Hi!
I have a series of satellite images of the same region
over a time series. In some cases, there are gaps due
to cloud cover, which are interpolated linearly with
time (i.e., the missing value is interpolated based on
the previous and next values for that location). In
other words, the interpolation is purely made in time,
which sort of works for small temporal spans, but I
would like to have a more robust approach, whereby the
geospatial properties of the images (as well as the
temporal) are also taken into account. Can anyone
recommend any "summer reading" on this?
Thanks
Jose
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