Hello,
what methodes are recommended to use within GRASS to calibrate a map
with by using geostatistical methods?
OK, normally the method depends on the kind of data. Therefore I may
give an example:
I have long-term meteorological mesurement data (timeseries aggregated
to monthly frequency) from the climate data logging stations in a
region. The components are temperature, humidity, wind speed and
direction as well as precipitation. These are imported by v.in.ascii and
interpolated into a map. This data may come from a third-party source
or be obtained by remote sensing.
Since it is difficult to obtain reliable data I put my own three
stations out in the field at critical points where I have the most
doubts about the data. I conduct two years of measurements.
How to I update my interpolated map with the new values obtained from
the three stations?
Of course, I can just update the corresponding z values of xyz-vector
(externally in OOo Calc or by scripting) and then interpolate again.
Or update all values of the input data according to a calculated
deviation from the longterm value.
But...
* is there any tool or workflow that could facilitate this?
* is there any article or report that describes doing such a procedure
using
GRASS?
I am just asking for ideas and experineces.
Thanks in advance for any hints or pointers.
I think that this is related to the recent question:
Thin plate spline for climate point record interpollation?
http://permalink.gmane.org/gmane.comp.gis.grass.user/24940
Kind regards,
Timmie
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