Gap Filling of Biophysical Parameter Time Series with Multi-Output Gaussian Processes
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Gap Filling of Biophysical Parameter Time Series with Multi-Output Gaussian Processes

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Gap Filling of Biophysical Parameter Time Series with Multi-Output Gaussian Processes

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Mateo-Sanchis, Anna; Muñoz Marí, Jordi; Campos Taberner, Manuel; García Haro, Francisco Javier; Camps Valls, Gustavo
This document is a conferenciaDate2018
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. In particular, we focus on LAI and fAPAR over rice areas. We show how this problem cannot be solved with standard single-output (SO) GP models, and how the proposed MO-GP models are able to successfully predict these variables even in high missing data regimes, by implicitly performing an across-domain information transfer.

    A. Mateo-Sanchis, J. Muñoz-Marí, M. Campos-Taberner, J. García-Haro and G. Camps-Valls, "Gap Filling of Biophysical Parameter Time Series with Multi-Output Gaussian Processes," IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, 2018, pp. 4039-4042, doi: 10.1109/IGARSS.2018.8519254.
https://doi.org/10.1109/IGARSS.2018.8519254

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