A Case for Better Graphics: The Unclassed Choropleth Map

Gale, Nathan; Halperin, William C.

doi:10.1080/00031305.1982.10483043

Cited by 11 publications

(4 citation statements)

References 17 publications

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“…Tobler presented the original idea of unclassed maps in 1973 and was first rebutted by Dobson (1973). Investigation, application, and comment have continued in papers by Muller and Honsaker (1978), Muller (1979), Dobson (1980), Groop and Smith (1982), MacEachren (1982), Gale and Halperin (1984), Lavin and Archer (1984), Mak and Coulson (1991), and Kennedy (1994). Peterson's (1979) research included evaluation of classed and unclassed maps using a whole-map comparison task.…”

Section: Other Choropleth Mapping Issuesmentioning

confidence: 96%

Evaluation of Methods for Classifying Epidemiological Data on Choropleth Maps in Series

Brewer

Pickle²

2002

Annals of the Association of American Geographers

329

165

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Our research goal was to determine which choropleth classification methods are most suitable for epidemiological rate maps. We compared seven methods using responses by fifty-six subjects in a two-part experiment involving nine series of U.S. mortality maps. Subjects answered a wide range of general map-reading questions that involved individual maps and comparisons among maps in a series. The questions addressed varied scales of map-reading, from individual enumeration units, to regions, to whole-map distributions. Quantiles and minimum boundary error classification methods were best suited for these general choropleth map-reading tasks. Natural breaks (Jenks) and a hybrid version of equal-intervals classing formed a second grouping in the results, both producing responses less than 70 percent as accurate as for quantiles. Using matched legends across a series of maps (when possible) increased map-comparison accuracy by approximately 28 percent. The advantages of careful optimization procedures in choropleth classification seem to offer no benefit over the simpler quantile method for the general map-reading tasks tested in the reported experiment.

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Section: Other Choropleth Mapping Issuesmentioning

confidence: 96%

Evaluation of Methods for Classifying Epidemiological Data on Choropleth Maps in Series

Brewer

Pickle²

2002

Annals of the Association of American Geographers

329

165

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“…Often, the cartographer must sacrifice the efficiency of one task in the interest of another. One such example is the functional difference between classed and unclassed choropleth maps (Gale & Halperin, 1982). A classed choropleth map divides the information values into ranges, with each member of a class receiving identical shading; an unclassed choropleth map employs a color ramp such that each enumeration unit has its own unique color, according to its unique attribute value.…”

Section: -Tasks In Bivariate Map Readingmentioning

confidence: 99%

Value of Professional Organizations

Smith¹

2019

GIS&T BoK

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Bivariate thematic maps are powerful tools for understanding geographic phenomena, making visible spatial associations between them. But bivariate thematic maps are more visually complex than a univariate map, a source of frustration for both map creators and map readers. Despite a variety of visual solutions for bivariate mapping, there exists few 'best practices' for selecting or implementing an appropriate bivariate map type for a given scenario. This results in a need for empirical research examining the perceptual and functional differences among bivariate mapping solutions. This research reports on a controlled experiment informed by the theory of selective attention, a concept describing the human capacity to tune out unwanted stimuli, and attend specifically to the information desired. The goal of this research was to examine if and how the perceptual characteristics of bivariate map types impact the ability of map readers to extract information from different bivariate map types. 55 participants completed a controlled experiment in which they had to answer close ended questions using bivariate maps. Accuracy and response time were recorded for each question. The experiment also opened with biographical questions to determine participant expertise and finished with a Likertbased survey to determine participant preference of the different map types. The results of this experiment suggest that 1) despite longstanding hesitations regarding the utility of bivariate maps, participants were largely successful in extracting information from most if not all of the tested map types, and 2) the eight map types varied in terms of how intuitively participants were able to use the maps to answer the survey questions. While selective attention theory could explain some of these differences, the performance of the map types differed appreciably from similar studies that examined these map symbols in a more abstract, perception-focused setting. While the perceptual models of selective attention can still be useful in guiding map design, more work needs to be done in understanding the cognitive aspects and limitations to bivariate map reading.

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“…More detailed reviews of this debate are found in Brewer and Pickle (2002) and Slocum et al (2005). The core arguments that have been voiced repeatedly in this debate are that while unclassed maps have the chief advantage of being more accurate in terms of quantised errors (Tobler, 1973;Peterson, 1979;Muller, 1979;Peterson, 1993;Gale and Halperin, 1984), they are simply harder to read because the user must be able to first see subtle differences in colour (i.e., lightness, hue, and/or saturation) and then match those with a legend that contains too many hard-to-discern choices (Dobson, 1973;Dobson,1980;Cromley, 1995;Brewer and Pickle, 2002) increasing map-reading time (Gilmartin and Shelton 1989) and decreasing the accuracy of data recovery (Mersey, 1990). Summarising these debates, Egbert and Slocum (1992, p. 284) say 'from a mathematical standpoint, unclassed maps are ideal because they eliminate error due to data classification, but cartographers have never been able to agree on the perceptual merits of this approach'.…”

Section: New Technology Changes Old Argumentsmentioning

confidence: 99%

Unclassed Animated Choropleth Maps

Harrower¹

2007

The Cartographic Journal

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The potential of unclassed animated choropleth maps as a solution to false patterns of geographic change arising from data classification is investigated. Old concerns about unclassed choropleth maps may be mitigated through map interactivity that offers four advantages over traditional data legends, and previous insights from testing static choropleth maps do not necessarily translate to animated cartography. Data from user testing revealed unclassed animated choropleth maps neither help nor hurt the ability of map readers to understand patterns of geographic change. However, the unclassed map (1) appeared 'less jumpy' to participants and was perceived to run at a slower pace (despite running at the same number of frames per second), and (2) subtle geographic shifts (e.g., seasonal unemployment cycles) were more readily noticed on the unclassed maps. Preliminary results also suggest classed data emphasise stability over time -while their unclassed counterparts improve our ability to see changes. This paper also outlines animated simultaneous contrast as a new perceptual issue in the creation of animated choropleth maps.

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A Case for Better Graphics: The Unclassed Choropleth Map

Cited by 11 publications

References 17 publications

Evaluation of Methods for Classifying Epidemiological Data on Choropleth Maps in Series

Evaluation of Methods for Classifying Epidemiological Data on Choropleth Maps in Series

Value of Professional Organizations

Unclassed Animated Choropleth Maps

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