Apply r.neighbours or Neighbourhood analysis (LecoS plugin for QGIS) to 3000 rasters

Question

I need to apply r.neighbours or Neighbourhood analysis (QGIS plugin LecoS (or equivalent) to 3000 rasters and define a neighbourhood of 5 x 5 and calculate the mean.

I suppose I need to create a script with a loop that goes through the raster files and applies the same analysis settings. Unfortunately I only know how to program in R. So I'm asking if anyone can show me how to create a script that does this.

I use QGIS and I would prefer to do this using the QGIS Processing Framework. But GRASS GIS or SAGA GIS are also OK for me.

Thanks in advance

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EDIT: This how I did it on Ubuntu 12.04. Thanks @Curlew.

I created GRASS Location/Mapstet and batch imported the 3000 rasters using "Common formats import (r.in.gdal)" to the mapset (I recommend deactivating the option "add to layer tree"). I used one of the rasters for setting the region (g.region).

Then I opened R, set the workspace to the folder where the rasters are stored and run this:

library(raster)
library(spgrass6)
initGRASS(gisBase = "/usr/lib/grass64", home = tempdir(), gisDbase = "/path/to/gis/data/directory", location = "Location", mapset = "Mapset", override = TRUE) #Initate the previously created Location/Mapset

ls <- lapply(list.files(".","*.tif"),FUN=raster) # Import all raster to the list "ls"

for(i in seq_along(ls)){
execGRASS("r.neighbors", input=names(ls[[i]]),size=5,output="teste",flags=c("overwrite"))
execGRASS("r.out.gdal", input="teste",output=paste(paste("/path/to/output/folder",sep="",names(ls[[i]])),sep="",".tif"))
}

This solves my problem, but I'm still curious about how the equivalent Python code for QGIS Processing looks like.

Answer 1

Just quick, as i don't have the time to code sth. for you. You know that you can call GRASS and also SAGA modules in R?
For GRASS: spgrass6
For SAGA: RSAGA

Then you just read in all the files you need and build a loop to calculate the needed statistics.

library(raster)
library(RSAGA)
library(spgrass6)
ls <- lapply(list.files(".","*.tif"),FUN=raster)

for(i in ls){
  res <- doGRASS("r.neighbors") # like that
  res <- RSAGA::rsaga.filter.simple() # or that
  # you could write the result to a new file or use assign to save it as variable
}

However i would suggest to learn a bit python.