Jean-Baptiste FERET

I am a Research Associate in remote sensing of vegetation at INRAE as a permanent member of the [TETIS](https://www.umr-tetis.fr/index.php/fr/) laboratory based in Montpellier (south of France). My lab is hosted at the Maison de la Teledetection. Prior to joining INRAE, I worked as a Postdoctoral Research Associate for the Carnegie Institution for Science at the department of Global Ecology in the Asner lab (Stanford, USA). I hold a PhD in Environmental Sciences, and an eninering degree in agronomy from Montpellier Supagro. My research focuses on remote sensing data processing and analysis, and methodological development for applications in ecology and environmental monitoring, and a bit of agronomy. I am interested in developing new methods contributing to the estimation of different components of biodiversity (see EBVs), and for the estimation of vegetation biophysical properties. These methodological developments involve imaging spectroscopy, multispectral images and time series, LiDAR data and various optical data acquired from leaf scale (field spectroscopy, close-range imaging spectroscopy) to satellite platforms. My research is based on two types of approaches : - Physically-based approaches using radiative transfer modeling ([PROSPECT](https://jbferet.gitlab.io/prospect/), [SAIL](https://jbferet.gitlab.io/prosail/), DART) to help understand and interpret interactions between terrestrial ecosystems and remotely sensed radiometric signal. - Data-driven approaches (including machine learning), in order to develop methodologies for classification / regression tasks, and for the estimation of ecological metrics (with a particular interest for tropical biodiversity) and biophysical properties of vegetation, taking advantage of spatial information and high-dimensionality data (spectrally and temporally). I am particularly interested in exploring the complementarity between these two approaches.