Recent work from Megan Henriksen and the LROC team is improving their color-shaded relief and slope maps, see New Dynamically Generated Color-shaded Reliefs For Narrow Angle Camera Digital Terrain Models.
@thare pointed out that although it’s a major step away from the traditional rainbow color ramp (see NASA please no rainbows, troubles with rainbows or a dangerous rainbow), we can question the use of divergent color ramps for topography, especially for people with Color Vision Deficiency (CVD).
- Quote: “A divergent colormap is used to compare data values to a reference value in a way that visually highlights whether values are above or below the reference.” [ref].
- Topography generally doesn’t have that reference (even including sea-level for Earth).
We propose to produce and test different color ramps, including:
Just to expand on Trent’s point about divergent color ramps and topography:
The issue is not so much that divergent color ramps are intrinsically bad for people with CVD. There are several CVD-safe divergent ramps available. Divergent color ramps are just more appropriate when the intention is to draw attention to divergence from some critical value. The classic application for divergent ramps is temperature difference maps: Use a Red-Blue color ramp with white in the middle to show positive (usually blue) and negative (usually red) deviations from an average value (white).
For topography, it is more appropriate to use a color ramp whose apparent lightness changes monotonically and (with a few exceptions) linearly.
I encourage folks to read Rob Simmon’s 6-part series “Subtleties of Color” to gain a better understanding of basic color theory and how to apply it to geospatial data. Part 1 is available here:
Matplotlib has done a good review of their colors for version 2, and there is some nice material – also about customizing palette --, here are some references to the discussion: