raster

If have three rasters(as matrix): r1 <- raster(nrows=10, ncols=10); r1 <- setValues(r1, 1:ncell(r1)) r16 <- raster(nrows=10, ncols=10);r16 <- setValues(r16, 1:ncell(r16)) r30 <- raster(nrows=10, ncols=10);r30 <- setValues(r30, 1:ncell(r30)) I would like to linearly interpolate r1,c16,c30 to find the values in between i.e. r2,r3,r4,......r15 then r17,r18,r19,..........r29 . Is this possible using R? Robert Hijmans Here is a way to do that library(raster) r <- raster(nrows=10, ncols=10); values(r) <- NA x <- sapply(1:30, function(...) r) x[[1]] <- setValues(r, runif(ncell(r))) x[[16]] <-

With the R base plot, I can plot any geotiff with the following command: library("raster") plot(raster("geo.tiff")) For example, downloading this data, I would do the follwing: setwd("C:/download") # same folder as the ZIP-File map <- raster("smr25musterdaten/SMR_25/SMR_25KOMB_508dpi_LZW/SMR25_LV03_KOMB_Mosaic.tif") How do you Plot GeoTif Files in ggplot2? EDIT: 1: I've replaced the greyscale map from the sample files with a coloured map to ilustrate the problem of the missing colortable. 2: With the help of Pascals answer, I was able to adapt and improve this solution and make it more dynamic

I have a matrix data with spatial coordinates and one variable. The spatial resolution is 1000 meters. > str(dat1) > List of 3 > $ x: num [1:710] 302340 303340 304340 305340 306340 ... > $ y: num [1:1241] 5431470 5432470 5433470 5434470 5435470 ... > $ z: num [1:710, 1:1241] 225 225 225 225 225 ... I want to convert it into raster format. > dat1$x[1:10] > [1] 302339.6 303339.6 304339.6 305339.6 306339.6 307339.6 308339.6 309339.6 310339.6 311339.6 > dat1$y[1:10] > [1] 5431470 5432470 5433470 5434470 5435470 5436470 5437470 5438470 5439470 5440470 I used the following code to do it. But the

I am processing a time series of rasters (modis ndvi imagery) to calculate average and st.deviation of the series. Each yearly series is composed of 23 ndvi.tif images, each of 508Mb, so total is a big 11Gb to process. Below is the script for one year. I have to repeat this for a number of years. library(raster) library("rgeos") filesndvi <- list.files(, pattern="NDVI.tif",full.names=TRUE) filesetndvi10 <- stack(filesndvi) names(filesetndvi10) avgndvi10<-mean(filesetndvi10) desviondvi10 <- filesetndvi10 - avgndvi10 sumdesvioc <-sum(desviondvi10^2) varndvi10 <- sumdesvioc/nlayers(filesetndvi10)

I am trying to plot a map with positive and negative values. All positive values should have red color while negative should have blue color and zero should have white just like in this sample plot with discrete colors Below is the code I'm using: library (rasterVis) ras1 <- raster(nrow=10,ncol=10) set.seed(1) ras1[] <- rchisq(df=10,n=10*10) ras2=ras1*(-1)/2 s <- stack(ras1,ras2) levelplot(s,par.settings=RdBuTheme()) Thanks very much for providing a general solution which can be applied in other mapping exercises as well. jbaums I wrote a gist to do this. It takes a trellis object generated by