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Gap Filling of Biophysical Parameter Time Series with Multi-Output Gaussian Processes
In this work we evaluate multi-output (MO) Gaussian Process (GP) models based on the linear model of coregionalization (LMC) for estimation of biophysical parameter variables under a gap filling setup.
Physics-Aware Gaussian Processes in Remote Sensing
However, GPs are typically used for inverse modeling based on concurrent observations and in situ measurements only.
Mapping Leaf Area Index with a Smartphone and Gaussian Processes
We show the first LAI maps obtained with ground data from a smartphone combined with advanced machine learning.
Joint Gaussian Processes for Biophysical Parameter Retrieval
Radiative transfer models (RTMs) represent mathematically the physical laws which govern the phenomena in remote sensing applications (forward models).
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