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I am working with Landsat 8 images to create seasonal NDVI images in QGIS.

For all NDVI images I masked the clouds/cloud shadows so there are 4 different NDVI images with different cloud/cloud shadow masks .

How could I create one single NDVI image with mean NDVI values out of the 4 different NDVI images?

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A workaround could be using R scripts in QGIS.

For your specific purpose use this script:

##LayerA = raster
##LayerB = raster
##LayerC = raster
##LayerD = raster
##output = output raster
library(raster)
calc(stack(LayerA, LayerB, LayerC,LayerD), fun = mean, na.rm = T)

enter image description here

And you'll be able to compute NDVI mean taking account No Data pixels (masked pixels).

enter image description here

 Requirements:

Rasters should have the same extent and pixel resolution. You can solve this before with GDAL, SAGA or GRASS tools or add a normalization step in R script.

Notes:

If you stack layers before, you can define only one input file and work with several layers (from 2 to hundreds of layers or even more, depending on the amount of memory required) with minor changes (deleting the others inputs)

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