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I have a set of raster images (GeoTIFF, Landsat 1984-2018) which I cropped with my AOI using a shapefile.

Now I want to stack them and calculate the mean and standard deviation of every pixel of the stacked images (in space and time). How can I stack them and calculate the mean and standard deviation? For the outputfile I need one image for the mean and one for the standard deviation.

library(raster) library(rgdal)

#load data

setwd("C:/Users/cathe/Documents/GEOTIFF_offsetcorrected") dbase = "C:/Users/cathe/Documents/GEOTIFF_offsetcorrected"

#polygon with crop-extend

shape_data <- readOGR("C:/Users/cathe/OneDrive/Documents/ArcGIS/Projects/Cologne/WGS_1984_UTM_Zone_32N/Cologne.shp", stringsAsFactors=FALSE)

#load tif files

ALL_FILES <- list.files(path = dbase, pattern = ".tif$|.TIF$")

#output

outfiles = file.path("C:/Users/cathe/Documents/Output", paste0(basename(tools::file_path_sans_ext(ALL_FILES)), ".tif")) #crop

for (i in seq_along(ALL_FILES)) { r = crop(stack(ALL_FILES[i]), shape_data) writeRaster(r, filename=outfiles[i], bylayer=FALSE, format="GTiff", datatype= "INT1U", options="COMPRESS=ZIP", overwrite=TRUE) }

mean <- mean(r)

plot(mean)

writeRaster(x = mean, filename = "mean1.tif", driver = "GeoTiff", overwrite=TRUE)

I get a result, but i am not sure if it is correct?

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