![](bg6.png)
benefits most by adding spatial information compared
to the baseline method. As a possible extension to
the proposed method, the square-root transform of the
dependent variable can be incorporated into the Gaus-
sian process model, but this idea requires further stud-
ies since it involves designing a non-stationary covari-
ance function.
ACKNOWLEDGEMENTS
This work was supported by NSF Grants IIS-0705815
and IIS-0612149.
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PREDICTING GROUND-BASED AEROSOL OPTICAL DEPTH WITH SATELLITE IMAGES VIA GAUSSIAN
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