popelka - the role of hill-shading in tourist maps: an eye-tracking study

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THE ROLE OF HILL-SHADING IN TOURIST MAPS:

an eye-tracking study

Stanislav POPELKA

Department of geoinformaticsPalacký University in Olomouc

Czech Republic

www.eyetracking.upol.cz

EVALUATION OF 3D VISUALIZATION IN GIS WITH THE USE OF EYE-TRACKING

• 3D visualization in three areas:

• 3D visualization of terrain– Perspective maps (Popelka and Brychtová, 2013)

– Hill-shading in maps

• 3D visualization of cities– Photorealistic visualization (Popelka and Dědková, 2013)

– Non-photorealistic visualization (Popelka and Doležalová, 2014)

• Thematic 3D maps

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Our laboratory

• Equipment: – SMI RED 250 – Sampling frequency 120 Hz– Attached web camera

• Software– SMI Experiment center– SMI BeGaze– OGAMA– V-Analytics (a.k.a. CommonGIS)– R

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Shading in maps

• Three categories of shading in cartography– Slope Shading– Oblique shading– Combined shading

• Most frequently used is Conventional lighting Bernabé-Poveda et al., 2011

– The light is coming from the upper left corner of the map– This situation cannot occur in nature, but is the most effective for the

perception of plasticity (Imhof, 2007)

– Several reasons for support of South-East shading exists – BUT…users are so completely conditioned to a light source from above

left that they will percieve the terrain as a negativ (Imhof, 2007)

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The influence of lighting from the South-East

• Task – mark the highest point in the mapPerspective 3D map

2D map illuminated from the bottom-right corner

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The role of hill-shading in tourist maps

• Eye-tracking experiment• Total of 40 respondents (Within – subject study)• Total of 12 stimuli (screenshots from Mapy.cz)

– always a pair of maps

• The task was to find and mark particular hill or village

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Stimuli in the experiment

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Results of the questionnaire

• After the end of experiment, respondents were asked to fill the questionnaire:– Which type of map was more usable for solving the task– Which map type they like more

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Visualization of eye-tracking data

Attention maps in the stimuli from task 3 created in OGAMA software. Kernel 100px

Identified fixations in the stimuli from task 6 – Created from data of all respondents in OGAMA software. Radius = 20

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• Visualization of the grid representing the distribution of fixations within the stimulus

Ooms et al., 2014

• A regular grid of size 5x10 cells was created above each stimulus

• These values can be used in further analyses (adding, substracting, etc…)

Visualization of eye-tracking data

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Analyses of eye-tracking metrics

• At the beginning, the Trial Duration was analyzed„ How long it took to answer“

Comparing of the median values of Trial Duration. Error bars represent the interquartile range.

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Analyses of eye-tracking metrics• Fixation Count - A larger number of fixations indicates a lower level of efficiency

in the search. Goldberg and Kotval, 1999

• Scanpath Length - Depending on the size of this metric comprehensibility of stimuli or difficulty of the questions can be derived. Goldberg and Helfman, 2011

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Analyses of eye-tracking metrics

Trial Duration Fixation Count Fixation Duration Scanpath LengthTrial 1 0.06856 0.05789 0.65 0.01411Trial 2 0.03783 0.03093 0.004077 0.01853Trial 3 0.02155 0.02791 0.08049 0.01925Trial 4 0.02989 0.03659 0.3567 0.02497Trial 5 0.8785 0.9222 0.3303 0.8368Trial 6 0.000009 0.0004388 0.07838 0.000008

• Data were tested using the Wilcoxon test• Nonparametric test – data had not a normal distribution• Statisticaly significant differences between shaded and non-

shaded stimuli are highlighted

Results of the testing of the difference between shaded and non-shaded maps for four evaluated eye-tracking metrics. Data were analyzed using the Wilcoxon test for each pair of stimuli separately. Statistically significant differences (significance level of α = 0.05) are highlighted .

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Analyses of eye-tracking metrics

• In the next step, data were analyzed for all maps together (shaded vs. non-shaded)

• Statistically significant differences were found for all evaluated eye-tracking metrics except Fixation Duration

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Analyses of the role of the task

• The last part of data analyses was evaluation of the role of the task„If respondents were trying to find village (trial 1-3) or the hill (trial 4-6)“

• Statisticaly significant differences were found for all evaluated eye-tracking metrics

Village vs. Hill Aplha V p-value statementTrial Duration 0.05 5708.5 4.369e-16 Rejecting H0Fixation Count 0.05 4954 <2.2e-16 Rejecting H0Fixation Duration 0.05 17794.5 1.979e-06 Rejecting H0Scanpath Length 0.05 5499 <2.2e-16 Rejecting H0

Results of the testing of the difference between task dealing with finding village (trial 1-3) and hill (task 4-6) for four evaluated eye-tracking metrics. Data were analyzed using the Wilcoxon test. Statistically significant differences (significance level of α = 0.05) are highlighted .

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Analyses of the role of the task

• Finally, the statistical dependence between the type of the task (village – hill) and type of visualization (shaded – non-shaded) was analysed

• Testing of Trial Duration metric• Two-way ANOVA + TukeyHSDDvojice Diff Lwr Upr P adj3D hill-2D hill 655.050 -1828.5881 3138.688 0.90469022D village - 2D hill 4088.767 1605.1286 6572.405 0.00015443D village - 2D hill 8169.833 5686.1952 10653.471 0.00000002D village - 3D hill 3433.717 950.0786 5917.355 0.00226433D village - 3D hill 7514.783 5031.1452 9998.421 0.00000003D village - 2D village 4081.067 1597.4286 6564.705 0.0001598

Results of the comparison of the effect of question (village - hill) and visualization (shaded – non-shaded) for eye-tracking metric Trial Duration. (ANOVA* + TukeyHSD)

*Residuas from ANOVA comparison had not a normal distribution, but result of Bootstraping confirmed the accuracy of the results

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Dedendance between task and visualization method

• Type of the task:„It was more difficult to find a village, especially in the map with the shading

• Type of the visualization method:„Shaded variant of the maps were less usable – especially when the task was to find a village“

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Conclusion• An eye-tracking experiment containing tourist maps with and without

shading was created• The questionnaire showed that users liked shaded maps more than non-

shaded.• Shaded vs. Non-shaded

– When analysing eye-tracking metrics Trial Duration, Fixation Count a Scanpath Length statisticaly significant differences were found.

– Higher values were observed in the case of shaded maps

• Village vs. Hill– Statisticaly significant differences were found for all analysed eye-tracking metrics – Higher values were observed in the case of task about finding a village (except Fixation

Duration)

• It was easier to find hill than village• Search in shaded maps was less effective.

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References• BERNABÉ-POVEDA, M. A., SÁNCHEZ-ORTEGA, I., ÇÖLTEKIN, A. Techniques for Highlighting Relief on

Orthoimaginery. Procedia-Social and Behavioral Sciences, 2011, 21, pp. 346-352.• GOLDBERG, J., HELFMAN, J. Eye tracking for visualization evaluation: Reading values on linear versus radial

graphs. Information Visualization, 2011, 10(3), pp. 182-195.• GOLDBERG, J. H., KOTVAL, X. P. Computer interface evaluation using eye movements: methods and

constructs. International Journal of Industrial Ergonomics, 1999, 24(6), pp. 631-645.• IMHOF, E. Cartographic relief presentation. ESRI, Inc., 2007. • OOMS, K., DE MAEYER, P., FACK, V. Study of the attentive behavior of novice and expert map users using

eye tracking. Cartography and Geographic Information Science, 2014, 41(1), pp. 37-54.• POPELKA, S., BRYCHTOVA, A. Eye-tracking Study on Different Perception of 2D and 3D Terrain Visualisation.

Cartographic Journal, Aug 2013, 50(3), pp. 240-246.• POPELKA, S., DEDKOVA, P. Extinct Village 3D Visualization and its Evaluation with Eye-Movement

Recording. ICCSA 2014 - Lecture Notes in Computer Science Volume 8579 Springer International Publishing, 2014, 10p.

• POPELKA, S., DOLEŽALOVÁ, J. Non-photorealistic 3D Visualization in City Maps: An Eye-tracking Study, New Trends in Cartography, 2014, 12p. - in print

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Thank you for your attention

The presentation was made with the support of European Social Fund - Operational Program Education for Competitiveness (project CZ.1.07/2.2.00/28.0078 „InDOG“) and Internal Grant

Agency of Palacký University (project: PrF_2013_024)

standa.popelka@gmail.com