123 citations as recorded by crossref.

1. Regional to global assessments of phytoplankton dynamics from the SeaWiFS mission D. Siegel et al. https://doi.org/10.1016/j.rse.2013.03.025
2. EnMAP-Box: Imaging spectroscopy in QGIS B. Jakimow et al. https://doi.org/10.1016/j.softx.2023.101507
3. Community review of Southern Ocean satellite data needs A. Pope et al. https://doi.org/10.1017/S0954102016000390
4. Modeling surface ocean phytoplankton pigments from hyperspectral remote sensing reflectance on global scales S. Kramer et al. https://doi.org/10.1016/j.rse.2021.112879
5. Responses of freshwater algal cell density to hydrochemical variables in an urban aquatic ecosystem, northern China J. Yang et al. https://doi.org/10.1007/s10661-018-7177-2
6. Ocean-scale patterns of environment and climate changes driving global marine phytoplankton biomass dynamics Z. Li et al. https://doi.org/10.1126/sciadv.adm7556
7. Relative contributions of photophysiology and chlorophyll-a abundance to phytoplankton group-specific primary production in the Kuroshio region as inferred by satellite ocean color remote sensing T. Hirata & K. Suzuki https://doi.org/10.1007/s10872-022-00638-5
8. Coupled ocean-atmosphere radiative transfer model in the framework of software package SCIATRAN: Selected comparisons to model and satellite data M. Blum et al. https://doi.org/10.1016/j.asr.2012.02.012
9. Synoptic relationships between surface Chlorophyll-a and diagnostic pigments specific to phytoplankton functional types T. Hirata et al. https://doi.org/10.5194/bg-8-311-2011
10. Phytoplankton Group Identification Using Simulated and In situ Hyperspectral Remote Sensing Reflectance H. Xi et al. https://doi.org/10.3389/fmars.2017.00272
11. Global assessment of ocean carbon export by combining satellite observations and food‐web models D. Siegel et al. https://doi.org/10.1002/2013GB004743
12. Remote sensing of size structure of phytoplankton communities using optical properties of the Chukchi and Bering Sea shelf region A. Fujiwara et al. https://doi.org/10.5194/bg-8-3567-2011
13. Improving the Remote Sensing Retrieval of Phytoplankton Functional Types (PFT) Using Empirical Orthogonal Functions: A Case Study in a Coastal Upwelling Region M. Correa-Ramirez et al. https://doi.org/10.3390/rs10040498
14. On the impacts of phytoplankton-derived organic matter on the properties of the primary marine aerosol – Part 1: Source fluxes E. Fuentes et al. https://doi.org/10.5194/acp-10-9295-2010
15. Eliminating the interference of water for direct sensing of submerged plastics using hyperspectral near-infrared imager C. Zhu & Y. Kanaya https://doi.org/10.1038/s41598-023-39754-7
16. Latitudinal distribution of reactive iodine in the Eastern Pacific and its link to open ocean sources A. Mahajan et al. https://doi.org/10.5194/acp-12-11609-2012
17. Deriving inherent optical properties from decomposition of hyperspectral non-water absorption B. Grunert et al. https://doi.org/10.1016/j.rse.2019.03.004
18. Differential Responses of Growth and Photochemical Performance of Marine Diatoms to Ocean Warming and High Light Irradiance Y. Wu et al. https://doi.org/10.1111/php.13268
19. Imaging Spectrometry of Inland and Coastal Waters: State of the Art, Achievements and Perspectives C. Giardino et al. https://doi.org/10.1007/s10712-018-9476-0
20. The Weddell Gyre, Southern Ocean: Present Knowledge and Future Challenges M. Vernet et al. https://doi.org/10.1029/2018RG000604
21. Reproduction of Spatio-Temporal Patterns of Major Mediterranean Phytoplankton Groups from Remote Sensing OC-CCI Data G. Navarro et al. https://doi.org/10.3389/fmars.2017.00246
22. The influence of the Indian Ocean Dipole on interannual variations in phytoplankton size structure as revealed by Earth Observation R. Brewin et al. https://doi.org/10.1016/j.dsr2.2012.04.009
23. The export and fate of organic matter in the ocean: New constraints from combining satellite and oceanographic tracer observations T. DeVries & T. Weber https://doi.org/10.1002/2016GB005551
24. Information content of absorption spectra and implications for ocean color inversion B. Cael et al. https://doi.org/10.1364/AO.389189
25. Bio-optical provinces in the eastern Atlantic Ocean and their biogeographical relevance B. Taylor et al. https://doi.org/10.5194/bg-8-3609-2011
26. Phytoplankton composition from sPACE: Requirements, opportunities, and challenges I. Cetinić et al. https://doi.org/10.1016/j.rse.2023.113964
27. Inter-comparison of phytoplankton functional type phenology metrics derived from ocean color algorithms and Earth System Models T. Kostadinov et al. https://doi.org/10.1016/j.rse.2016.11.014
28. Seasonal dynamics of major phytoplankton functional types in the coastal waters of the west coast of Canada derived from OLCI Sentinel 3A P. Vishnu et al. https://doi.org/10.3389/fmars.2022.1018510
29. Ocean-colour products for climate-change studies: What are their ideal characteristics? S. Sathyendranath et al. https://doi.org/10.1016/j.rse.2017.04.017
30. The Fundamental Contribution of Phytoplankton Spectral Scattering to Ocean Colour: Implications for Satellite Detection of Phytoplankton Community Structure L. Lain & S. Bernard https://doi.org/10.3390/app8122681
31. Determining the optimal spectral sampling frequency and uncertainty thresholds for hyperspectral remote sensing of ocean color R. Vandermeulen et al. https://doi.org/10.1364/OE.25.00A785
32. Global Assimilation of Ocean‐Color Data of Phytoplankton Functional Types: Impact of Different Data Sets H. Pradhan et al. https://doi.org/10.1029/2019JC015586
33. Perspectives on empirical approaches for ocean color remote sensing of chlorophyll in a changing climate H. Dierssen https://doi.org/10.1073/pnas.0913800107
34. A Consumer's Guide to Satellite Remote Sensing of Multiple Phytoplankton Groups in the Global Ocean C. Mouw et al. https://doi.org/10.3389/fmars.2017.00041
35. Phytoplankton Diversity in the Mediterranean Sea From Satellite Data Using Self‐Organizing Maps R. El Hourany et al. https://doi.org/10.1029/2019JC015131
36. Cyanobacteria blooms in the Baltic Sea: a review of models and facts B. Munkes et al. https://doi.org/10.5194/bg-18-2347-2021
37. Warming enhances protozooplankton top‐down control and nutrient competition E. Lee et al. https://doi.org/10.1002/lno.70422
38. Distribution of phytoplankton functional types in high-nitrate, low-chlorophyll waters in a new diagnostic ecological indicator model A. Palacz et al. https://doi.org/10.5194/bg-10-7553-2013
39. Assimilation of Global Total Chlorophyll OC‐CCI Data and Its Impact on Individual Phytoplankton Fields H. Pradhan et al. https://doi.org/10.1029/2018JC014329
40. Diatoms and Their Microbiomes in Complex and Changing Polar Oceans R. Gilbertson et al. https://doi.org/10.3389/fmicb.2022.786764
41. Prediction of the Export and Fate of Global Ocean Net Primary Production: The EXPORTS Science Plan D. Siegel et al. https://doi.org/10.3389/fmars.2016.00022
42. Global diffuse attenuation derived from vibrational Raman scattering detected in hyperspectral backscattered satellite spectra J. Oelker et al. https://doi.org/10.1364/OE.27.00A829
43. Sensing the ocean biological carbon pump from space: A review of capabilities, concepts, research gaps and future developments R. Brewin et al. https://doi.org/10.1016/j.earscirev.2021.103604
44. The United States' Next Generation of Atmospheric Composition and Coastal Ecosystem Measurements: NASA's Geostationary Coastal and Air Pollution Events (GEO-CAPE) Mission J. Fishman et al. https://doi.org/10.1175/BAMS-D-11-00201.1
45. Data Needs for Hyperspectral Detection of Algal Diversity Across the Globe H. Dierssen et al. https://doi.org/10.5670/oceanog.2020.111
46. Estimation of the Potential Detection of Diatom Assemblages Based on Ocean Color Radiance Anomalies in the North Sea A. Rêve-Lamarche et al. https://doi.org/10.3389/fmars.2017.00408
47. Liquid water absorption and scattering effects in DOAS retrievals over oceans E. Peters et al. https://doi.org/10.5194/amt-7-4203-2014
48. Optical determination of phytoplankton size composition from global SeaWiFS imagery C. Mouw & J. Yoder https://doi.org/10.1029/2010JC006337
49. A three component classification of phytoplankton absorption spectra: Application to ocean-color data E. Devred et al. https://doi.org/10.1016/j.rse.2011.04.025
50. Global retrieval of phytoplankton functional types based on empirical orthogonal functions using CMEMS GlobColour merged products and further extension to OLCI data H. Xi et al. https://doi.org/10.1016/j.rse.2020.111704
51. Radiometric approach for the detection of picophytoplankton assemblages across oceanic fronts P. Lange et al. https://doi.org/10.1364/OE.398127
52. High Resolution Water Column Phytoplankton Composition Across the Atlantic Ocean From Ship-Towed Vertical Undulating Radiometry A. Bracher et al. https://doi.org/10.3389/fmars.2020.00235
53. A Wavelet-Enhanced Inversion Method for Water Quality Retrieval From High Spectral Resolution Data for Complex Waters E. Ampe et al. https://doi.org/10.1109/TGRS.2014.2330251
54. Discrimination of phytoplankton functional groups using an ocean reflectance inversion model P. Werdell et al. https://doi.org/10.1364/AO.53.004833
55. Plankton energy flows using a global size-structured and trait-based model G. Negrete-García et al. https://doi.org/10.1016/j.pocean.2022.102898
56. Test Results From the Prelaunch Characterization Campaign of the Engineering Test Unit of the Ocean Color Instrument of NASA’s Plankton, Aerosol, Cloud and Ocean Ecosystem (PACE) Mission G. Meister et al. https://doi.org/10.3389/frsen.2022.875863
57. A global satellite observation of phytoplankton taxonomic groups over the past two decades Z. Li et al. https://doi.org/10.1111/gcb.16766
58. An algorithm for detecting Trichodesmium surface blooms in the South Western Tropical Pacific C. Dupouy et al. https://doi.org/10.5194/bg-8-3631-2011
59. Impact of multiple satellite ocean color samplings in a day on assessing phytoplankton dynamics Z. Lee et al. https://doi.org/10.1007/s12601-012-0031-5
60. Improvement to the PhytoDOAS method for identification of coccolithophores using hyper-spectral satellite data A. Sadeghi et al. https://doi.org/10.5194/os-8-1055-2012
61. Global retrieval of marine and terrestrial chlorophyll fluorescence at its red peak using hyperspectral top of atmosphere radiance measurements: Feasibility study and first results A. Wolanin et al. https://doi.org/10.1016/j.rse.2015.05.018
62. Remote sensing algorithms for particulate inorganic carbon (PIC) and the global cycle of PIC W. Balch & C. Mitchell https://doi.org/10.1016/j.earscirev.2023.104363
63. Environmental controls on N2 fixation by Trichodesmium in the tropical eastern North Atlantic Ocean—A model-based study Y. Ye et al. https://doi.org/10.1016/j.dsr.2012.01.004
64. Southern Ocean regime shift: divergent trends in surface phytoplankton community composition using a diagnostic pigment framework N. Adroli et al. https://doi.org/10.1038/s41467-026-75303-2
65. Spaceborne Lidar in the Study of Marine Systems C. Hostetler et al. https://doi.org/10.1146/annurev-marine-121916-063335
66. Oligotrophic waters of the Northwest Atlantic support taxonomically diverse diatom communities that are distinct from coastal waters S. Setta et al. https://doi.org/10.1111/jpy.13388
67. Future Retrievals of Water Column Bio-Optical Properties using the Hyperspectral Infrared Imager (HyspIRI) E. Devred et al. https://doi.org/10.3390/rs5126812
68. Contemporaneous disequilibrium of bio‐optical properties in the Southern Ocean M. Kahru et al. https://doi.org/10.1002/2016GL072453
69. Investigation of Spectral Band Requirements for Improving Retrievals of Phytoplankton Functional Types A. Wolanin et al. https://doi.org/10.3390/rs8100871
70. Light absorption by marine cyanobacteria affects tropical climate mean state and variability H. Paulsen et al. https://doi.org/10.5194/esd-9-1283-2018
71. On the possibility of recognising different phytoplankton functional groups and size classes in optically complex waters T. Kutser et al. https://doi.org/10.1016/j.rse.2026.115609
72. Obtaining Phytoplankton Diversity from Ocean Color: A Scientific Roadmap for Future Development A. Bracher et al. https://doi.org/10.3389/fmars.2017.00055
73. Concentrations of Multiple Phytoplankton Pigments in the Global Oceans Obtained from Satellite Ocean Color Measurements with MERIS G. Wang et al. https://doi.org/10.3390/app8122678
74. A comparison between phytoplankton community structures derived from a global 3D ecosystem model and satellite observation T. Hirata et al. https://doi.org/10.1016/j.jmarsys.2012.01.009
75. A global seasonal surface ocean climatology of phytoplankton types based on CHEMTAX analysis of HPLC pigments C. Swan et al. https://doi.org/10.1016/j.dsr.2015.12.002
76. Long-time-scale investigation of phytoplankton communities based on their size in the Arabian Sea R. Shunmugapandi et al. https://doi.org/10.1080/01431161.2020.1714785
77. Coupling ecological concepts with an ocean-colour model: Parameterisation and forward modelling X. Sun et al. https://doi.org/10.1016/j.rse.2024.114487
78. Plankton Imagery Data Inform Satellite‐Based Estimates of Diatom Carbon A. Chase et al. https://doi.org/10.1029/2022GL098076
79. Uncertainty in global downwelling plane irradiance estimates from sintered polytetrafluoroethylene plaque radiance measurements A. Castagna et al. https://doi.org/10.1364/AO.58.004497
80. Global Chlorophyll a Concentrations of Phytoplankton Functional Types With Detailed Uncertainty Assessment Using Multisensor Ocean Color and Sea Surface Temperature Satellite Products H. Xi et al. https://doi.org/10.1029/2020JC017127
81. Effect of phytoplankton community composition and cell size on absorption properties in eutrophic shallow lakes: field and experimental evidence Y. Zhang et al. https://doi.org/10.1364/OE.20.011882
82. Using Machine Learning for Timely Estimates of Ocean Color Information From Hyperspectral Satellite Measurements in the Presence of Clouds, Aerosols, and Sunglint Z. Fasnacht et al. https://doi.org/10.3389/frsen.2022.846174
83. A singular value decomposition approach for detecting and delineating harmful algal blooms in the Red Sea E. Gokul et al. https://doi.org/10.3389/frsen.2023.944615
84. Micron-Scale Biogeography of Seawater Biofilm Colonies at Submersed Solid Substrata Affected by Organic Matter and Microbiome Transformation in the Baltic Sea M. Grzegorczyk et al. https://doi.org/10.3390/ma15186351
85. Remote Sensing of Marine Phytoplankton Sizes and Groups Based on the Generalized Addictive Model (GAM) Y. Wang & F. Liu https://doi.org/10.3390/rs14133037
86. Coupling ecological concepts with an ocean-colour model: Phytoplankton size structure X. Sun et al. https://doi.org/10.1016/j.rse.2022.113415
87. Viewing Marine Bacteria, Their Activity and Response to Environmental Drivers from Orbit D. Grimes et al. https://doi.org/10.1007/s00248-013-0363-4
88. Marine sources of bromoform in the global open ocean – global patterns and emissions I. Stemmler et al. https://doi.org/10.5194/bg-12-1967-2015
89. Nutrient ratios in marine particulate organic matter are predicted by the population structure of well-adapted phytoplankton S. Sharoni & I. Halevy https://doi.org/10.1126/sciadv.aaw9371
90. AIGD-PFT: the first AI-driven global daily gap-free 4 km phytoplankton functional type data product from 1998 to 2023 Y. Zhang et al. https://doi.org/10.5194/essd-16-4793-2024
91. Hyperspectral optical discrimination of phytoplankton community structure in Funka Bay and its implications for ocean color remote sensing of diatoms T. Isada et al. https://doi.org/10.1016/j.rse.2014.12.006
92. Demonstration, validation, and application of hyperspectral microscopy for the collection of cyanobacterial spectral signatures N. Hall et al. https://doi.org/10.1002/lom3.70038
93. Phytoplankton “Missing” Absorption in Marine Waters: A Novel Pigment Compensation Model for the Packaging Effect Y. Huan et al. https://doi.org/10.1029/2020JC016458
94. NASA's surface biology and geology designated observable: A perspective on surface imaging algorithms K. Cawse-Nicholson et al. https://doi.org/10.1016/j.rse.2021.112349
95. Living up to the Hype of Hyperspectral Aquatic Remote Sensing: Science, Resources and Outlook H. Dierssen et al. https://doi.org/10.3389/fenvs.2021.649528
96. Retrospective satellite ocean color analysis of purposeful and natural ocean iron fertilization T. Westberry et al. https://doi.org/10.1016/j.dsr.2012.11.010
97. Seasonal bias in global ocean color observations K. Bisson et al. https://doi.org/10.1364/AO.426137
98. Carbon-based phytoplankton size classes retrieved via ocean color estimates of the particle size distribution T. Kostadinov et al. https://doi.org/10.5194/os-12-561-2016
99. Dynamics of environmental variables during the incidence of algal bloom in the coastal waters of Gujarat along the northeastern Arabian Sea V. Vase et al. https://doi.org/10.1007/s10661-023-11827-0
100. An overview of approaches and challenges for retrieving marine inherent optical properties from ocean color remote sensing P. Werdell et al. https://doi.org/10.1016/j.pocean.2018.01.001
101. Influence of sampling strategies on the monitoring of cyanobacteria in shallow lakes: Lessons from a case study in France D. Pobel et al. https://doi.org/10.1016/j.watres.2010.10.011
102. Simulating PACE Global Ocean Radiances W. Gregg & C. Rousseaux https://doi.org/10.3389/fmars.2017.00060
103. Influence of diatom diversity on the ocean biological carbon pump P. Tréguer et al. https://doi.org/10.1038/s41561-017-0028-x
104. Developing a Community of Practice for Applied Uses of Future PACE Data to Address Marine Food Security Challenges S. Schollaert Uz et al. https://doi.org/10.3389/feart.2019.00283
105. Impact of phytoplankton community size on a linked global ocean optical and ecosystem model C. Mouw et al. https://doi.org/10.1016/j.jmarsys.2011.08.002
106. Accuracy of Empirical Satellite Algorithms for Mapping Phytoplankton Diagnostic Pigments in the Open Ocean: A Supervised Learning Perspective A. Stock & A. Subramaniam https://doi.org/10.3389/fmars.2020.00599
107. TROPOMI-Retrieved Underwater Light Attenuation in Three Spectral Regions in the Ultraviolet and Blue J. Oelker et al. https://doi.org/10.3389/fmars.2022.787992
108. Snow and Water Imaging Spectrometer: mission and instrument concepts for earth-orbiting CubeSats H. Bender et al. https://doi.org/10.1117/1.JRS.12.044001
109. New methods for the retrieval of chlorophyll red fluorescence from hyperspectral satellite instruments: simulations and application to GOME-2 and SCIAMACHY J. Joiner et al. https://doi.org/10.5194/amt-9-3939-2016
110. Remotely sensing harmful algal blooms in the Red Sea E. Gokul et al. https://doi.org/10.1371/journal.pone.0215463
111. The Plankton, Aerosol, Cloud, Ocean Ecosystem Mission: Status, Science, Advances P. Werdell et al. https://doi.org/10.1175/BAMS-D-18-0056.1
112. Predicting global distributions of eukaryotic plankton communities from satellite data H. Kaneko et al. https://doi.org/10.1038/s43705-023-00308-7
113. Marine big data-driven ensemble learning for estimating global phytoplankton group composition over two decades (1997–2020) Y. Zhang et al. https://doi.org/10.1016/j.rse.2023.113596
114. Bio-optical discrimination of diatoms from other phytoplankton in the surface ocean: Evaluation and refinement of a model for the Northwest Atlantic S. Kramer et al. https://doi.org/10.1016/j.rse.2018.08.010
115. Satellite Observations of Phytoplankton Functional Type Spatial Distributions, Phenology, Diversity, and Ecotones T. Moisan et al. https://doi.org/10.3389/fmars.2017.00189
116. Remote sensing of coccolithophore blooms in selected oceanic regions using the PhytoDOAS method applied to hyper-spectral satellite data A. Sadeghi et al. https://doi.org/10.5194/bg-9-2127-2012
117. A pan-Arctic pigment database for phytoplankton and sea–ice algae A. Heidemann et al. https://doi.org/10.5194/essd-18-5505-2026
118. Retrieving the availability of light in the ocean utilising spectral signatures of vibrational Raman scattering in hyper-spectral satellite measurements T. Dinter et al. https://doi.org/10.5194/os-11-373-2015
119. Synergistic Exploitation of Hyper- and Multi-Spectral Precursor Sentinel Measurements to Determine Phytoplankton Functional Types (SynSenPFT) S. Losa et al. https://doi.org/10.3389/fmars.2017.00203
120. Diel light cycle as a key factor for modelling phytoplankton biogeography and diversity I. Tsakalakis et al. https://doi.org/10.1016/j.ecolmodel.2018.06.022
121. Global Retrieval of Diatom Abundance Based on Phytoplankton Pigments and Satellite Data M. Soppa et al. https://doi.org/10.3390/rs61010089
122. Hyperspectral Differentiation of Phytoplankton Taxonomic Groups: A Comparison between Using Remote Sensing Reflectance and Absorption Spectra H. Xi et al. https://doi.org/10.3390/rs71114781
123. Impact of Growth Phase, Pigment Adaptation, and Climate Change Conditions on the Cellular Pigment and Carbon Content of Fifty‐One Phytoplankton Isolates A. Neeley et al. https://doi.org/10.1111/jpy.13279