I have extensive experience with remote sensing data processing and analysis, involving imaging spectroscopy, multispectral time series, LiDAR data and various optical data acquired from leaf scale (field spectrometry, close-range imaging spectroscopy) to satellite platforms. My research is based on two types of approaches :
i) Physically-based approaches using radiative transfer modeling (PROSPECT, SAIL, DART)
to help understand and interpret interactions between terrestrial ecosystems and remotely sensed
radiometric signal.
ii) Data-driven approaches (machine learning), in order to develop methodologies for classification / regression tasks, and estimation of ecological metrics (including tropical biodiversity) and biophysical properties of vegetation, taking advantage of spatial information and high-dimensionality
data.
I am particularly interested in exploring the complementarity between these two approaches.