Ocean Remote Sensing Synergy summer school #2

Telecom Bretagne, Brest, France
July 6 to 10, 2015

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Overview:

During the last decade, the ocean community witnessed worldwide the launch of over 30 new ocean-related satellite missions. Plans for new satellites, to improve the spatial-temporal sampling, are already laid well into the foreseeable future, and today, we are already talking Petabytes of data to download, analyze, transform into accessible information. Increasing computer power and understandings of relevant physical processes are also rapidly evolving, and contribute to advances in model accuracy and resolution refinement. The different satellite sensors can only be combined to provide the required high spatio-temporal sampling using physically or statistically based merging approaches.

Aim of the summer school:

This year, the Summer School will focus on statistical and Bayesian methods for Ocean Remote Sensing Synergies. Lectures by invited speakers will provide both a broad coverage of statistical tools and models (e.g., geostatistics, regression, machine learning, state-space models) and applications to multi-sensor/multi-tracer ocean sensing data (e.g., data assimilation, missing data interpolation, statistical downscaling,...). Each lecture will comprise a Matlab practical session with applications to multi-sensor ocean remote sensing data, especially satellite-derived Sea Surface Temperature (SST) and Sea Surface Height (SSH).

Invited speakers:

  • Prof. Marc Genton (King Abdullah University of Science and Technology, Saudi Arabia)
  • Dr. Juan Ruiz (University of Buenos Aires, Argentina)
  • Dr. Ying Sun (King Abdullah University of Science and Technology, Saudi Arabia)

Local speakers:

Organizing committee:

       

  Fabrice Collard - René Garello - Pierre Tandeo - Ronan Fablet - Bertrand Chapron