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For comparison, I want to draw two maps alongside each other. Both maps should use the same color classes/scale. The problem is that the data for the maps is very different: The data for the first map (A) consists of many small spatial units while the data for the second map (B) consists of fewer and larger spatial units but also some outliers with regard to the measured attribute.

Now, how I should determine color classes? If each color class covers the same range (equal intervals) then the outlier of data set B will skew the color scaler, making relevant differences indistinguishable.

If I use jenks intervals or quantiles then the values of data B will be underrepresented because of their smaller number.

What can I do about the problem?

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I don't know if I am missing the point, but maybe you could "normalize" the values?

For Map A, divide all the values you want to represent by the largest value of the dataset. You will get a value between 0 and 1. Then do the same for the Map B dataset.

The values from each map will be between 0 and 1.

  • Possible, but this would alter the scales and make the maps hardly comparable. – Julian Mar 12 '17 at 11:23

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