1. Visual distance of map symbols evaluation of map readability with eye-tracking Alžběta BrychtováThis presentation is co-financed by theEuropean Social Fund and the statebudget of the Czech Republic
2. Visual distance Jan T. Bjørke, Norway (1996): „It is necessary to maintain sufficient visual distance between map symbols to make them distinguishable.“ visual distance 1. Euclidean distance between symbols  influenced by the real spatial location of mapped objects, topology, generalization and map purpose 2. Rate of difference between symbols appearance  experiences and ability of map makers to design easily distinguishable map symbols First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
3. Visual distance definition “Visual distance of map symbols is exactly determined numerical value describing the degree of variation of visual variables of compared map symbols.” variation of visual variables = change of information transmitted by a map easily distinguishable change of visual variable = easy to read the information First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
4. Visual distance necessity to emphasize sufficient difference of visual variables Jacques Bertins visual variables (7)  size  position  shape  orientation  color hue  color value  texture First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
5. Research task detect influence of color distance between two map elements on the readability of the map assumption:  increasing color distance will have positive impact on map readability experimental stimuli were designed to reflect changes in color value (color hue is currently in progress) First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
6. Color distance Visual distance definition: “Visual distance of map symbols is exactly determined numerical value describing the degree of variation of visual variables of compared map symbols.” The International Commission on Illumination (CIE) defines the color distance as Euclidean distance of two colors in the CIELuv color space In this case study the distance were computed as a dot product of two RGB vectors in the RGB color space: First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
7. Experimental design Eye-tracking experiment was performed statistical analyses of eye-tracking metrics Lab setup:  SMI RED 250 eye-tracker  120 Hz sampling rate  0.4°accuracy and 0.03°spatial resolution  gaze data classification by dispersion threshold algorithm (ID-T) dispersion threshold = 50 px, duration threshold = 80 ms  SMI BeGaze  R Project First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
8. Experimental design - stimuli  15 simple map stimuli varying in color distance of map labeling and background  20%, 40%, 60%, 80% and 98% color distance  8, 11 ad 14 pt size of labels  reduction of the number of independent variables to a minimum  participants were asked to find a concrete administrative unit by its name  avoid the effect of geographical knowledge First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
9.  20% 40% 60% 80% 98%8 pt11 pt14 pt First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
10. Experimental design - process within subject design – all participant tested under the same condition randomization of trials – prevention of the learning effect 15 First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
11. Experimental design - respondents 53 volunteers – students of Palacký University data from 3 respondents with the tracking ratio less than 90% wasn’t taken into account 50 respondents  20-25 years  30 cartographers + 20 non-cartographers  30 men + 20 women data were collected within bachelor thesis of Veronika Obadálková First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
12. Monitored metrics fixation count  more overall fixations indicates less efficient searching average duration of fixation  longer fixation duration indicates difficulty in extracting information, or the object is more engaging in some way scanpath  longer scanpath (the length of gaze trajectory over the stimulus) indicates less efficient searching time to answer  reflects the success during searching the information First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
13. Results Shapiro-Wilk test of normality average fixation fixation count scanpath length time to answer duration p-value 2.2e-16 3.129e-16 2.2e-16 2.2e-16 on the significance level α = 0.05 no one measured eye-tracking metric comes from normal distribution Mann-Whitney test for median comparison different perception between groups of cartographers and non-cartographers average fixation fixation count scanpath length time to answer duration p-value 0,09238 0,988 0,7801 0,2094 On the significance level α = 0.05 no differences between two groups of respondents in measured metrics were proven First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
14. Results different perception between groups men and women Mann-Whitney test for median comparison average fixation fixation count scanpath lenght time to answer duration p-value 0.008283 3.875e-09 0.02236 0.6384 On the significance level α = 0.05 the significant result was proven for fixation count, average fixation duration and scanpath length fixation count F<M average fixation duration F>M scanpath length F<M First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
15.  Kruskal-Wallis ANOVA for mean rank comparison different perception of maps with varying color distance no categorization average fixation fixation count scanpath lenght time to answer duration p-value 0,009817 0,9073 0,005274 0,0012 On the significance level α = 0.05 the significant result was proven for fixation count (H= 13.3192, DF = 4, N=50, P= 0,009817), scanpath length (H= 14.7391, DF = 4, N=50, P= 0,005274) and time to answer metric (H= 17.9129, DF = 4, N=50, P= 0,009817) the mean ranks of these metrics are significantly different among maps with different colour- distance between map labeling and background. First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
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18. Conclusions highest values of all analyzed metrics were observed on the map with the minimal color distance (20%), which means that respondents had difficulties in extracting information from these maps of low color distance; increasing color distance leads to decreasing count of fixations, which can mean the higher color distance the more successful information mining; similar statement can be done for scanpath length and time to answer, except the local maximum of measured metrics for maps with % color distance; color distance has evident influence on map readability, but its improvement can be observed only between stimuli with high differences of the color distance. First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
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