Skip to Main content Skip to Navigation
Theses

Télédétection du phytoplancton par méthode neuronale : du global au régional, de la composition pigmentaire aux biorégions

Abstract : This thesis presents a novel approach to analyze and observe the phytoplankton community structure at global and regional scale using satellite data (Ocean colour and Sea surface temperature) and in-situ observations. The approach is based on neural network classification methods, such as Self-Organizing Maps (SOM) trained on a large global database composed of satellite observations collocated with in-situ measurements. First, we developed a method to estimate secondary phytoplankton pigments from satellite measurements in the global ocean. Then we focused our studies on the Mediterranean Sea. Phytoplankton groups (PFTs) were identified from the secondary pigments estimated in the first phase. We then characterized seven bio-regions by clustering annual cycles MLD obtained from Argo floats, SST and Chla by using an advanced SOM. At last, these bio-regions were characterized in terms of PFTs. The methods developed in this thesis allowed us to estimate uncertainties on secondary pigments and PFTs. The applicability of these methods are broad and can be used to investigate other oceanic areas.
Complete list of metadatas

Cited literature [236 references]  Display  Hide  Download

https://tel.archives-ouvertes.fr/tel-02562426
Contributor : Abes Star :  Contact
Submitted on : Friday, November 20, 2020 - 12:02:08 PM
Last modification on : Friday, November 27, 2020 - 3:29:06 AM

File

EL_HOURANY_Roy_2019.pdf
Version validated by the jury (STAR)

Identifiers

  • HAL Id : tel-02562426, version 2

Collections

Citation

Roy El Hourany. Télédétection du phytoplancton par méthode neuronale : du global au régional, de la composition pigmentaire aux biorégions. Biodiversité et Ecologie. Sorbonne Université, 2019. Français. ⟨NNT : 2019SORUS095⟩. ⟨tel-02562426v2⟩

Share

Metrics

Record views

81

Files downloads

10