You should conduct a block kriging from the point sparse data to the regular grid (the domain of the satellite images). Try, e.g., gstat
Javier /// > 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. > > > > > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-Geo mailing list > R-sig-Geo@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > _______________________________________________ R-sig-Geo mailing list R-sig-Geo@stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-geo
