PhD: High-resolution remote sensing of phytoplankton blooms in coastal waters

Centre National D'Etudes Spatiales (CNES)

Nantes, France 🇫🇷


The Ph. D. project is part of the ANR PPR “River-dominated Ocean Margins” (RiOMar) project (2022-2029), which involves around 20 research laboratories in France.  

Continental shelves and coastal regions influenced by rivers are vulnerable ecosystems. These systems face a double constraint: first, the input of nutrients, particles and contaminants from rivers cause eutrophication, hypoxia, harmful algal blooms (HABs), enhanced turbidity, and contamination in the coastal environment; and second, climate change leads to an alteration of coastal circulation, changes in stratification, warming and acidification of the ocean, sea level rise and increase in the occurrence of extreme events (storms, heat waves, floods). The future of these highly productive systems, generally located in densely populated areas, remains particularly uncertain, and their medium- to long-term management requires numerical tools capable of limiting uncertainties about their trajectories. In this context and to prepare solutions for the future, an integrated approach is required combining augmented observatories, innovative digital tools, and model simulations to anticipate the future of water quality in French coastal areas under the influence of rivers in the 21st century. Within the broad context of RiOMAR, the Ph. D. project will focus on the observation of phytoplankton bloom dynamics, with a regional highlight on HABs and seawater discolorations in coastal waters directly exposed to terrestrial inputs from the Loire and Vilaine rivers (dissolved and particulate matter, nutrients and other contaminants). For that purpose, the Ph. D. candidate will process and analyse phytoplankton time-series using high-resolution satellite remote sensing and field data in the shelf area influenced by estuarine drivers, in order to better understand how phytoplankton responds to freshwater inputs, river plumes, and fluxes of dissolved and particulate matter along the river – ocean continuum. 

However, current satellites are not designed to accurately observe phytoplankton in extremely dynamics coastal zones. The ideal satellite mission should meet the so-called “H4 requirements” (Muller-Karger et al., 2018), i.e. offer at the same time: high spatial resolution (< 30 m), high temporal resolution (< 1 day), high radiometric quality (SNR > 1000 in the visible and near-infrared, VNIR), and high spectral resolution (ideally hyperspectral in the VNIR, and at least two SWIR bands for atmospheric correction in turbid environments). Such mission does not currently exist. The originality of the Ph. D. project will be to combine the most-advanced sensors to densify the series of satellite observations. Phytoplankton blooms will be observed at high spatial resolution using Sentinel-2 (20 m / 5 days), at high temporal resolution using Sentinel-3 (300 m / 2 days), and at hyperspectral resolution using PRISMA (30 m / 29 days) and/or EnMAP (30 m / 4 days). Furthermore, VENmS data (5 m / 2 days) acquired in the Vilaine estuary since March 2022 in the frame of VM5 phase will be used, thus significantly increasing both the spatial and temporal resolutions. To our knowledge, it is the first time that VENmS will be used to study phytoplankton blooms, and its unprecedented resolution will be critical to better understand bloom trajectories in highly dynamic coastal waters.  

In complement to satellite observations, high-frequency measurements from the MOLIT buoy will be combined with field sampling of bio-optical properties (reflectance, absorption, and pigments), phytoplankton biodiversity, dissolved oxygen, and nutrients to determine environmental trajectories underpinning red tides and associated hypoxia events. In situ data will make it possible to better understand phytoplankton environmental dynamics and optical variability, and validate satellite observation in terms of reflectance and derived bio-optical properties. In particular, innovative algorithms developed in the frame of the CNES LASHA project will be evaluated and improved, aiming at (i) remotely identifying the main bloom-forming phytoplankton species, and (ii) estimating cell numbers during red tides dominated by species such as M. rubrum, L. polyedra, or L. chlorophorum using specific algorithms developed from an hyperspectral library of phytoplankton cultures’ optical properties available at Ifremer and Nantes University. 

The Ph. D. project will be organized as follow: 

Year 1: bibliographic review, implementation of red tide algorithms (Beta version), sampling of bio-optical properties during phytoplankton blooms (spring – summer), samples analysis 

Year 2:  improvement of red tide algorithms, field sampling (spring – summer), samples analysis, processing and validation of satellite-derived phytoplankton products, writing of 1st article 

Year 3: analysis of phytoplankton trajectories, writing of 2nd article and Ph. D. dissertation


For more Information about the topics and the co-financial partner (found by the lab !), contact Directeur de thèse :

Then, prepare a resumé, a recent transcript and a reference letter from your M2 supervisor/ engineering school director and you will be ready to apply online !


Environmental Sciences, Oceanography

Infos pratiques


Mot du recruteur

More details on CNES website :




IHE Delft MSc in Water and Sustainable Development