Lidar monitoring of dinoflagellate algal bloom on the Swedish coast

Roberto Barbini; Francesco Colao; Roberta Fantoni; Antonio Palucci; Sergio Ribezzo

doi:10.1117/12.274754

23 May 1997 Lidar monitoring of dinoflagellate algal bloom on the Swedish coast

Roberto Barbini, Francesco Colao, Roberta Fantoni, Antonio Palucci, Sergio Ribezzo

Proceedings Volume 3107, Remote Sensing of Vegetation and Water, and Standardization of Remote Sensing Methods; (1997) https://doi.org/10.1117/12.274754
Event: Environmental Sensing III, 1997, Munich, Germany

Abstract

The ENEA group has participated to the second ICES/IOC workshop on in situ growth rates of dinoflagellates, held at the Kristineberg Marine Research Station. The laser induced fluorescence (LIF) emission of natural communities and cultures has been monitored in vivo to obtain information on the algae species, characterized by different pigments contents, and on their photosynthetic activity, which is related to the growth rate and biomass production. A laser fluorometer and a lidar system, used for local and remote LIF excitation of phytoplankton, have been operated during the marine campaign, both exciting the sea water in the UV. In particular, the lidar fluorosensor has been equipped with a laser transmitter specifically designed to operate differentially in the pump-and-probe mode, which allows to directly measure in vivo the chlorophyll fluorescence quantum yield. Experiments were conducted on two mesocosms containing the natural community with addition of nutrients. Chemical methods have been used for calibration of the two laser apparata. Results of the campaign are presented, together with the lidar data collected from the sea surface in crossing two nearby fjords along a selected sea transect.

Citation Download Citation

Roberto Barbini, Francesco Colao, Roberta Fantoni, Antonio Palucci, and Sergio Ribezzo "Lidar monitoring of dinoflagellate algal bloom on the Swedish coast", Proc. SPIE 3107, Remote Sensing of Vegetation and Water, and Standardization of Remote Sensing Methods, (23 May 1997); https://doi.org/10.1117/12.274754

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