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(MCs) for civilian ships or military vessels requires robust and efficient in-situ waves-based Structural Health Monitoring (SHM) algorithms to monitor them throughout their lifetime in a harsh
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selectivity is the first important barrier to overcome in order to perform quantitative analyses for each pollutant and avoid ionic interference between the different sensors used in the project. Sensor
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different institutions (CNES, CNRS, IRD, UT3). This position is part of the continuous scientific support to the ESA BIOMASS mission, contributing to the development and validation of higher-level forest
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at different spatial scales. Although significant progress has been made in understanding and predicting urban microclimates, the implications of atmospheric dynamics in heterogeneous environments remain
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-criteria, defining their formalization as fuzzy subsets, and characterizing their uncertainty; Integrating Machine Learning algorithms to better account for low-level sensor data (precipitation, wind-driven