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Active Learning Methods for Efficient Hybrid Biophysical Variable Retrieval
Kernel-based machine learning regression algorithms (MLRAs) are potentially powerful methods for being implemented into operational biophysical variable retrieval schemes.
Spectral band selection for vegetation properties retrieval using Gaussian processes regression
GPR-BAT allows (1) to identify the most informative bands in relating spectral data to a biophysical variable, and (2) to find the least number of bands that preserve optimized accurate predictions.
Emulation as an Accurate Alternative to Interpolation in Sampling Radiative Transfer Codes
Computationally expensive Radiative Transfer Models (RTMs) are widely used} to realistically reproduce the light interaction with the Earth surface and atmosphere.
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