I am a physicist with a PhD about the modeling of radiative transfer in
the vegetation and retrieval of vegetation biophysical parameters from
remotely sensed data.
After this first theoretical and mathematical introduction to remote sensing,
I decided to turn my career toward the application of remote sensing, especially for
monitoring the environment at global scale
Informatics
My favorite tools for processing geo-data are gdal, bash and python
on Linux stations.
Combining those three on a linux machine let's me do almost anything
I like in an elegant way. I also like written code in C/C++ using STL.
For years, I also developped codes in fortran, ENVI/IDL, matlab, pv-wave, ...
the long list of software used in research!
I even found myself writting assembly code on my Z80, back in the the 80'!
These times, I am experimenting with Objective C/Cocoa (mac os X
programming language, if you had any doubt). Hopefully, some goodies to download
soon...
Work record
2010 to now:
Independent consultant. Feel free to contact me if you are looking for some expertise!
2004 to 2010:
Remote sensing expert. Development of satellite imagery
processing algorithms for monitoring the environment (vegetation, crops,
fires, surface water, potential fishing zones, ...) in Africa.
I developed there a data processing system (eStation), reading
Eumetcast data and automatically updating its database of environment indicator.
This system is installed in all sub-Saharan countries and maintained
by the European Union (projects AMESD and MESA).
2002 to 2004:
Research engineer, remote sensing expert, in a former subsidiary
of CNES. Leading agriculture and environment assessment projects.
Development of a SPOT/HRV (high resolution) processing chain for
assessing crops productivity.
2000 to 2001:
2 years postdoc at INRA (French National Agronomy Institute):
developping algorithms for assessing crops biophysical properties from hyperspectral data.
1998 to 1999:
PhD at LaMP (Laboratoire de Meteorologie Physique, France):
modeling radiative transfer in the canopy; analysis of the
best conditions of observation for retrieving the plant stand biophysical parameters.