23.2.6.1 Chlorophyll Estimation in Water

Chapter Contents (Back)
Chlorophyll. Leaf Chlorophyll:
See also Chlorophyll Estimation, Chlorophyll Concentration, Chlorophyll Fluorescence, Chlorophyll Index.
See also Water Quality, Turbidity, Water Areas.
See also Ocean Color Analysis, Ocean Colour Analysis, Water Quality.
See also Cyanobacteria, Analysis, Detection.

Zhan, H.G.[Hai-Gang], Shi, P.[Ping], Chen, C.Q.[Chu-Qun],
Retrieval of oceanic chlorophyll concentration using support vector machines,
GeoRS(41), No. 12, December 2003, pp. 2947-2951.
IEEE Abstract. 0402
BibRef

Kwiatkowska, E.J., Fargion, G.S.,
Application of machine-learning techniques toward the creation of a consistent and calibrated global chlorophyll concentration baseline dataset using remotely sensed ocean color data,
GeoRS(41), No. 12, December 2003, pp. 2844-2860.
IEEE Abstract. 0402
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Alvarez, G.A., Salinas, R.A., Malthus, T.J.,
Integrating CFD modelling, neural networks and remote sensing: controlled prediction of chlorophyll-a concentration in the Mejillones of South Bay,
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Montes-Hugo, M., Fiorani, L., Marullo, S., Roy, S., Gagné, J., Borelli, R., Demers, S., Palucci, A.,
A Comparison between Local and Global Spaceborne Chlorophyll Indices in the St. Lawrence Estuary,
RS(4), No. 12, December 2012, pp. 3666-3688.
DOI Link 1211
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El-Alem, A.[Anas], Chokmani, K.[Karem], Laurion, I.[Isabelle], El-Adlouni, S.E.[Sallah E.],
Comparative Analysis of Four Models to Estimate Chlorophyll-a Concentration in Case-2 Waters Using MODerate Resolution Imaging Spectroradiometer (MODIS) Imagery,
RS(4), No. 8, August 2012, pp. 2373-2400.
DOI Link 1209
BibRef

El-Alem, A.[Anas], Chokmani, K.[Karem], Laurion, I.[Isabelle], El-Adlouni, S.E.[Sallah E.],
An Adaptive Model to Monitor Chlorophyll-a in Inland Waters in Southern Quebec Using Downscaled MODIS Imagery,
RS(6), No. 7, 2014, pp. 6446-6471.
DOI Link 1408
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Morales, C.E.[Carmen E.], Hormazabal, S.[Samuel], Andrade, I.[Isabel], Correa-Ramirez, M.A.[Marco A.],
Time-Space Variability of Chlorophyll-a and Associated Physical Variables within the Region off Central-Southern Chile,
RS(5), No. 11, 2013, pp. 5550-5571.
DOI Link 1312
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Ha, N.T.T.[Nguyen Thi Thu], Koike, K.[Katsuaki], Nhuan, M.T.[Mai Trong],
Improved Accuracy of Chlorophyll-a Concentration Estimates from MODIS Imagery Using a Two-Band Ratio Algorithm and Geostatistics: As Applied to the Monitoring of Eutrophication Processes over Tien Yen Bay (Northern Vietnam),
RS(6), No. 1, 2013, pp. 421-442.
DOI Link 1402
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Ha, N.T.T.[Nguyen Thi Thu], Thao, N.T.P.[Nguyen Thien Phuong], Koike, K.[Katsuaki], Nhuan, M.T.[Mai Trong],
Selecting the Best Band Ratio to Estimate Chlorophyll-a Concentration in a Tropical Freshwater Lake Using Sentinel 2A Images from a Case Study of Lake Ba Be (Northern Vietnam),
IJGI(6), No. 9, 2017, pp. xx-yy.
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Ogashawara, I.[Igor], Alcântara, E.H.[Enner H.], Curtarelli, M.P.[Marcelo P.], Adami, M.[Marcos], Nascimento, R.F.F.[Renata F. F.], Souza, A.F.[Arley F.], Stech, J.L.[José L.], Kampel, M.[Milton],
Performance Analysis of MODIS 500-m Spatial Resolution Products for Estimating Chlorophyll-a Concentrations in Oligo- to Meso-Trophic Waters Case Study: Itumbiara Reservoir, Brazil,
RS(6), No. 2, 2014, pp. 1634-1653.
DOI Link 1403
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Zhou, L.G.[Li-Guo], Roberts, D.A.[Dar A.], Ma, W.C.[Wei-Chun], Zhang, H.[Hao], Tang, L.[Lin],
Estimation of higher chlorophylla concentrations using field spectral measurement and HJ-1A hyperspectral satellite data in Dianshan Lake, China,
PandRS(88), No. 1, 2014, pp. 41-47.
Elsevier DOI 1402
Hyperspectral BibRef

Song, K.[Kaishan], Li, L.[Lin], Li, S.[Shuai], Tedesco, L., Duan, H.T.[Hong-Tao], Li, Z.[Zuchuan], Shi, K.[Kun], Du, J.[Jia], Zhao, Y.[Ying], Shao, T.T.[Tian-Tian],
Using Partial Least Squares-Artificial Neural Network for Inversion of Inland Water Chlorophyll-a,
GeoRS(52), No. 2, February 2014, pp. 1502-1517.
IEEE DOI 1402
calibration BibRef

Yu, G.L.[Gong-Liang], Yang, W.[Wei], Matsushita, B.[Bunkei], Li, R.H.[Ren-Hui], Oyama, Y.[Yoichi], Fukushima, T.[Takehiko],
Remote Estimation of Chlorophyll-a in Inland Waters by a NIR-Red-Based Algorithm: Validation in Asian Lakes,
RS(6), No. 4, 2014, pp. 3492-3510.
DOI Link 1405
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Huang, C.C.[Chang-Chun], Zou, J.[Jun], Li, Y.M.[Yun-Mei], Yang, H.[Hao], Shi, K.[Kun], Li, J.S.[Jun-Sheng], Wang, Y.H.[Yan-Hua], Chena, X.[Xia], Zheng, F.[Fa],
Assessment of NIR-red algorithms for observation of chlorophyll-a in highly turbid inland waters in China,
PandRS(93), No. 1, 2014, pp. 29-39.
Elsevier DOI 1407
Optimal spectral band BibRef

Zhang, Y.C.[Yu-Chao], Ma, R.H.[Rong-Hua], Duan, H.T.[Hong-Tao], Loiselle, S.[Steven], Xu, J.[Jinduo],
A Spectral Decomposition Algorithm for Estimating Chlorophyll-a Concentrations in Lake Taihu, China,
RS(6), No. 6, 2014, pp. 5090-5106.
DOI Link 1407
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Kahru, M.[Mati], Kudela, R.M.[Raphael M.], Anderson, C.R.[Clarissa R.], Manzano-Sarabia, M.[Marlenne], Mitchell, B.G.[B. Greg],
Evaluation of Satellite Retrievals of Ocean Chlorophyll-a in the California Current,
RS(6), No. 9, 2014, pp. 8524-8540.
DOI Link 1410
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Qi, L.[Lin], Hu, C.M.[Chuan-Min], Duan, H.T.[Hong-Tao], Barnes, B.B.[Brian B.], Ma, R.H.[Rong-Hua],
An EOF-Based Algorithm to Estimate Chlorophyll a Concentrations in Taihu Lake from MODIS Land-Band Measurements: Implications for Near Real-Time Applications and Forecasting Models,
RS(6), No. 11, 2014, pp. 10694-10715.
DOI Link 1412
BibRef

Augusto-Silva, P.B.[Pétala B.], Ogashawara, I.[Igor], Barbosa, C.C.F.[Cláudio C. F.], de Carvalho, L.A.S.[Lino A. S.], Jorge, D.S.F.[Daniel S. F.], Fornari, C.I.[Celso Israel], Stech, J.L.[José L.],
Analysis of MERIS Reflectance Algorithms for Estimating Chlorophyll-a Concentration in a Brazilian Reservoir,
RS(6), No. 12, 2014, pp. 11689-11707.
DOI Link 1412
BibRef

Feng, L.[Lian], Hu, C.M.[Chuan-Min], Han, X.X.[Xing-Xing], Chen, X.L.[Xiao-Ling], Qi, L.[Lin],
Long-Term Distribution Patterns of Chlorophyll-a Concentration in China's Largest Freshwater Lake: MERIS Full-Resolution Observations with a Practical Approach,
RS(7), No. 1, 2014, pp. 275-299.
DOI Link 1502
BibRef

Matsushita, B.[Bunkei], Yang, W.[Wei], Yu, G.L.[Gong-Liang], Oyama, Y.[Youichi], Yoshimura, K.[Kazuya], Fukushima, T.[Takehiko],
A hybrid algorithm for estimating the chlorophyll-a concentration across different trophic states in Asian inland waters,
PandRS(102), No. 1, 2015, pp. 28-37.
Elsevier DOI 1503
Chlorophyll-a concentration BibRef

Bao, Y.[Ying], Tian, Q.J.[Qing-Jiu], Chen, M.[Min],
A Weighted Algorithm Based on Normalized Mutual Information for Estimating the Chlorophyll-a Concentration in Inland Waters Using Geostationary Ocean Color Imager (GOCI) Data,
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Delgado, A.L.[Ana L.], Loisel, H.[Hubert], Jamet, C.[Cédric], Vantrepotte, V.[Vincent], Perillo, G.M.E.[Gerardo M.E.], Piccolo, M.C.[M. Cintia],
Seasonal and Inter-Annual Analysis of Chlorophyll-a and Inherent Optical Properties from Satellite Observations in the Inner and Mid-Shelves of the South of Buenos Aires Province (Argentina),
RS(7), No. 9, 2015, pp. 11821.
DOI Link 1511
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Wattelez, G.[Guillaume], Dupouy, C.[Cécile], Mangeas, M.[Morgan], Lefèvre, J.[Jérôme], Touraivane, Frouin, R.[Robert],
A Statistical Algorithm for Estimating Chlorophyll Concentration in the New Caledonian Lagoon,
RS(8), No. 1, 2016, pp. 45.
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Arabi, B.[Behnaz], Salama, M.S.[Mhd. Suhyb], Wernand, M.R.[Marcel Robert], Verhoef, W.[Wouter],
MOD2SEA: A Coupled Atmosphere-Hydro-Optical Model for the Retrieval of Chlorophyll-a from Remote Sensing Observations in Complex Turbid Waters,
RS(8), No. 9, 2016, pp. 722.
DOI Link 1610
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Salem, S.I.[Salem Ibrahim], Higa, H.[Hiroto], Kim, H.J.[Hyung-Jun], Kazuhiro, K.[Komatsu], Kobayashi, H.[Hiroshi], Oki, K.[Kazuo], Oki, T.[Taikan],
Multi-Algorithm Indices and Look-Up Table for Chlorophyll-a Retrieval in Highly Turbid Water Bodies Using Multispectral Data,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link 1706
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Wang, Z.M.[Zuo-Min], Kawamura, K.[Kensuke], Sakuno, Y.J.[Yu-Ji], Fan, X.Y.[Xin-Yan], Gong, Z.[Zhe], Lim, J.Y.[Jih-Yun],
Retrieval of Chlorophyll-a and Total Suspended Solids Using Iterative Stepwise Elimination Partial Least Squares (ISE-PLS) Regression Based on Field Hyperspectral Measurements in Irrigation Ponds in Higashihiroshima, Japan,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link 1704
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Al-Naimi, N.[Noora], Raitsos, D.E.[Dionysios E.], Ben-Hamadou, R.[Radhouan], Soliman, Y.[Yousria],
Evaluation of Satellite Retrievals of Chlorophyll-a in the Arabian Gulf,
RS(9), No. 3, 2017, pp. xx-yy.
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Lins, R.C.[Regina Camara], Martinez, J.M.[Jean-Michel], da Motta Marques, D.[David], Cirilo, J.A.[José Almir], Fragoso, C.R.[Carlos Ruberto],
Assessment of Chlorophyll: A Remote Sensing Algorithms in a Productive Tropical Estuarine-Lagoon System,
RS(9), No. 6, 2017, pp. xx-yy.
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Zhang, H.L.[Hai-Long], Qiu, Z.F.[Zhong-Feng], Sun, D.Y.[De-Yong], Wang, S.Q.[Sheng-Qiang], He, Y.J.[Yi-Jun],
Seasonal and Interannual Variability of Satellite-Derived Chlorophyll-a (2000-2012) in the Bohai Sea, China,
RS(9), No. 6, 2017, pp. xx-yy.
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Li, W.Z.[Wen-Zhao], El-Askary, H.[Hesham], ManiKandan, K.P., Qurban, M.A.[Mohamed A.], Garay, M.J.[Michael J.], Kalashnikova, O.V.[Olga V.],
Synergistic Use of Remote Sensing and Modeling to Assess an Anomalously High Chlorophyll-a Event during Summer 2015 in the South Central Red Sea,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link 1708
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Salem, S.I.[Salem Ibrahim], Strand, M.H.[Marie Hayashi], Higa, H.[Hiroto], Kim, H.[Hyungjun], Kazuhiro, K.[Komatsu], Oki, K.[Kazuo], Oki, T.[Taikan],
Evaluation of MERIS Chlorophyll-a Retrieval Processors in a Complex Turbid Lake Kasumigaura over a 10-Year Mission,
RS(9), No. 10, 2017, pp. xx-yy.
DOI Link 1711
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Carswell, T.[Tyson], Costa, M.[Maycira], Young, E.[Erika], Komick, N.[Nicholas], Gower, J.[Jim], Sweeting, R.[Ruston],
Evaluation of MODIS-Aqua Atmospheric Correction and Chlorophyll Products of Western North American Coastal Waters Based on 13 Years of Data,
RS(9), No. 10, 2017, pp. xx-yy.
DOI Link 1711
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Laliberté, J.[Julien], Larouche, P.[Pierre], Devred, E.[Emmanuel], Craig, S.[Susanne],
Chlorophyll-a Concentration Retrieval in the Optically Complex Waters of the St. Lawrence Estuary and Gulf Using Principal Component Analysis,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
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Watanabe, F.[Fernanda], Rodrigues, T.[Thanan], do Carmo, A.[Alisson], Alcântara, E.H.[Enner Herênio], Shimabukuro, M.[Milton], Imai, N.[Nilton], Bernardo, N.[Nariane], Rotta, L.H.[Luiz Henrique],
Assessment of Scattering Error Correction Techniques for AC-S Meter in a Tropical Eutrophic Reservoir,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
Measurements of absorption coefficients overestimate due to scattering. BibRef

Watanabe, F.[Fernanda], Alcântara, E.H.[Enner Herênio], Imai, N.[Nilton], Rodrigues, T.[Thanan], Bernardo, N.[Nariane],
Estimation of Chlorophyll-a Concentration from Optimizing a Semi-Analytical Algorithm in Productive Inland Waters,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
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Markogianni, V.[Vassiliki], Kalivas, D.[Dionissios], Petropoulos, G.P.[George P.], Dimitriou, E.[Elias],
An Appraisal of the Potential of Landsat 8 in Estimating Chlorophyll-a, Ammonium Concentrations and Other Water Quality Indicators,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
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Campos Gomes, A.C.[Ana Carolina], Bernardo, N.[Nariane], Coelho do Carmo, A.[Alisson], Rodrigues, T.[Thanan], Alcântara, E.H.[Enner Herênio],
Diffuse Attenuation Coefficient Retrieval in CDOM Dominated Inland Water with High Chlorophyll-a Concentrations,
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Yang, M.M.[Meng Meng], Ishizaka, J.[Joji], Goes, J.I.[Joaquim I.], do R. Gomes, H.[Helga], de Raús Maúre, E.[Elígio], Hayashi, M.[Masataka], Katano, T.[Toshiya], Fujii, N.[Naoki], Saitoh, K.[Katsuya], Mine, T.[Takayuki], Yamashita, H.[Hirokazu], Fujii, N.[Naoki], Mizuno, A.[Akiko],
Improved MODIS-Aqua Chlorophyll-a Retrievals in the Turbid Semi-Enclosed Ariake Bay, Japan,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810
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Lins, R.C.[Regina Camara], Martinez, J.M.[Jean-Michel], da Motta Marques, D.[David], Cirilo, J.A.[José Almir], Medeiros, P.R.P.[Paulo Ricardo Petter], Júnior, C.R.F.[Carlos Ruberto Fragoso],
A Multivariate Analysis Framework to Detect Key Environmental Factors Affecting Spatiotemporal Variability of Chlorophyll-a in a Tropical Productive Estuarine-Lagoon System,
RS(10), No. 6, 2018, pp. xx-yy.
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Lacava, T.[Teodosio], Ciancia, E.[Emanuele], di Polito, C.[Carmine], Madonia, A.[Alice], Pascucci, S.[Simone], Pergola, N.[Nicola], Piermattei, V.[Viviana], Satriano, V.[Valeria], Tramutoli, V.[Valerio],
Evaluation of MODIS: Aqua Chlorophyll-a Algorithms in the Basilicata Ionian Coastal Waters,
RS(10), No. 7, 2018, pp. xx-yy.
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Bellacicco, M.[Marco], Ciani, D.[Daniele], Doxaran, D.[David], Vellucci, V.[Vincenzo], Antoine, D.[David], Wang, M.[Menghua], d'Ortenzio, F.[Fabrizio], Marullo, S.[Salvatore],
Assessing the Potential Benefits of the Geostationary Vantage Point for Generating Daily Chlorophyll-a Maps in the Baltic Sea,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901
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Ansper, A.[Ave], Alikas, K.[Krista],
Retrieval of Chlorophyll a from Sentinel-2 MSI Data for the European Union Water Framework Directive Reporting Purposes,
RS(11), No. 1, 2018, pp. xx-yy.
DOI Link 1901
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Molkov, A.A.[Alexander A.], Fedorov, S.V.[Sergei V.], Pelevin, V.V.[Vadim V.], Korchemkina, E.N.[Elena N.],
Regional Models for High-Resolution Retrieval of Chlorophyll a and TSM Concentrations in the Gorky Reservoir by Sentinel-2 Imagery,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
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Xu, M., Liu, H., Beck, R., Lekki, J., Yang, B., Shu, S., Liu, Y., Benko, T., Anderson, R., Tokars, R., Johansen, R., Emery, E., Reif, M.,
Regionally and Locally Adaptive Models for Retrieving Chlorophyll-a Concentration in Inland Waters From Remotely Sensed Multispectral and Hyperspectral Imagery,
GeoRS(57), No. 7, July 2019, pp. 4758-4774.
IEEE DOI 1907
Lakes, Adaptation models, Hyperspectral imaging, Atmospheric modeling, Water resources, Airborne hyperspectral, Sentinel-2 multispectral BibRef

Caballero, I.[Isabel], Stumpf, R.P.[Richard P.], Meredith, A.[Andrew],
Preliminary Assessment of Turbidity and Chlorophyll Impact on Bathymetry Derived from Sentinel-2A and Sentinel-3A Satellites in South Florida,
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Rani, M.[Meenu], Rehman, S.[Sufia], Sajjad, H.[Haroon], Alare, R.S.[Rahinatu Sidiki], Chaudhary, B.S., Patairiya, S.[Shashikanta], Rawat, J.S., Chetri, T.[Tilok], Patel, S.[Swagatika], Kumar, P.[Pavan],
NIR-red algorithms-based model for chlorophyll-a retrieval in highly turbid Inland Densu River Basin in South-East Ghana, West Africa,
IET-IPR(13), No. 8, 20 June 2019, pp. 1328-1332.
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A New Algorithm to Estimate Chlorophyll-A Concentrations in Turbid Yellow Sea Water Using a Multispectral Sensor in a Low-Altitude Remote Sensing System,
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Moutier, W.[William], Thomalla, S.J.[Sandy J], Bernard, S.[Stewart], Wind, G.[Galina], Ryan-Keogh, T.J.[Thomas J], Smith, M.E.[Marié E],
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Liu, Y.P.[Yu-Peng], Tang, D.L.[Dan-Ling], Evgeny, M.[Morozov],
Chlorophyll Concentration Response to the Typhoon Wind-Pump Induced Upper Ocean Processes Considering Air-Sea Heat Exchange,
RS(11), No. 15, 2019, pp. xx-yy.
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Blix, K.[Katalin], Li, J.[Juan], Massicotte, P.[Philippe], Matsuoka, A.[Atsushi],
Developing a New Machine-Learning Algorithm for Estimating Chlorophyll-a Concentration in Optically Complex Waters: A Case Study for High Northern Latitude Waters by Using Sentinel 3 OLCI,
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Liu, F., Tang, S.,
Evaluation of Red-Peak Algorithms for Chlorophyll Measurement in the Pearl River Estuary,
GeoRS(57), No. 11, November 2019, pp. 8928-8936.
IEEE DOI 1911
Rivers, Sea measurements, Oceans, Satellites, Image color analysis, Optical sensors, Instruments, Chlorophyll, peak enveloped area BibRef

Clay, S.[Stephanie], Peña, A.[Angelica], DeTracey, B.[Brendan], Devred, E.[Emmanuel],
Evaluation of Satellite-Based Algorithms to Retrieve Chlorophyll-a Concentration in the Canadian Atlantic and Pacific Oceans,
RS(11), No. 22, 2019, pp. xx-yy.
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Cairo, C.[Carolline], Barbosa, C.[Claudio], Lobo, F.[Felipe], Novo, E.[Evlyn], Carlos, F.[Felipe], Maciel, D.[Daniel], Júnior, R.F.[Rogério Flores], Silva, E.[Edson], Curtarelli, V.[Victor],
Hybrid Chlorophyll-a Algorithm for Assessing Trophic States of a Tropical Brazilian Reservoir Based on MSI/Sentinel-2 Data,
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Vadakke-Chanat, S., Shanmugam, P.,
A Model for the Vertical Chlorophyll-a Distribution in the Bay of Bengal Using Remote Sensing Data,
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IEEE DOI 2001
Sea measurements, Optical variables measurement, Oceans, Optical sensors, Market research, Estimation, Biomass, Bay of Bengal, remote sensing BibRef

Xu, J.[Jian], Gao, C.[Chen], Wang, Y.Q.[Ye-Qiao],
Extraction of Spatial and Temporal Patterns of Concentrations of Chlorophyll-a and Total Suspended Matter in Poyang Lake Using GF-1 Satellite Data,
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Han, Z.H.[Zhao-Hui], He, Y.J.[Yi-Jun], Liu, G.Q.[Guo-Qiang], Perrie, W.[William],
Application of DINCAE to Reconstruct the Gaps in Chlorophyll-a Satellite Observations in the South China Sea and West Philippine Sea,
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Lee, D.[Dabin], Son, S.[SeungHyun], Joo, H.[HuiTae], Kim, K.[Kwanwoo], Kim, M.J.[Myung Joon], Jang, H.K.[Hyo Keun], Yun, M.S.[Mi Sun], Kang, C.K.[Chang-Keun], Lee, S.H.[Sang Heon],
Estimation of the Particulate Organic Carbon to Chlorophyll-a Ratio Using MODIS-Aqua in the East/Japan Sea, South Korea,
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Umbert, M.[Marta], Guimbard, S.[Sebastien], Poy, J.B.[Joaquim Ballabrera], Turiel, A.[Antonio],
Synergy between Ocean Variables: Remotely Sensed Surface Temperature and Chlorophyll Concentration Coherence,
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Cui, T.W., Zhang, J., Wang, K., Wei, J.W., Mu, B., Ma, Y., Zhu, J.H., Liu, R.J., Chen, X.Y.,
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Elsevier DOI 2005
Chlorophyll concentration (Chla), Retrieval algorithm, Optical water type (OWT), Optical classification, Bohai Sea BibRef

Buma, W.G.[Willibroad Gabila], Lee, S.I.[Sang-Il],
Evaluation of Sentinel-2 and Landsat 8 Images for Estimating Chlorophyll-a Concentrations in Lake Chad, Africa,
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Yu, Y.[Yan], Chen, S.B.[Sheng-Bo], Qin, W.H.[Wen-Han], Lu, T.Q.[Tian-Qi], Li, J.[Jian], Cao, Y.J.[Yi-Jing],
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Robles-Tamayo, C.M.[Carlos Manuel], García-Morales, R.[Ricardo], Valdez-Holguín, J.E.[José Eduardo], Figueroa-Preciado, G.[Gudelia], Herrera-Cervantes, H.[Hugo], López-Martínez, J.[Juana], Enríquez-Ocaña, L.F.[Luis Fernando],
Chlorophyll a Concentration Distribution on the Mainland Coast of the Gulf of California, Mexico,
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Iwasaki, S.[Suginori],
Daily Variation of Chlorophyll-A Concentration Increased by Typhoon Activity,
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Yang, M.M.[Meng-Meng], Goes, J.I.[Joaquim I.], Tian, H.Z.[Hong-Zhen], de R. Maúre, E.[Elígio], Ishizaka, J.[Joji],
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Park, J.[Jinku], Kim, H.C.[Hyun-Cheol], Bae, D.[Dukwon], Jo, Y.H.[Young-Heon],
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Estimating Chlorophyll-a of Inland Water Bodies in Greece Based on Landsat Data,
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Hyperspectral Imaging from a Multipurpose Floating Platform to Estimate Chlorophyll-a Concentrations in Irrigation Pond Water,
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DOI Link 2007
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Hammond, M.L.[Matthew L.], Henson, S.A.[Stephanie A.], Lamquin, N.[Nicolas], Clerc, S.[Sébastien], Donlon, C.[Craig],
Assessing the Effect of Tandem Phase Sentinel-3 OLCI Sensor Uncertainty on the Estimation of Potential Ocean Chlorophyll-a Trends,
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Lisboa, F.[Filipe], Brotas, V.[Vanda], Santos, F.D.[Filipe Duarte], Kuikka, S.[Sakari], Kaikkonen, L.[Laura], Maeda, E.E.[Eduardo Eiji],
Spatial Variability and Detection Levels for Chlorophyll-a Estimates in High Latitude Lakes Using Landsat Imagery,
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Liu, R.R.[Ruo-Ran], Ling, Q.L.[Qiao-Lv], Zhang, Q.B.[Qiang-Bo], Zhou, Y.[Yudi], Le, C.F.[Cheng-Feng], Chen, Y.T.[Ya-Tong], Liu, Q.[Qun], Chen, W.B.[Wei-Biao], Tang, J.W.[Jun-Wu], Liu, D.[Dong],
Detection of Chlorophyll a and CDOM Absorption Coefficient with a Dual-Wavelength Oceanic Lidar: Wavelength Optimization Method,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
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Wang, L.[Lei], Xu, M.[Min], Liu, Y.[Yang], Liu, H.X.[Hong-Xing], Beck, R.[Richard], Reif, M.[Molly], Emery, E.[Erich], Young, J.[Jade], Wu, Q.S.[Qiu-Sheng],
Mapping Freshwater Chlorophyll-a Concentrations at a Regional Scale Integrating Multi-Sensor Satellite Observations with Google Earth Engine,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010
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Yang, X.[Xiao], Xu, G.J.[Guang-Jun], Liu, Y.[Yu], Sun, W.J.[Wen-Jin], Xia, C.S.[Chang-Shui], Dong, C.M.[Chang-Ming],
Multi-Source Data Analysis of Mesoscale Eddies and Their Effects on Surface Chlorophyll in the Bay of Bengal,
RS(12), No. 21, 2020, pp. xx-yy.
DOI Link 2011
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Kritten, L.[Lena], Preusker, R.[Rene], Fischer, J.[Jürgen],
A New Retrieval of Sun-Induced Chlorophyll Fluorescence in Water from Ocean Colour Measurements Applied on OLCI L-1b and L-2,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012
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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 Chlorophyll-a and Temperature Fields from Remote Sensing Observations,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012
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Tenjo, C.[Carolina], Ruiz-Verdú, A.[Antonio], van Wittenberghe, S.[Shari], Delegido, J.[Jesús], Moreno, J.[José],
A New Algorithm for the Retrieval of Sun Induced Chlorophyll Fluorescence of Water Bodies Exploiting the Detailed Spectral Shape of Water-Leaving Radiance,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101
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Yang, M.M.[Meng-Meng], Khan, F.A.[Faisal Ahmed], Tian, H.Z.[Hong-Zhen], Liu, Q.P.[Qin-Ping],
Analysis of the Monthly and Spring-Neap Tidal Variability of Satellite Chlorophyll-a and Total Suspended Matter in a Turbid Coastal Ocean Using the DINEOF Method,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
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Maier, P.M.[Philipp M.], Keller, S.[Sina], Hinz, S.[Stefan],
Deep Learning with WASI Simulation Data for Estimating Chlorophyll a Concentration of Inland Water Bodies,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
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Su, H.[Hua], Lu, X.M.[Xue-Mei], Chen, Z.Q.[Zuo-Qi], Zhang, H.S.[Hong-Sheng], Lu, W.F.[Wen-Fang], Wu, W.T.[Wen-Ting],
Estimating Coastal Chlorophyll-A Concentration from Time-Series OLCI Data Based on Machine Learning,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
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Tavares, M.H.[Matheus Henrique], Lins, R.C.[Regina Camara], Harmel, T.[Tristan], Fragoso, Jr., C.R.[Carlos Ruberto], Martínez, J.M.[Jean-Michel], Motta-Marques, D.[David],
Atmospheric and sunglint correction for retrieving chlorophyll-a in a productive tropical estuarine-lagoon system using Sentinel-2 MSI imagery,
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 on Satellite Imagery for Chlorophyll-a Estimation in Freshwater Bodies?,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
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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
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Rousseaux, C.S.[Cecile S.], Gregg, W.W.[Watson W.], Ott, L.[Lesley],
Assessing the Skills of a Seasonal Forecast of Chlorophyll in the Global Pelagic Oceans,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
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Hu, C.M.[Chuan-Min], Feng, L.[Lian], Guan, Q.[Qi],
A Machine Learning Approach to Estimate Surface Chlorophyll a Concentrations in Global Oceans From Satellite Measurements,
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 Chlorophyll in a Drinking Water Reservoir Using Landsat 5 TM Data,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link 2106
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Niroumand-Jadidi, M.[Milad], Bovolo, F.[Francesca], Bruzzone, L.[Lorenzo], Gege, P.[Peter],
Inter-Comparison of Methods for Chlorophyll-a Retrieval: Sentinel-2 Time-Series Analysis in Italian Lakes,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link 2106
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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 Temperature, and Their Relationship with Bathymetry over the Coasts of UAE,
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
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Wang, Y.[Yueqi], Gao, Z.Q.[Zhi-Qiang], Ning, J.[Jicai],
An Adaptive Piecewise Harmonic Analysis Method for Reconstructing Multi-Year Sea Surface Chlorophyll-A Time Series,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107
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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 Islands,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107
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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 (OHS) Imagery for Remotely Monitoring Chlorophyll-a in Eutrophic Plateau Lakes,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107
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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
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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
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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
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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
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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
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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 Inland Lakes and Reservoirs Based on ZY1-02D Satellite Hyperspectral 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 Concentration, and Ocean Eddies in the Gulf of Mexico,
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 Temperatures over the Arabian and Omani Gulf,
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], Urrutia, R.[Roberto],
Assessment of the Diffuse Attenuation Coefficient of Photosynthetically Active Radiation in a Chilean Lake,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209
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Glukhovets, D.[Dmitry], Sheberstov, S.[Sergey], Vazyulya, S.[Svetlana], Yushmanova, A.[Anna], Salyuk, P.[Pavel], Sahling, I.[Inna], Aglova, E.[Evgeniia],
Influence of the Accuracy of Chlorophyll-Retrieval Algorithms on the Estimation of Solar Radiation Absorbed in the Barents Sea,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
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Wang, D.[Dong], Tang, B.H.[Bo-Hui], Fu, Z.[Zhitao], Huang, L.[Liang], Li, M.[Menghua], Chen, G.[Guokun], Pan, X.J.[Xue-Jun],
Estimation of Chlorophyll-A Concentration with Remotely Sensed Data for the Nine Plateau Lakes in Yunnan Province,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Shi, X.M.[Xu-Ming], Gu, L.J.[Ling-Jia], Jiang, T.[Tao], Zheng, X.M.[Xing-Ming], Dong, W.[Wen], Tao, Z.[Zui],
Retrieval of Chlorophyll-a Concentrations Using Sentinel-2 MSI Imagery in Lake Chagan Based on Assessments with Machine Learning Models,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
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Quang, N.H.[Nguyen Hong], Nguyen, M.N.[Minh Nguyen], Paget, M.[Matt], Anstee, J.[Janet], Viet, N.D.[Nguyen Duc], Nones, M.[Michael], Tuan, V.A.[Vu Anh],
Assessment of Human-Induced Effects on Sea/Brackish Water Chlorophyll-a Concentration in Ha Long Bay of Vietnam with Google Earth Engine,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
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Robles-Tamayo, C.M.[Carlos Manuel], García-Morales, R.[Ricardo], Romo-León, J.R.[José Raúl], Figueroa-Preciado, G.[Gudelia], Peñalba-Garmendia, M.C.[María Cristina], Enríquez-Ocaña, L.F.[Luis Fernando],
Variability of Chl a Concentration of Priority Marine Regions of the Northwest of Mexico,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
Chlorophyll a. BibRef

Xu, S.Q.[Shi-Qi], Li, S.[Sijia], Tao, Z.[Zui], Song, K.[Kaishan], Wen, Z.D.[Zhi-Dan], Li, Y.[Yong], Chen, F.F.[Fang-Fang],
Remote Sensing of Chlorophyll-a in Xinkai Lake Using Machine Learning and GF-6 WFV Images,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211
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Fernández-Tejedor, M.[Margarita], Velasco, J.E.[Jorge Enrique], Angelats, E.[Eduard],
Accurate Estimation of Chlorophyll-a Concentration in the Coastal Areas of the Ebro Delta (NW Mediterranean) Using Sentinel-2 and Its Application in the Selection of Areas for Mussel Aquaculture,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211
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Cen, H.B.[Hao-Bin], Jiang, J.[Jiahan], Han, G.Q.[Guo-Qing], Lin, X.[Xiayan], Liu, Y.[Yu], Jia, X.Y.[Xiao-Yan], Ji, Q.[Qiyan], Li, B.[Bo],
Applying Deep Learning in the Prediction of Chlorophyll-a in the East China Sea,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
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Barraza-Moraga, F.[Francisca], Alcayaga, H.[Hernán], Pizarro, A.[Alonso], Félez-Bernal, J.[Jorge], Urrutia, R.[Roberto],
Estimation of Chlorophyll-a Concentrations in Lanalhue Lake Using Sentinel-2 MSI Satellite Images,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
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Chen, S.L.[Shuang-Ling], Meng, Y.[Yu], Lin, S.[Sheng], Xi, J.Y.[Jing-Yuan],
Remote Sensing of the Seasonal and Interannual Variability of Surface Chlorophyll-a Concentration in the Northwest Pacific over the Past 23 Years (1997-2020),
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
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Salyuk, P.A.[Pavel A.], Stepochkin, I.E.[Igor E.], Sokolova, E.B.[Ekaterina B.], Pugach, S.P.[Svetlana P.], Kachur, V.A.[Vasiliy A.], Pipko, I.I.[Irina I.],
Developing and Using Empirical Bio-Optical Algorithms in the Western Part of the Bering Sea in the Late Summer Season,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
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Ma, Y.X.[Yuan-Xu], Sun, D.Q.[Dong-Qi], Liu, W.H.[Wei-Hua], You, Y.F.[Yong-Fa], Wang, S.Y.[Si-Yuan], Sun, Z.C.[Zhong-Chang], Wang, S.H.[Shao-Hua],
Using a Remote-Sensing-Based Piecewise Retrieval Algorithm to Map Chlorophyll-a Concentration in a Highland River System,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link 2212
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Lin, J.Y.[Jia-Yi], Ho, H.[Hua], Zheng, Z.W.[Zhe-Wen],
Improved Understanding of Typhoon-Induced Immediate Chlorophyll-A Response Using Advanced Himawari Imager (AHI) Onboard Himawari-8,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link 2212
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Merged Multi-Sensor Ocean Colour Chlorophyll Product Evaluation for the British Columbia Coast,
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Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Greenhouse Detection, Plastic Mulch Detection and Analysis .


Last update:Mar 16, 2024 at 20:36:19