, M.[Md],
Ferdous, J.[Jannatul],
An, K.G.[Kwang-Guk],
Empirical Estimation of Nutrient, Organic Matter and Algal
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RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Niroumand-Jadidi, M.[Milad],
Bovolo, F.[Francesca],
Bruzzone, L.[Lorenzo],
Gege, P.[Peter],
Inter-Comparison of Methods for Chlorophyll-a Retrieval: Sentinel-2
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RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Hussein, K.A.[Khalid A.],
Abdouli, K.A.[Khameis Al],
Ghebreyesus, D.T.[Dawit T.],
Petchprayoon, P.[Pakorn],
Hosani, N.A.[Naeema Al],
Sharif, H.O.[Hatim O.],
Spatiotemporal Variability of Chlorophyll-a and Sea Surface
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RS(13), No. 13, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Perrone, M.[Michela],
Scalici, M.[Massimiliano],
Conti, L.[Luisa],
Moravec, D.[David],
Kropácek, J.[Jan],
Sighicelli, M.[Maria],
Lecce, F.[Francesca],
Malavasi, M.[Marco],
Water Mixing Conditions Influence Sentinel-2 Monitoring of
Chlorophyll Content in Monomictic Lakes,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Wang, Y.[Yueqi],
Gao, Z.Q.[Zhi-Qiang],
Ning, J.[Jicai],
An Adaptive Piecewise Harmonic Analysis Method for Reconstructing
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RS(13), No. 14, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Xu, T.F.[Teng-Fei],
Wei, Z.[Zexun],
Li, S.[Shujiang],
Susanto, R.D.[Raden Dwi],
Radiarta, N.[Nyoman],
Yuan, C.[Chao],
Setiawan, A.[Agus],
Kuswardani, A.[Anastasia],
Agustiadi, T.[Teguh],
Trenggono, M.[Mukti],
Satellite-Observed Multi-Scale Variability of Sea Surface
Chlorophyll-a Concentration along the South Coast of the Sumatra-Java
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RS(13), No. 14, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Zhang, R.F.[Run-Fei],
Zheng, Z.B.[Zhu-Bin],
Liu, G.[Ge],
Du, C.G.[Cheng-Gong],
Du, C.[Chao],
Lei, S.H.[Shao-Hua],
Xu, Y.F.[Yi-Fan],
Xu, J.[Jie],
Mu, M.[Meng],
Bi, S.[Shun],
Li, J.Z.[Jian-Zhong],
Simulation and Assessment of the Capabilities of Orbita Hyperspectral
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RS(13), No. 14, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Li, J.[Junyi],
Zheng, H.Y.[Hui-Yuan],
Xie, L.L.[Ling-Ling],
Zheng, Q.[Quanan],
Ling, Z.[Zheng],
Li, M.[Min],
Response of Total Suspended Sediment and Chlorophyll-a Concentration
to Late Autumn Typhoon Events in the Northwestern South China Sea,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link
2108
BibRef
Stramska, M.[Malgorzata],
Konik, M.[Marta],
Aniskiewicz, P.[Paulina],
Jakacki, J.[Jaromir],
Darecki, M.[Miroslaw],
Comparisons of Satellite and Modeled Surface Temperature and
Chlorophyll Concentrations in the Baltic Sea with In Situ Data,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link
2108
BibRef
Ye, H.B.[Hai-Bin],
Tang, S.L.[Shi-Lin],
Yang, C.Y.[Chao-Yu],
Deep Learning for Chlorophyll-a Concentration Retrieval:
A Case Study for the Pearl River Estuary,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Ye, X.M.[Xiao-Min],
Liu, J.Q.[Jian-Qiang],
Lin, M.[Mingsen],
Ding, J.[Jing],
Zou, B.[Bin],
Song, Q.J.[Qing-Jun],
Global Ocean Chlorophyll-a Concentrations Derived From COCTS Onboard
the HY-1C Satellite and Their Preliminary Evaluation,
GeoRS(59), No. 12, December 2021, pp. 9914-9926.
IEEE DOI
2112
Satellites, Image color analysis, Ocean temperature, Sea surface,
Scattering, Atmospheric measurements, Aerosols,
ocean color
BibRef
Wang, Z.[Zhi],
Chen, G.[Ge],
Han, Y.[Yong],
Ma, C.Y.[Chun-Yong],
Lv, M.[Ming],
Southwestern Atlantic Ocean Fronts Detected from Satellite-Derived
SST and Chlorophyll,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Wirasatriya, A.[Anindya],
Susanto, R.D.[Raden Dwi],
Setiawan, J.D.[Joga Dharma],
Ramdani, F.[Fatwa],
Iskandar, I.[Iskhaq],
Jalil, A.R.[Abd. Rasyid],
Puryajati, A.D.[Ardiansyah Desmont],
Kunarso, K.[Kunarso],
Maslukah, L.[Lilik],
High Chlorophyll-a Areas along the Western Coast of South
Sulawesi-Indonesia during the Rainy Season Revealed by Satellite Data,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Bi, S.[Shun],
Li, Y.M.[Yun-Mei],
Liu, G.[Ge],
Song, K.[Kaishan],
Xu, J.[Jie],
Dong, X.Z.[Xian-Zhang],
Cai, X.L.[Xiao-Lan],
Mu, M.[Meng],
Miao, S.[Song],
Lyu, H.[Heng],
Assessment of Algorithms for Estimating Chlorophyll-a Concentration
in Inland Waters: A Round-Robin Scoring Method Based on the Optically
Fuzzy Clustering,
GeoRS(60), 2022, pp. 1-17.
IEEE DOI
2112
Clustering algorithms, Measurement, Adaptive optics,
Optical sensors, Biomedical optical imaging, remote sensing
BibRef
Shi, J.R.[Jia-Rui],
Shen, Q.[Qian],
Yao, Y.[Yue],
Li, J.S.[Jun-Sheng],
Chen, F.[Fu],
Wang, R.[Ru],
Xu, W.T.[Wen-Ting],
Gao, Z.Y.[Zuo-Yan],
Wang, L.B.[Li-Bing],
Zhou, Y.T.[Yu-Ting],
Estimation of Chlorophyll-a Concentrations in Small Water Bodies:
Comparison of Fused Gaofen-6 and Sentinel-2 Sensors,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link
2201
BibRef
Chen, J.Q.[Jian-Qiang],
Gong, X.[Xun],
Guo, X.Y.[Xin-Yu],
Xing, X.G.[Xiao-Gang],
Lu, K.Y.[Ke-Yu],
Gao, H.W.[Hui-Wang],
Gong, X.[Xiang],
Improved Perceptron of Subsurface Chlorophyll Maxima by a Deep Neural
Network: A Case Study with BGC-Argo Float Data in the Northwestern
Pacific Ocean,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Guo, J.T.[Jun-Ting],
Lu, J.F.[Jing-Fang],
Zhang, Y.M.[Yu-Ming],
Zhou, C.[Chen],
Zhang, S.F.[Shu-Fang],
Wang, D.S.[Dao-Sheng],
Lv, X.Q.[Xian-Qing],
Variability of Chlorophyll-a and Secchi Disk Depth (1997-2019)
in the Bohai Sea Based on Monthly Cloud-Free Satellite Data
Reconstructions,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Wakamatsu, L.[Lael],
Britten, G.L.[Gregory L.],
Styles, E.J.[Elliot J.],
Fischer, A.M.[Andrew M.],
Chlorophyll-a and Sea Surface Temperature Changes in Relation to
Paralytic Shellfish Toxin Production off the East Coast of Tasmania,
Australia,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Zhuo, W.[Wei],
Wu, N.[Nan],
Shi, R.[Runhe],
Wang, Z.[Zuo],
UAV Mapping of the Chlorophyll Content in a Tidal Flat Wetland Using
a Combination of Spectral and Frequency Indices,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Kayastha, P.[Priya],
Dzialowski, A.R.[Andrew R.],
Stoodley, S.H.[Scott H.],
Wagner, K.L.[Kevin L.],
Mansaray, A.S.[Abubakarr S.],
Effect of Time Window on Satellite and Ground-Based Data for
Estimating Chlorophyll-a in Reservoirs,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Yang, C.Y.[Chao-Yu],
Ye, H.B.[Hai-Bin],
Enhanced Chlorophyll-a in the Coastal Waters near the Eastern
Guangdong during the Downwelling Favorable Wind Period,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link
2203
BibRef
Yang, H.B.[Hai-Bo],
Du, Y.[Yao],
Zhao, H.[Hongling],
Chen, F.[Fei],
Water Quality Chl-a Inversion Based on Spatio-Temporal Fusion and
Convolutional Neural Network,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link
2203
BibRef
Lu, L.[Li],
Gong, Z.[Zhaoning],
Liang, Y.[Yanan],
Liang, S.[Shuang],
Retrieval of Chlorophyll-a Concentrations of Class II Water Bodies of
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Data,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Mandal, S.[Samiran],
Susanto, R.D.[Raden Dwi],
Ramakrishnan, B.[Balaji],
On Investigating the Dynamical Factors Modulating Surface
Chlorophyll-a Variability along the South Java Coast,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Li, H.T.[Hai-Tao],
Xie, X.[Xuetong],
Yang, X.[Xiankun],
Cao, B.[Bowen],
Xia, X.[Xuening],
An Integrated Model of Summer and Winter for Chlorophyll-a Retrieval
in the Pearl River Estuary Based on Hyperspectral Data,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Werther, M.[Mortimer],
Odermatt, D.[Daniel],
Simis, S.G.H.[Stefan G.H.],
Gurlin, D.[Daniela],
Jorge, D.S.F.[Daniel S.F.],
Loisel, H.[Hubert],
Hunter, P.D.[Peter D.],
Tyler, A.N.[Andrew N.],
Spyrakos, E.[Evangelos],
Characterising retrieval uncertainty of chlorophyll-a algorithms in
oligotrophic and mesotrophic lakes and reservoirs,
PandRS(190), 2022, pp. 279-300.
Elsevier DOI
2208
Chlorophyll-a, Lakes, Uncertainties,
Shapley additive explanations, Machine learning
BibRef
Zhang, L.S.[Lin-Shan],
Zhang, L.[Lifu],
Cen, Y.[Yi],
Wang, S.[Sa],
Zhang, Y.[Yu],
Huang, Y.[Yao],
Sultan, M.[Mubbashra],
Tong, Q.X.[Qing-Xi],
Prediction of Total Phosphorus Concentration in Macrophytic Lakes
Using Chlorophyll-Sensitive Bands: A Case Study of Lake Baiyangdian,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Hadjal, M.[Madjid],
Medina-Lopez, E.[Encarni],
Ren, J.C.[Jin-Chang],
Gallego, A.[Alejandro],
McKee, D.[David],
An Artificial Neural Network Algorithm to Retrieve Chlorophyll a for
Northwest European Shelf Seas from Top of Atmosphere Ocean Colour
Reflectance,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Tanner, K.B.[Kaylee Brook],
Cardall, A.C.[Anna Catherine],
Williams, G.P.[Gustavious Paul],
A Spatial Long-Term Trend Analysis of Estimated Chlorophyll-a
Concentrations in Utah Lake Using Earth Observation Data,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Ali, K.A.[Khalid A.],
Moses, W.J.[Wesley J.],
Application of a PLS-Augmented ANN Model for Retrieving Chlorophyll-a
from Hyperspectral Data in Case 2 Waters of the Western Basin of Lake
Erie,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Li, G.[Geng],
Wang, Z.K.[Zhan-Kun],
Wang, B.B.[Bin-Bin],
Multidecade Trends of Sea Surface Temperature, Chlorophyll-a
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RS(14), No. 15, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Cai, L.[Lina],
Yu, M.[Menghan],
Yan, X.J.[Xiao-Jun],
Zhou, Y.D.[Yong-Dong],
Chen, S.[Songyu],
HY-1C/D Reveals the Chlorophyll-a Concentration Distribution Details
in the Intensive Islands' Waters and Its Consistency with the
Distribution of Fish Spawning Ground,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Hamdeno, M.[Manal],
Nagy, H.[Hazem],
Ibrahim, O.[Omneya],
Mohamed, B.[Bayoumy],
Responses of Satellite Chlorophyll-a to the Extreme Sea Surface
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RS(14), No. 18, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Rodríguez-López, L.[Lien],
González-Rodríguez, L.[Lisdelys],
Duran-Llacer, I.[Iongel],
García, W.[Wirmer],
Cardenas, R.[Rolando],
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Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Greenhouse Detection, Plastic Mulch Detection and Analysis .