Hi Mary, This might help answer your questions. I used the meuse dataset and converted to raster formats, but I think the general approach should work for what you want to do.
library(raster) library(gstat) data(meuse.grid) coordinates(meuse.grid) = ~x+y gridded(meuse.grid) = TRUE class(meuse.grid) m2 <- as(meuse.grid, "SpatialGridDataFrame") m3 <- raster(m2, layer = "soil") # Convert soil classes to raster > > Question1. > How can i remove the ninth class in R because it does not have to be included > in > geostatical analysis. m4 <- m3 * ((m3 < 3) / (m3 < 3)) # Removes class 3 from soil, converts it to NA values (this could also # serve as a mask) # If you want to keep that part of the grid in the analysis, then you might want to collapse the one class # into another m5 <- (m3 == 3 | m3 == 2) * 2 + (m3 == 1) # Class 2 now includes 2 and 3 > Question 2 > how can i use the map created in Q1 to clip the other 5 aboventioned maps (eg > DEM etc) or how can i create a mask from the map in Q1. > # Create a mask for just the area of soil class 1 sc1.mask <- (m3 == 1) / (m3 == 1) # You then multiply your other rasters by your mask to reduce rasters to the areas you want to analyze. Cheers, Lyndon _______________________________________________ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
