Water detection for the SWOT mission (2014 - 2017)


To obtain a better coverage both spatially and temporally, hydrologists use spaceborne data in addition to data acquired in situ. Resulting from a collaboration between NASA’s Jet Propulsion Laboratory (JPL) and the French Space Agency (CNES), the upcoming SWOT mission will provide global continental water elevation measures using Synthetic Aperture Radar (SAR) interferometry. In this project, we addressed the problem of water detection in SWOT amplitude images, which is to be performed before the interferometric processing. To this end, we propose to use a method dedicated to the detection of large water bodies and a specific algorithm for the detection of narrow rivers. The first method is based on Markov Random Fields (MRF). The classification is regularized and the class parameters, which cannot be assumed constant in the case of SWOT, are jointly estimated. The second method is based on segment detection at the pixel level, completed by a connection step.

This project was the main topic of my PHD.


As a PhD student on this project, I was supervised by:

  • Florence Tupin
  • Roger Fjørtoft
  • Loïc Denis

I also had collaborations with:

  • Victor Poughon
  • Manuel Grizonnet
  • Damien Desroches
  • Lucie Labat