This presentation is co-financed by the European Social Fund and the state budget of the Czech Republic

Visual distance of map symbols evaluation of map readability with eye-tracking

Alžběta Brychtová

First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc

Jan T. Bjørke, Norway (1996):„It is necessary to maintain sufficient visual distance between map symbols to make them distinguishable.“

visual distance1. 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

Visual distance

First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc

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

Visual distance

First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc

necessity to emphasize sufficient difference of visual variables

Jacques Bertin's visual variables (7) size position shape orientation color hue color value texture

Visual distance

First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc

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)

Research task

First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc

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:

Color distance

R, G, B

RA, GA, BA and RB, GB, BB determine RGB vector of colors A and B being compared

First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc

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

Experimental design

First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc

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

Experimental design - stimuli

First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc

20% 40% 60% 80% 98%

8 pt

14 pt

11 pt

First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc

within subject design – all participant tested under the same condition

randomization of trials – prevention of the learning effect

Experimental design - process

15

First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc

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

Experimental design - respondents

First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc

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

Monitored metrics

First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc

Shapiro-Wilk test of normality

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

On the significance level α = 0.05 no differences between two groups of respondents in measured metrics were proven

Results

fixation count average fixation duration scanpath length time to answer

p-value 2.2e-16 3.129e-16 2.2e-16 2.2e-16

fixation count average fixation duration scanpath length time to answer

p-value 0,09238 0,988 0,7801 0,2094

First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc

different perception between groups men and women Mann-Whitney test for median comparison

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

Results

fixation count average fixation duration scanpath lenght time to answer

p-value 0.008283 3.875e-09 0.02236 0.6384

First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc

Kruskal-Wallis ANOVA for mean rank comparison different perception of maps with varying color distance no categorization

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.

fixation count average fixation duration scanpath lenght time to answer

p-value 0,009817 0,9073 0,005274 0,0012

First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc

Results post-hoc Kruskal-Wallis tests differences of perception between pairs of map of

concrete color distance

color distance

observed difference

critical difference

difference

20%-40% 39.125000 68.99673 FALSE

20%-60% 31.665398 68.87767 FALSE

20%-80% 82.903329 68.87767 TRUE

20%-98% 63.527778 68.99673 FALSE

40%-60% 7.459602 68.87767 FALSE

40%-80% 43.778329 68.87767 FALSE

40%-98% 24.402778 68.99673 FALSE

60%-80% 51.237931 68.75840 FALSE

60%-98% 31.862380 68.87767 FALSE

80%-98% 19.375551 68.87767 FALSE

color distance

observed difference

critical difference

difference

20%-40% 48.36111 68.99673 FALSE

20%-60% 20.10352 68.87767 FALSE

20%-80% 79.71386 68.87767 TRUE

20%-98% 69.28472 68.99673 TRUE

40%-60% 28.25759 68.87767 FALSE

40%-80% 31.35275 68.87767 FALSE

40%-98% 20.92361 68.99673 FALSE

60%-80% 59.61034 68.75840 FALSE

60%-98% 49.18120 68.87767 FALSE

80%-98% 10.42914 68.87767 FALSE

color distance

observed difference

critical difference

difference

20%-40% 51.24306 68.99673 FALSE

20%-60% 31.85699 68.87767 FALSE

20%-80% 95.19837 68.87767 TRUE

20%-98% 72.83681 68.99673 TRUE

40%-60% 19.38606 68.87767 FALSE

40%-80% 43.95532 68.87767 FALSE

40%-98% 21.59375 68.99673 FALSE

60%-80% 63.34138 68.75840 FALSE

60%-98% 40.97981 68.87767 FALSE

80%-98% 22.36157 68.87767 FALSE

fixation count scanpath length time to answer

First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc

First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc

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.

Conclusions