I am new to working with spatial data in R and I have run into a few issues, that I was hoping the community could help me with. Here is the situation: I generated a raster file of a country with a range of probabilities. Within that country, I have state-level data - # of farms. My goal is to randomly seed a certain number of points (farms) (# of farms is stored in CSV file, “Table2”) in each state of the country, based on the probability, indicated in the raster file. As such, I clipped my raster probability file up into 16 different raster files (the number of states in this country).

I have my code written, for what I describe above. But this code needs to be performed over each of the 16 layers - the ‘ncells’ and “TotalFarm’ value needs to be updated for each file.

install.packages("raster")
install.packages("sp")
install.packages("rgdal")

setwd("~XXXXXX”) r <- raster("Suitability_Prob_v30.tif") Reading in 16 rasters
r_31 <- raster("Suitability_Prob_v31.tif") r_32 <- raster("Suitability_Prob_v32.tif") r_33 <- raster("Suitability_Prob_v33.tif") r_34 <- raster("Suitability_Prob_v34.tif") r_35 <- raster("Suitability_Prob_v35.tif") r_36 <- raster("Suitability_Prob_v36.tif") r_37 <- raster("Suitability_Prob_v37.tif") r_38 <- raster("Suitability_Prob_v38.tif") r_39 <- raster("Suitability_Prob_v39.tif") r_310 <- raster("Suitability_Prob_v310.tif") r_311 <- raster("Suitability_Prob_v311.tif") r_312 <- raster("Suitability_Prob_v31.tif") r_313 <- raster("Suitability_Prob_v313.tif") r_314 <- raster("Suitability_Prob_v314.tif") r_315 <- raster("Suitability_Prob_v315.tif")

TABLE2 <- read.csv(file=“XXXXX”, header=TRUE, sep=",") Read in cvs that has farm #'s

Here performing ONLY on the first of the 16 raster files Set NAs to 0
r[==-3.402823e+38] <- NA r[is.na(r)]=0

Calculating number of cells
ncells<-dim(r)[1]*dim(r)[2] ncells Calling in the # of farms for this state, stored in CSV TotalFarm<-sum(TABLE2[,'X30']) TotalFarm

For point selection, set number of cells (ncells) and the number of points to be selected, (specific to each state) Weighted by the value in the cells: ptscell = sample(ncells, TotalFarm, prob=r[], replace=TRUE)

Distribute the points throughout the grid cells Get the cell half-width: hs = res(r)/2 Now find the center of those points: centers = xyFromCell(r,ptscell) Generate random uniform points in the cell by using the center and the half-width/height pts = cbind(runif(nrow(centers),centers[,1]-hs[1],centers[,1]+hs[1]), runif(nrow(centers),centers[,2]-hs[2],centers[,2]+hs[2])) Print and finish: plot(r) points(pts) print(pts) write.csv(pts, file = "Points_5.txt",row.names=FALSE)

My attempts to apply this code over the series of 16 states has failed, in part, because I cannot get my 16 raster files into a “raster object” that allows me to use the rasters individually with those changes. Specifically, I made a mosaic image out of the 16 rasters , however the changes that I made on the mosaic were not made on the original raster files (only on the new mosaic object), so when I need to go back and seed the files individually with the number of farms specific to each state, the modifications that I do to the mosaic, i.e. NA’s, are not there.

All of the tutorials that I have seen perform loops on rasters by building a brick or stack. But since these are not bands which have similar extents, rather, they are neighboring states, this approach is not appropriate here.

So, how do I perform a loop on rasters, that are in the “raster” class or otherwise apply the code written above, to each raster automatically?