Micha wrote: > From my understanding, r.in.xyz is best suited for cases > where you have a very high density of x-y values (i.e. lidar > data) and you want to create a raster where each cell will > contain several of the original points. You can then > choose to average all point values (or max, min, etc) to > create the final cell value.
r.in.xyz is also good if your input data coords are already in a grid, as if you set the region bounds correctly it can replicate that grid and therefore the input data *exactly*. > 1- You want the final raster at the same or larger > resolution as the original points, and ie r.in.xyz and r.resamp.stats are good at aggregating data, v.surf.rst and r.resamp.interp are good at interpolating data. > 2- You have at least one point value for *every* target > raster cell. (Other wise you'll end up with cells with value > '0') only for the "n" count map (which is great for checking that r.in.xyz is doing what you meant). for other methods cells with no-data are filled with NULL, not 0. (as you might hope for something like minimum!) regards, Hamish _______________________________________________ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user
