[splittingTimes]

IBM did research back in the 90s on perceptually-based colormaps and how to best represent various types of data within the color dimensions of luminescence, saturation and hue [1]. For example, they found that,

(1) Hue was not a good dimension for encoding magnitude information, i.e. rainbow color maps are bad.

(2) The mechanisms in human vision responsible for high spatial frequency information processing are luminance channels. If the data to be represented have high spatial frequency, use a color map which has a strong luminance variation across the data range.

(3) For interval and ratio data, both luminance- and saturation-varying color maps should produce the effect of having equal steps in data value correspond to equal perceptual steps, but the first will be most effective for high spatial frequency data variations and the second will be most effective for low spatial frequency variations.

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[1] the original link got removed from IBMs website. Back in the day it was under

https://www.research.ibm.com/people/l/lloydt/color/color.HTM

A pdf copy is here:

https://github.com/frankMilde/interesting-reads/blob/master/...

[Daub]

> (1) Hue was not a good dimension for encoding magnitude information, i.e. rainbow color maps are bad.

This is very good advice. Generally, hue expresses difference in kind whilst lightness and saturation expresses difference in degree. This is beautifully demonstrated in Nault's study of how children read maps.

Nault, W.H.: Children’s Map Reading Abilities. Geographic Society of Chicago, Newsletter, III (1967)

[RugnirViking]

Is there any online fulltext link to that? It's pretty weird you used the exact same reference with the exact same format as your own earlier comment in this 2021 submission https://news.ycombinator.com/item?id=26489887

the study sounds interesting though