Colour and Light in the Ocean, volume II

This research topic focuses on the use of satellite remote sensing to monitor and measure global aquatic ecosystems. It explores the potential of multispectral remote sensing to detect dominant phytoplankton groups, the magnitude and variability of the biological pump, the accuracy of atmospheric correction methods, the uncertainties associated with phytoplankton pigment quantification, a bio-geo-optical model for natural waters, a novel correction method for the OC-CCI dataset, parameters used to define the depth of the ocean's productive layer, a retrieval scheme to derive concentrations of dissolved organic carbon, the influence of climate variations on phytoplankton, a locally developed algal-bloom classification algorithm, a scalable Earth Observation framework to assess the national extent, blue carbon stock and sequestration rate of seagrass ecosystems, seasonal variability of net primary production, a feed-forward neural network model for the inversion of subsurface particulate backscatter coefficients, chlorophyll concentration and total particulate organic carbon, the use of in situ observations of chlorophyll a and nitrate with remote sensing, a new dataset produced by merging Chla records from multiple sensors, an a-POC algorithm to accurately map global surface ocean POC concentrations, a framework to classify five major groups of phytoplankton, a quantile regression model to derive phytoplankton nitrogen and carbon, and two concepts to quantify fragility in marine photosynthesis.

The research highlights the potential of multispectral remote sensing to detect dominant phytoplankton groups, the use of satellite-derived products to estimate the magnitude of the biological pump, the accuracy of atmospheric correction methods, the uncertainties associated with phytoplankton pigment quantification, a bio-geo-optical model for natural waters, a novel correction method for the OC-CCI dataset, the depth of the ocean's productive layer, a retrieval scheme to derive concentrations of dissolved organic carbon, the influence of climate variations on phytoplankton, a locally developed algal-bloom classification algorithm, a scalable Earth Observation framework to assess the national extent, blue carbon stock and sequestration rate of seagrass ecosystems, seasonal variability of net primary production, a feed-forward neural network model for the inversion of subsurface particulate backscatter coefficients, chlorophy