Hi all, This question goes mainly for Hanlie, but everyone is welcome..
I'm thinking on doing some similar to you, Hanlie, comparing satellite information vs rain gauges. But I had the following doubt: Do you need to change the projection of the satellite information to match the projection of the rain gauges georeferenced localization? I see that you are assuming 28 sq. km grid, but depending on the latitude that you are, it can be a different surface, right? On Aug 15, 12:27 pm, Andy Wilson <[email protected]> wrote: > If you calculate Thiessen polygons for your 6 gauges and clip them to your > grid cell boundary then you'll be able to see how much each gauge would > contribute to the interpolated mean grid cell value. So you can just use the > areas of the polygons as weights for a weighted mean, and that should come > out the same as interpolating and then aggregating. If the position of the > gauges doesn't change, then the weights don't change so you only have to do > that once. Then you just apply your weighted mean function 730 times. > > Does that make sense or did I misunderstand something? > > On Mon, Aug 15, 2011 at 2:03 AM, Hanlie Pretorius < > > > > > > > > [email protected]> wrote: > > Hi, > > > I have rainfall measurements from 6 gauges that I want to interpolate > > to an areal value (a 'surface'), so that I can compare the > > interpolated gauge values to a satellite rainfall estimate that covers > > a grid cell of 28kmx28km. Two of the gauges are outside, but close to > > the border of the grid cell. Therefore, I also need to clip the > > interpolated surface to the grid cell and to get the average of the > > surface value in this clipped surface. > > > However, for each rain gauge I have 730 values representing a daily > > measurement over two years. As output, I need a text file > > with the interpolated rainfall values for each day in my time series. > > So, I was wondering if there is an 'easy' way to get my output without > > creating 730 GIS layers? > > > Regards > > Hanlie
