I need to conduct a Landuse classification of New Caledonia. I therefore used the Landsat 8 satelite images of one year and created a multi temporal mosaic by a mean function. As most of the areas were ostly clouded, I used a cloud mask, which resulted in areas of no value. I then tried the focal.median function. However, this led to a change of DN values for the whole image.

I am therefore looking for a function which only tackles the specific areas of no data and leaves the other values untouched.

I was thinking of using Sentinel-1 Radar data, check the radar signature of those areas of my landsat8 image where I have no values, look for the same radar signature at another area, from where I also have a spectral value in my Landsat8 image to then use that value of my Landsat 8 image to fill my missing Landsat8 areas.

Does that make sense? If so, how could I execute that idea? Or is there even any other option?

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.