Dear All, I tried to fit variogram model (spherical, Gaussian, exponential, and linear) to each year data from the same production field. Exponential function seemed to be the best function in each year. I want to assess the stability of the spatial pattern by looking at the correlation of predicted yield values among the year from ordinary kriging. I tried to use option nmax=100 and it works perfectly. This implies I am using local interpolation of 100 observations to predict a value at unknown locations rather than global interpolation approach. I think this is better considering large size of my observation. Now, I find the range of projected spatial coordinates (easting and northing) in meters for each year data from the same field. I intend to probably consider the interpolation grid of 10 meters spacing for each data. Does it make sense? I wish to look at the correlation of predicted yield value among the years obtain from ordinary kriging in other to assess the stability of the spatial pattern quantitatively. Since the spatial location of each yield value varies from one year to the other, I thought of using the interpolation value from block ordinary kriging rather than point ordinary kriging. Please advise me on this. If I am to use block ordinary kriging, how do I modify my script below? The table below shows how the spatial coordinates vary from one year to others in meters within the same production field.
*Easting range (meter)* *Northing range (meter)* years *Min* *Max* *Min* *Max* 2008 299,678 301,298 5,737,285 5,738,128 2009 299,678 301,299 5,737,278 5,738,129 2010 299,678 301,298 5,737,279 5,738,128 2011 299,679 301,298 5,737,279 5,738,123 This is my script ### Create grid for the interpolation (prediction) through ordinary kriging easting.range <- as.integer(range(canmod.sp@coords[,1])) northing.range <-as.integer(range(canmod.sp@coords[,2])) ## now expand to a grid with 100 meter spacing: grd <- expand.grid(x=seq(from=easting.range[1], to=easting.range[2], by=100), y=seq(from=northing.range[1], to=northing.range[2], by=100)) names(grd)<-c("easting","northing") coordinates(grd)<-~easting+northing proj4string(grd)<-CRS("+proj=utm +zone=12 +ellps=WGS84 +datum=WGS84 +units=m +no_defs +towgs84=0,0,0") Pred_ok <- krige(id="yield",yield ~ 1, canmod.sp, newdata = grd, model=exp.mod) Thank you all for your assistance. Moshood [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo