ocean color

Bellacicco, M., Volpe, G., Briggs, N., Brando, V., Pitarch, J., Landolfi, A., et al. (2018). Global Distribution of Non-algal Particles From Ocean Color Data and Implications for Phytoplankton Biomass Detection. Geophysical Research Letters. http://doi.org/10.1029/2018GL078185

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Bellacicco, M., Volpe, G., Briggs, N., Brando, V., Pitarch, J., Landolfi, A., et al. (2018). Global Distribution of Non-algal Particles From Ocean Color Data and Implications for Phytoplankton Biomass Detection. Geophysical Research Letters. http://doi.org/10.1029/2018GL078185

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Sammartino, M., Di Cicco, A., Marullo, S., & Santoleri, R. (2015). Spatio-temporal variability of micro-, nano- and pico-phytoplankton in the Mediterranean Sea from satellite ocean colour data of SeaWiFS. Ocean Science. http://doi.org/10.5194/os-11-759-2015

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Brando, V. E., Lovell, J. L., King, E. A., Boadle, D., Scott, R., & Schroeder, T. (2016). The potential of autonomous ship-borne hyperspectral radiometers for the validation of ocean color radiometry data. Remote Sensing. http://doi.org/10.3390/rs8020150

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Brando, V. E., Lovell, J. L., King, E. A., Boadle, D., Scott, R., & Schroeder, T. (2016). The potential of autonomous ship-borne hyperspectral radiometers for the validation of ocean color radiometry data. Remote Sensing. http://doi.org/10.3390/rs8020150

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Sammartino, M., Di Cicco, A., Marullo, S., & Santoleri, R. (2015). Spatio-temporal variability of micro-, nano- and pico-phytoplankton in the Mediterranean Sea from satellite ocean colour data of SeaWiFS. Ocean Science. http://doi.org/10.5194/os-11-759-2015

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