If you are willing to do simple interpolation,
i.e., ignoring any spatial correlation, you could
look at the interp() function, which is in the
akima package. Even if you need to incorporate
spatial correlation, starting with the interp()
function would probably serve as a good way to
get started learning R. The help page for
interp() has some examples.
Here's an excerpt from the help page for the interp() function:
interp package:akima R Documentation
Gridded Bivariate Interpolation for Irregular Data
Description:
These functions implement bivariate interpolation onto a grid for
irregularly spaced input data. Bilinear or bicubic spline
interpolation is applied using different versions of algorithms
from Akima.
Install the akima package using the R console GUI
(Mac or Windows) or the install.packages()
function (linux).
Then there's the question of coordinate systems.
interp() assumes cartesian coordinates, but
lat/long is not cartesian. If your site is too
large, you shouldn't ignore this, so you will
have to learn how to project from lat/long to UTM
or other appropriate local coordinate system.
For this, I use the spTransform() function in the
rgdal package. Looking on the CRAN website, it
appears there is a Windows binary for rgdal; for
the other platforms (I use Mac), it can be more
challenging. Converting your data into a
"spatial" class object, so that it can be
projected, will be a challenge at first.
Gettng the book that Mark Connolly mentioned would help a lot.
-Don
At 10:20 AM -0700 6/2/10, Thiago Veloso wrote:
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Dear R colleagues!
I´d like to start my participation in this list
by describing my current problem: inside my area
of study I need to compare precipitation data
from two different sources: both station (total
of 86) and a grid (at 8km) of satellite
estimates.
My specific objective is to interpolate the
station data into a regular grid in the same
resolution of the satellite estimates,
preferentially having control of the spatial
domain (lat/lon coordinates). As far as I know
this is the correct way of making such
comparison.
Could anybody please point directions to
perform this task using R? I´m such a beginner
that I don´t even know if
there´s a package designed to create regular
grids from "random" data (interpolating by
kriging or other technique). Usage examples
would be welcomed as well!
Thanks in advance,
Thiago.
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--
--------------------------------------
Don MacQueen
Environmental Protection Department
Lawrence Livermore National Laboratory
Livermore, CA, USA
925-423-1062
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