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combining space-based remote sensing and modeling, it aims to better understand the evolution of forest fuels and their role in fire propagation. Tested on pilot forest areas (Centre-Val de Loire and Pyrénées
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in the use and exploitation of high spatial and temporal resolution remote sensing data. An interest in causal discovery and inference is more than welcome. The candidate will be required to interact
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combining space-based remote sensing and modeling, it aims to better understand the evolution of forest fuels and their role in fire propagation. Tested on pilot forest areas (Centre-Val de Loire and Pyrénées
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algorithm development and satellite remote sensing • Good written and spoken English • Ability to work independently as well as in a team • Proficiency in programming languages (e.g. Python, R, Fortran
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Eligibility criteria . PhD in atmospheric sciences • Knowledge of cloud physics • Experience in algorithm development and satellite remote sensing • Good written and spoken English • Ability to work
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for calibrating remote sensing instruments and validating national and regional aerial biomass maps. The One Forest Vision initiative (OFVi project, https://www.oneforestvision.org/eng ) has enabled the creation