When I import my image into ArcGIS Desktop I get a black border around the region that didn't exist before in Google Earth Engine (GEE).

How can I prevent GEE from doing this when I export an image?

enter image description here

  • Set whatever value the black is to the color white. Border gone.
    – Jon
    Oct 9, 2018 at 19:25
  • @Jon thanks for the answer, but the issue with that is the border isn't noData, it's been assigned to class 0. It causes issues with my analysis. I need to find a way to prevent GEE from exporting the border all-together. Oct 9, 2018 at 19:32
  • Export the image as a float and the masked pixels should be nodata. Apparently that's not an option for int-type exports.
    – Jon
    Oct 9, 2018 at 19:48
  • Alternatively set the metadata of the Geotiff accordingly NoData Value = 0 and your GIS software will then interpret all 0 value pixels as No Data.
    – Kersten
    Oct 10, 2018 at 7:50
  • @Kersten that's basically what I said to do within GIS, but apparently there are legitimate zero values within the non-masked region :/
    – Jon
    Oct 10, 2018 at 13:55

1 Answer 1


I'm not sure why GEE adds a black border to exported images, I think it's something to do with the re-orienting the image to the new projection system and cannot be changed. This isn't an issue if you're exporting a satellite image raster, as it sets the border pixel values to class 0 and this doesn't interfere with the pixels in the rest of the image.

It's a bit of a pain when exporting a classified image that contains useful pixels that are classified as zero as this messes with the analysis. Anyway, I managed to figure it out with a simple .remap code. I just reassigned the values from class 0 onwards to the integer above, thus leaving class 0 free for noData pixels. Here is the code:

// Classified image with 5 classes (from cluster analysis)
var classified_image = cluster.cluster(clusterer);

// remap values in class to integer above so class 0 becomes free for noData pixels   
var remap = ee.Image(classified_image)
 .remap([0,1,2,3,4], [1,2,3,4,5]);


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