Hi Alexandru,
Depends...if you want to make an interpolated map on 8 points, I would
say that 8 points is quite a small amount. A rule of thumb would be
around a minimum of 30 observations. On the upside, I think you have
more than just 8 points because of the temporal dimension. So for
fitting the trend between satellite and ground observations you can use
n_times * 8 observations, assuming that you fit one set of trend
coefficients to the entire dataset. When the coefficients become
variable in time, this number decreases again. When predicting maps per
time step you do only have 8 residuals to base the map on, which is on
the low side.
You could also look at a space-time kriging approach, this allows you to
use information from other time steps to predict the map for the current
timestep. See Heuvelink 2010 for an example of this approach [1].
So lot's of thoughts from my side, but it depends really on your approach.
cheers,
Paul
[1] http://dx.doi.org/10.1111/j.1538-4632.2010.00788.x
On 09/01/2010 07:39 AM, Alexandru Dumitrescu wrote:
Hello everybody,
Is 8 spatial points sufficient to perform a multivariate spatial
interpolation, using as independent variable satellite data, on a monthly
temporal scale? Sample points consist in meteorological data which seams to
be highly correlated with satellite images. The geographical area is the
territory of Romania.
Thank you,
Alexandru
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Department of Physical Geography
Faculty of Geosciences
University of Utrecht
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