A Cartographer Who’s Transforming Map Design

Some of her earlier papers can be found here: http://www.personal.psu.edu/cab38/Pub_scans/Brewer_pubs.html

Here's the ColorBrewer tool: http://colorbrewer2.org/

I never thought about what a PhD in cartography would look like. Nice to learn more about the thought being put into maps.

Here is the popular Color Brewer implementation in R. https://cran.r-project.org/web/packages/RColorBrewer/index.h...

A tutorial on how to implement RColorBrewer in R. http://www.compbiome.com/2010/12/r-using-rcolorbrewer-to-col...

Here's the blog post about how her work has influenced Esri's ArcGIS software: http://blogs.esri.com/esri/arcgis/2014/11/12/brewing-a-new-c...

I sit a few buildings down from Cindy's office and have also been studying colormaps quite a bit in the last 3 years. Its interesting how many plotting packages get this wrong but are finally catching up.

I switched from Matlab to Python years ago and was sad to see pyplot using the default rainbow palette still. However, there was some good work done by Chris Beaumont to improve the plot quality. See: http://plotornot.chrisbeaumont.org/ You can easily import these styles into matplotlib using rcparams.

Matlab is using a roughly perceptually linearly luminant colormap they call Parula now. Good job Matlab.

Paulo Penteado has also done some good work in this area. See: http://www.ppenteado.net/ast/csbc2012_pfp_2_pres.pdf

I want to talk about the Luv Lab colorspace. There are several places on the net (even in the literature) that are wrong about these colorspaces saying Lab is for emissive displays and Luv is for reflected light. This is actually not true. (If anything it is reversed). See: https://groups.google.com/d/msg/scikit-image/DIRaSXJoEes/2jD... and Berns reference.

The interesting with colorspaces (and colormaps thereof) is that working in a perceptual space like Luv/Lab is yields a non-linear (and non-convex) gamut in the sRGB space used by most monitors. There is more "headroom" in the magenta hue of colors than say green. However, you have to then look at monitor output as a function of hue and human sensitivity -- with a red object and blue object with the same reflectance under the same illumination, the red object will appear darker to humans. So there are many transfer functions at work here which makes the problem challenging in picking the right colormap that is perceptually uniform, has the maximum number of perceived differences, and has the appropriate number of hues for best represeting your dataset.

Finally, it would not be complete of me to not mention this article: http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=411848...

Slides: http://www.cs.odu.edu/~mweigle/cs725s15/presentations/nam-pr...

The "Tufte" of maps.

I've been using colorbrewer to make maps for many years now, nice to see her getting some recognition.

This java library (among several others, certainly) provides color schemes for data viz, including the ColorBrewer schemes

http://www.dishevelled.org/color-scheme/

The article is dated, very subtly, 2014. Look just above the headline, next to the byline.