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Due to the necessity that I have to process the model in specific CRS (EPSG:3006), I try to reproject the ImageCollection after calculating all the vegetation indices I need. I use the code below to reproject that whole imagecollection so that I can continue the further analysis.

var res2L2017c_Veg = s2L2017c_Veg.reduceRegion({
  reducer: ee.Reducer.median(),
  geometry: ROI,
  scale: 10,  // meters
  crs: 'EPSG:3006',  //sweref99 tm
});
print(res2L2017c_Veg)

However, it shows the error:

Dictionary (Error) Image.reduceRegion: Too many pixels in the region. Found 41709676124, but maxPixels allows only 10000000. Ensure that you are not aggregating at a higher resolution than you intended; that is a frequent cause of this error. If not, then you may set the 'maxPixels' argument to a limit suitable for your computation; set 'bestEffort' to true to aggregate at whatever scale results in 'maxPixels' total pixels; or both.

Does it mean that it exceeds the computation affordability of GEE? How should I correct this error?

This is the link to my code: https://code.earthengine.google.com/6a40e656de80a79aa4308c97f313b756

This is the geometry "ROI": https://code.earthengine.google.com/?asset=projects/ee-sweden2023study/assets/ROI

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1 Answer 1

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As the error message informs, the issue is with the maxPixels value. You can simply add it as an argument increasing the maxPixels allowed:

var res2L2017c_Veg = s2L2017c_Veg.reduceRegion({
  reducer: ee.Reducer.median(),
  geometry: largearea,
  scale: 10,  // meters
  crs: 'EPSG:3006',  //sweref99 tm
  maxPixels: 41709676125
});

It will take time and it could run out of memory since the area is huge

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    Adding to this: If it still runs out of memory with the maxPixels set to max then you'll either have to reduce the size of your area or increase the scale
    – M. Nicolas
    Apr 13 at 19:29
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    Exactly, thanks for the addition. Scale equal to 10 is too detailed for this area
    – aldo_tapia
    Apr 13 at 19:34
  • Thank you! I have tried but it showed "Computation timed out." maybe it's due to the large area and high resolution I assigned. According to the suggestions from GEE (developers.google.com/earth-engine/guides/debugging), I should reproject while exporting, which means I cannot conduct further analysis with this CRS. Am I correct?
    – Lin Annie
    Apr 13 at 19:59
  • Thank you! I just saw your comments. I'm afraid the study area is fixed and the scale is also required to be as detailed as possible. If I skip this part and convert my CRS of other data (training dataset) to the GEE default one, which means I don't do any reprojection to this imagecollection. Would it be better?
    – Lin Annie
    Apr 13 at 20:06
  • 1
    Actually using a scale of 1000, the computation is super fast. If you can't reduce the scale, split the area into smaller polygons and then you can aggregate statistics weighted by area
    – aldo_tapia
    Apr 13 at 22:13

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