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I have a Landsat image collection with, additional to the usual bands, the NDWI index (used for water) for each image in that collection.

I would like to create two subsets of this image collection:

  1. one with the upper 25 percent of NDWI index values (75 - 100);
  2. another one with the lower 25 percent of the NDWI index values (0 - 25);

So the result would be three separate image collections (containing all bands). First one containing all images. The second one containing all images selected by the upper 25% NDWI index values. The third one containing all images selected by the lowest 25% NDWI index values.

Please find a toy script at this link: https://code.earthengine.google.com/4bc201244078d5849d033bb7560a3479.

Please note that in that script there is also a quality mosaic. However, I am not satisfied by the quality mosaic because it tends to pick up the extremes. Therefore I would like to work with the lower and upper 25 percent.

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I guess you are looking for reducing the image collection with percentiles. You could either use the percentiles or use interval mean to get the mean of values in a percentile range. Most of the times, the reducer percentile with percentiles between 20-40 works best, as cloud are in the ~ upper 60-100% and shadows in the lower ~0-10% of the image collection pixel values. You will see that in the outcome of the reducer 25 and 75:

// get the original bandNames
var bandNames = l8withNDWI.first().bandNames();

// Use reducer percentiles to get the 25 and 75 
var upper75 = l8withNDWI.reduce(ee.Reducer.percentile([75])).rename(bandNames);
var lower25 = l8withNDWI.reduce(ee.Reducer.percentile([25])).rename(bandNames);

// Or use reduce intervalMean to get the mean of all values between 0-25 or 75-100
var intervalMean0_25 = l8withNDWI.reduce(ee.Reducer.intervalMean(0, 25)).rename(bandNames);
var intervalMean75_100 = l8withNDWI.reduce(ee.Reducer.intervalMean(75, 100)).rename(bandNames);

If you want to slice all the pixel values between percentile 0 and 25, you will need to coop with imageCollection.toArray() and slice out the lower and higher values. But I guess you are looking for a way to make simple and fast composites. That will succeed using these reducer.

Link code

  • Thank you for your useful comment; the code is working properly. However, I'm afraid I'll have to do it with imageCollection.toArray() because I want to calculate the standard statistics (by applying a combined reducer) over both subsets. I want to use the NDWI index as a criterium to dive the collection into two subcollections. Then I would like to calculate descriptive statistics (intv mean, median etc. etc.) by applying a combined reducer. – sir_olf May 13 at 16:37

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