MAPPING MORTALITY - EVALUATING COLOR SCHEMES FOR CHOROPLETH MAPS

Use of color for representing health data on maps raises many unanswer ed questions. This research addresses questions about which colors all ow accurate map reading and which colors map users prefer. Through the combination of a review of previous color research and an experiment designed to test specific combinations of colors on maps, criteria wer e established and evaluated for selecting colors for choropleth maps o f mortality data. The color-selection criteria provide pairs of hues f or diverging schemes that avoid naming and colorblind confusions. We a lso tested sequential and spectral schemes. Our results show that colo r is worth the extra effort and expense it adds to map making because it permits greater accuracy in map reading In addition, people prefer color maps over monochrome maps. Interestingly, scheme preference is a ffected by levers of clustering within mapped distributions. In this r esearch, people preferred spectral and purple/green hue combinations. Contrary to our expectations, spectral schemes are effective if design ed to include diverging lightness steps suited to the logical structur e of mapped data. Diverging schemes produce better rate retrievals tha n both spectral and sequential schemes, however. In addition, divergin g schemes place better emphasis on map clusters than sequential scheme s. Thus map effectiveness is improved by use of diverging schemes. Our interdisciplinary research connects geographers with epidemiologists through concern about map symbolization and map reading, strengthening a significant area of collaboration. Providing guidelines that improv e the design of customized color schemes will assist map makers in arl disciplines in gaining insights about their data.