A Tutorial on Color Symbolization and Data Classification

STIS 2003 / BioMedware

A Tutorial on Color Symbolization

and Data Classification for Mapping and Visualization

Cynthia Brewer, Penn State Geography

Prepared for STIS conference sponsoredby BioMedware, January 9-10, 2003, in Ann Arbor


Color Symbolization


Digital Government Quality Graphics

NSF Grant No. 9983451

www.geovista.psu.edu

www.ColorBrewer.org

with Mark Harrower


Full view - solution


Color scheme types

Sequential: light-to-dark; low-to-high data

Diverging: dark-light-dark, two hues; emphasize critical midrange in ordered data

Qualitative: different hues, similar lightness; categorical data


Example maps

Sequential

DivergingQualitative

From MappingCensus 2000 atlas


Use perceptual system

such as Munsell (HVC)

Figure from www.munsell.com/munsell1.htm


…to be sure you understand the perceptual dimensions of color

Break for Munsell chip organization task

STIS 2003 / BioMedwareHue and lightness, sequential schemes from ColorBrewer


Sequential scheme paths

hue and value graph


Sequential paths collapsed


Example chroma & value paths for sequentialschemes


Diverging paths collapsed


Example divergingschemes


Qualitative schemes


Summary

Each scheme type has a characteristic path through perceptual color space


Classification


Classification for map comparison

is key issue in multi-map contexts


Stroke, White MaleTime SeriesMatched legends


Classification literature

Brewer & Pickle (Dec. 2002 Annals of AAG)

Reviews: Jenks, Coulson, Evans, Paslawski, Slocum

On Comparison (most in 70s):Monmonier, Lloyd & Steinke, Olson, Muller

1990s: Cromley


Experiment

Classification7 map series, 6 questions each, 58 subjects

Matched Legends2 map series—one with matched legends, 48 subjects

Questions about polygons, regions, whole maps;Within map and comparison questions


Classification types

Tested:- Quantile (percentile)- Min. boundary error- Jenks optimization,

Natural breaks - Equal interval

with class for extremes- Mean and st. deviation- Shared area- Box plot based

Others:- Arithmetic, Geometric- Nested means- Significance based- Equal area- Min. difference from

class midpoints or medians

- Critical values…


Map series

Lung cancer for WM, WF, BM, BFHIV, unintentional injuries for WM, BMAll causes, heart, cancer, stroke (WF)Motor vehicle, suicide, homicide (WM) and % urbanBreast cancer (WF), income, education, urbanHeart disease, 4 time periods (WM)Stroke, lung cancer, 2 time periods each (WM)

Liver disease, COPD for WM, WFStroke, 4 time periods (WM)


Quantile example mapStroke, White Female


Hybrid equal interval exampleStroke, White Female


Quantiledata

classing


Hybrid equal interval


Results Graph


Conclusions

Classifications suited for choropleth maps in series intended for a wide range of map reading tasks:

QuantileMinimum boundary errorNatural breaks (Jenks)


Use same legends

Matched legends aid map comparison 28% improvement!


Difficult tasks

- interpreting broader map patterns- comparing patterns between maps- questions requiring map legend reading


Classing strategies for series

- share class breaks between maps

- use meaningful breaks:national rate, median, zero, threshold…

- round aggressively


Two change maps“One race” or “One or more including…”


Example comparison

One race, AIAN One or more…AIAN

26.4% 110.3%


Classing series

- class aggregate of all data for series- use many classes/colors- map with subset of classes for each map- limit to true max and min within each map


Classing series examples

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STIS 2003 / BioMedwareSame map pair with and without matched legends


Color and classes reveal your data; use them smartly

www.personal.psu.edu/cab38

www.colorbrewer.org

[email protected]

Documents

A Tutorial on Color Symbolization and Data Classification