Presentation from Third InDOG Doctoral Conference in Olomouc, Czech Republic. 13. - 16. October 2014

1. EYE TRACKING IN THE GEO-DOMAIN
A PERCEPTION ON CARTOGRAPHY,
NAVIGATION AND LANDSCAPE DESIGN
Research Conducted at the Landscape & CartoGIS Research
Unit, Department of Geography, Ghent University
Kristien Ooms Fanny Van den Haute
Lien Dupont Annelies Incoul
Pieter Laseure Pepijn Viaene
Philippe De Maeyer Nico Van de Weghe Veerle Van Eetvelde
InDOG – 13-16/10/2014
Palacký University – Olomouc

2. 2
Eye tracking in the Geo-Domain
1. Visual impact of wind turbines in the landscape
• Master Thesis Fanny Van den Haute
2. The use of eye tracking in landscape perception research
• PhD Research Lien Dupont
3. Search strategies on time intervals in 1D and 2d representations
• Master Thesis Pieter Laseure
4. Comparing paper and digital maps using eye tracking
• Master Thesis Annelies Incoul
5. Influence of toponyms’ colours on their readability
• PhD Research Rasha Deeb
6. Maps, how do users see them?
• PhD & PostDoc research Kristien Ooms
7. In search of indoor landmarks
• Master Thesis and PhD research Pepijn Viaene
InDOG – 13-16/10/2014
Palacký University – Olomouc

3. VISUAL IMPACT OF WIND
TURBINES IN THE LANDSCAPE
MASTER THESIS
FANNY VAN DEN HAUTE
InDOG – 13-16/10/2014
Palacký University – Olomouc

4. 4
Research Objective & Questions
▪ Sustainable energy >> wind turbines >> spatial planning
• Appropriate in the landscape?
• Visual impact?
▪ Research Questions
• How do people look at a landscape with wind turbines?
• Is there a difference before and after placement of the wind turbines?
• Is there a difference due to personal characteristics (expertise)?
• Does the type of landscape play any role in this?
InDOG – 13-16/10/2014
Palacký University – Olomouc

5. 5
Research Objective & Questions
▪ Stimuli
• Panoramic photos
• Simulations in photoshop
• 5 different landscape types
• 60 pictures in total
• 7 seconds free viewing
• Participants
• 15 experts
• 29 non-experts
InDOG – 13-16/10/2014
Palacký University – Olomouc

6. 6
Resultaten
▪ Wind turbine
• Viewed at after avg 1,5 s
• 86,8 % eye catchers
• 86,3% longest viewings
▪ Wind turbine vs. other vertical objects
• Faster
• More and longer fixations
• Shorter first fixation
• More returned movements
InDOG – 13-16/10/2014
Palacký University – Olomouc
1. How do people look at a landscape
with wind turbines?
2. Is there a difference before and after
placement of the wind turbines?
3. Is there a difference due to personal
characteristics (expertise)?
4. Does the type of landscape play any
role in this?

7. 7
Resultaten
 Eye catchers
• Type changes > wind turbine
• Viewed at faster
 Fixations
• More and longer fixations
• More returned movements
• Cause: presence wind turbines
WIND TURBINES HAVE
A VISUAL IMPACT
InDOG – 13-16/10/2014
Palacký University – Olomouc
1. How do people look at a landscape
with wind turbines?
2. Is there a difference before and after
placement of the wind turbines?
3. Is there a difference due to personal
characteristics (expertise)?
4. Does the type of landscape play any
role in this?

8. 8
Resultaten
 Similarity
• Type eye catcher> wind turbine
• Type longest viewed object > wind turbine
• Timing of viewings
• Number of fixations
 Difference
• Experts shorter fixations
EXPERTISE HAS NO INFLUENCE
ON VIEWING PATTERN
1. How do people look at a landscape
with wind turbines?
2. Is there a difference before and after
placement of the wind turbines?
3. Is there a difference due to personal
characteristics (expertise)?
4. Does the type of landscape play any
role in this?
InDOG – 13-16/10/2014
Palacký University – Olomouc

9. 9
Resultaten
 Similarity
• Timing of perceiving wind turbine
 Difference
• Type eye catcher and object viewed at longest
- industrial and infrastructural landscapes
 wind turbines less dominant
• Timings of eye catcher
- Woody area > hill or open rural area
TYPE OF LANDSCAPE HAS INFLUENCE
ON VIEWING PATTERN
1. How do people look at a landscape
with wind turbines?
2. Is there a difference before and after
placement of the wind turbines?
3. Is there a difference due to personal
characteristics (expertise)?
4. Does the type of landscape play any
role in this?
InDOG – 13-16/10/2014
Palacký University – Olomouc

10. THE USE OF EYE-TRACKING IN
LANDSCAPE PERCEPTION
RESEARCH
PHD RESEARCH
LIEN DUPONT
InDOG – 13-16/10/2014
Palacký University – Olomouc

11. 11
Research Questions
Which elements in a landscape catch the attention and in
which context are they most eye-catching?
Important for the location of new
infrastructures
Observer
Representation
Observations of landscapes
are influenced by…
Landscape
InDOG – 13-16/10/2014
Palacký University – Olomouc

12. 12
Research Questions
 How do people observe landscapes in general?
• Influence of the photograph properties?
‒ Focal length, horizontal and vertical view angles
• Influence of the landscape characteristics?
‒ Degree of openness
‒ Degree of heterogeneity
• Influence of the social/professional background of the observer?
‒ Landscape experts versus novices
• Influence of type of landscape?
‒ Degree of urbanisation
‒ Landscape experts versus novices
‒ Predict viewing pattern?
Experiment 3 Experiment 2 Experiment 1
InDOG – 13-16/10/2014
Palacký University – Olomouc

13. 13
Study design – Experiment 1
 Photograph sampling
Focal
length
18 landscapes
Horizontal
view angle
90 photographs in total
Vertical
view
angle
a) Panoramic
photograph
50mm 70° 20,9°
b) Standard
photograph
50mm 31° 20,9°
c) Zoom 1 70mm 22,4° 15°
d) Zoom 2 100mm 15,8° 10,5°
e) Wide angle
photograph
18mm 75,1° 54,3°
23 participants (geographers)
InDOG – 13-16/10/2014
Palacký University – Olomouc

14. 14
Enclosed Semi-open Open
Homogeneous Heterogeneous
90 photographs in total
21 landscape expert participants
23 novice participants
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Palacký University – Olomouc

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Study design – Experiment 2&3
21 landscape expert participants
InDOG – 13-16/10/2014
Palacký University – Olomouc
74 photographs,
differing in degree of
urbanisation
21 novice participants

16. 16
Methodology
 Eye tracking technology
• Non-portable RED-system (SMI)
 Eye tracking experiments
• Random order
• 5 or 10 seconds per photograph
• Free-viewing
• Measured eye tracking metrics
• Fixations: number, duration (ms)
• Saccades: number, amplitude (°), velocity (°/s)
• Derived products: focus maps
InDOG – 13-16/10/2014
Palacký University – Olomouc

17. 17
Results – Experiment 1
Panoramic Open
 More fixations
 Shorter saccades
More information extraction
 Shorter fixation duration
Easier information extraction
 More saccades
 Larger saccades
 Faster saccades
Stronger visual exploration
InDOG – 13-16/10/2014
Palacký University – Olomouc
 Less & longer fixations
 Less saccades
Weaker visual exploration
Homogeneous
 Less fixations
 Less & longer saccades
Weaker visual exploration

18. 18
InDOG – 13-16/10/2014
Palacký University – Olomouc
Expert Novice
More
fixations &
saccades
Less
fixations &
saccades
Shorter
fixations
Longer
fixations
Longer
scan
path
Shorter
scan
path
Larger visual
span
Smaller
visual
span
Smaller
Voronoi
cells
Larger
Vorornoi
cells
Scan paths
Focus maps
Voronoi cells
Results – Experiment 2

19. 19
1050 x 1680 matrices
Saliency map
Focus map
Correlation between focus maps and saliency maps?
InDOG – 13-16/10/2014
Palacký University – Olomouc

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Results experiment 3
▪ Significant effect of landscape type,
▪ No effect of expertstatus, no significant interaction
▪ Non-experts’ viewing pattern is a little more predictable
InDOG – 13-16/10/2014
Palacký University – Olomouc

21. SEARCH STRATEGIES ON TIME
INTERVALS IN 1D AND 2D
REPRESENTATIONS
MASTER THESIS
PIETER LASEURE
InDOG – 13-16/10/2014
Palacký University – Olomouc

22. 22
Research Objective
Evaluate added value of the
Triangular Model
to depict time intervals, compared to the ‘traditional’
Linear Model
InDOG – 13-16/10/2014
Palacký University – Olomouc

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Relevance and Research Questions
▪ Importance in education:
“How to depict temporal information most efficiently?”
▪ Research Questions:
• Is the TM a clearer / more efficient model than the LM?
• Do males and females search differently in these models?
• Do students and experts search differently in these models?
• Can we distinguish differences in the users search strategies; TM vs. LM?
InDOG – 13-16/10/2014
Palacký University – Olomouc

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Study Design
LM TM
 25 novice participant; some removed
 3 expert participants
 8 stimuli & questions for LM
 8 stimuli & questions for TM
 Similar questions
 Mixed
 Alternate
Quantitative analyses
 Response time
 Score
 Fixation duration
 Saccadic length
Qualitative analyses
InDOG – 13-16/10/2014
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Results: Quantitative
Students’ response time
Students’ nr of fixations per second
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Participants’ preference and score attributed to the models
GROUP nr
AVG. SCORE
LM
AVG. SCORE
TM
PREFERENCE
Students 25 5,48/10 8,3/10 TM (25/25)
Experts 3 4,75/10 8/10 TM (3/3)
Students’ fixation duration
Students’ saccadic length
Students’ score

26. 26
Results: Qualitative
InDOG – 13-16/10/2014
Palacký University – Olomouc

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Results: Qualitative
InDOG – 13-16/10/2014
Palacký University – Olomouc
Part. Gender SCANPAD STRING
P01 M
MMBACCDEDCCCCDDEEBBBBBCBCDEDDE
EDDSWWRSSSSSSSSSSSSSSNSRWSSSSS
SSSWWSSMNSSDEEDCCDDDEFDDRSXWS
P02 F
MLAABBBBCCDDDDDDDEDEEDDDWWXSSR
RRSSSSSSSSWCDEEXWSXSSWXSSSSSSS
WSSSSSSSNSRDEBDDRSSSSSNNSSSRRM
MLRRNSSWXXXXWXDDEWSSSSSSNSNSSS
SWNSSSSS
P03 M
MMHBABBCDDCCDERWSSSSSXXIDEBBBBC
CCCDDDEESSSXXRSSSSSSSXDESRRWSSS
SNSSSSSSSD
P05 F
MMLBCCCCDDDDEENXXWSSSSSSSSSSXW
RCDDCBCBBRSSSRSWWRMRLLIRRWWR
P06 F
MMBBABBCDDDEEDEDEWWWWWXSSSSSS
SRSSSSSWSSSXXWSSWN
Scanpad String Similarities

28. 28
Results: Qualitative
InDOG – 13-16/10/2014
Palacký University – Olomouc

29. COMPARING MAP READING ON
PAPER AND DIGITAL MAPS
MASTER THESIS
ANNELIES INCOUL
InDOG – 13-16/10/2014
Palacký University – Olomouc

30. 30
Introduction
▪ Paper versus digital maps
▪ Drawbacks of digital maps:
• Resolution
• Colour ranges
• Dimensions
▪ Same information displayed differently
▪ Eye tracking
• Register the users’ eye movements (Point of Regards, POR)
• Users’ cognitive process
 compare the users’ attentive behaviour
InDOG – 13-16/10/2014
Palacký University – Olomouc

31. 31
Study Design
▪ Participants
• 32 Master students or researchers
• Department of Geography, Ghent University
• Similar domain knowledge in geography and cartography
• Familiar with the design of the Belgian topographic maps
▪ Stimuli
• 6 topographic maps on 1 : 10 000
• Regions in the Southern part of Belgium
• Two similar groups of participants
• Three paper and three digital maps (alternately)
InDOG – 13-16/10/2014
Palacký University – Olomouc

32. 32
Study Design
▪ Task
• Visual search
• Locate three labels in the map image
• Questionnaire
- Background information
- Familiarity with the depicted regions
- Search strategy
▪ Apparatus and Set-up
• Eye tracker: SMI RED system 120Hz
• 50 inch television screen
• Stand alone mode
InDOG – 13-16/10/2014
Palacký University – Olomouc

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Methodology
▪ Data selection
• Calibration accuracy: < 1°
• Tracking ratio: > 85%
• Visual verification
• Shift correction
- At least 10 individuals for each stimulus
- In total: 25 participants
- 68 paper and 70 digital stimuli
Part. 1D 2P 3D 4P 5D 6P Part. 1P 2D 3P 4D 5P 6D
P01 x x x x x x P10 x x x x x
P05 x x x x x x P14 x x x x x
P07 x x x x P16 x x x x x x
P09 x x x x x x P18 x x x x x x
P11 x x x x x x P20 x x x x x x
P13 x x x x x x P22 x x x x
P15 x x x x x x P24 x x x x x x
P17 x x x x x x P28 x x x x x
P21 x x x x x P30 x x x x x x
P25 x x x x x x P32 x x x x x
P27 x x x x P34 x x x x x x
P29 x x x x x x P36 x x x x x x
P33 x x x x x
TOT. 13 11 12 12 12 12 TOT. 10 10 11 11 12 12
InDOG – 13-16/10/2014
Palacký University – Olomouc

34. 34
Methodology
▪ Creating the gridded visualisation
• Areas Of Interest (AOIs)
• Fixation counts and distribution
• Grid of 32 x 22 cells
• AOIs of 40 x 40 pixels
InDOG – 13-16/10/2014
Palacký University – Olomouc

35. paper digital paper digital paper digital paper digital
35
Results
Mean search times
(P = 0.956 > 0.05)
InDOG – 13-16/10/2014
Palacký University – Olomouc
Fixations per second
(P < 0.000)
 Digital maps were less difficult
to interpret than paper maps
Mean fixation duration
(P = 0.210 > 0.05)
Shorter saccades digital maps
1
2
3
4
5
6
1
2
3
4
5
6
Fixation count Fixation duration

36. 36
Conclusion & Future Work
▪ Users’ attentive behaviour on paper and digital maps
▪ Controlled study design
▪ No unidirectional conclusions concerning efficiency
▪ Distribution of the fixations was similar
▪ No real-life situations:
• Generally, digital maps are presented on smaller screens
▪ Further research, taking into account (digital maps):
• Different screen sizes
• Interaction tools
• Specific design
InDOG – 13-16/10/2014
Palacký University – Olomouc

37. INFLUENCE OF TOPONYMS’
COLOURS ON THEIR
READABILITY
PHD RESEARCH
RASHA DEEB
InDOG – 13-16/10/2014
Palacký University – Olomouc

38. 38
Research Context
▪ Typography on maps
• Semiotics according to Bertin
• Bold, italic, shape (font), orientation, etc.
▪ Preference?
▪ Efficiency?
▪ Lettering system?
▪ Colour?
InDOG – 13-16/10/2014
Palacký University – Olomouc

39. 39
Research Questions
▪ Influence of complementary colors (background-label) on the
users’ search efficiency;
▪ Is this further influenced by the user’s characteristics
(gender and expertise)
▪ Are the users’ preference and search efficiency linked?
▪ The findings are compared to the ‘traditionally’ black labels
InDOG – 13-16/10/2014
Palacký University – Olomouc

40. 40
Study Design
Color
system
Design conditions Display conditions
HSV RGB CIE XYZ
Color
No.
H° S% V% R G B
L*
(D65)
a*
(D65)
b*
(D65)
X Y Z
1 0, 100 100 255 0 0 69.9 95.7 77.5 76.09 40.18 4.617
2 30 100 100 255 128 0 86.0 48.6 79.7 88.28 67.98 11.92
3 60 100 100 255 255 0 121.8 -24.3 101.1 140.21 167.63 34.10
4 90 100 100 128 255 0 115.3 -90.6 90.3 81.46 145.01 33.79
5 120 100 100 0 255 0 112.3 -111.5 86.9 65.28 135.30 32.49
6 150 100 100 0 255 128 111.2 -99.6 40.6 68.50 131.85 76.55
7 180 100 100 0 255 255 116.5 -64.8 -39.4 98.45 149.03 257.74
8 210 100 100 0 128 255 70.6 20.4 -109.4 46.27 41.60 232.25
9 240 100 100 0 0 255 45.6 87.8 -148.7 33.45 14.97 222.16
10 270 100 100 128 0 255 55.5 94.3 -132.2 49.45 23.41 223.65
11 300 100 100 255 0 255 71.7 101.5 -6.3 83.62 43.21 52.41
12 330 100 100 255 0 128 79.1 114.9 -92.2 109.63 55.10 225.46
Black 0 0 0 0 0 0 1.5 0.8 -5 0 0.2 0.2
InDOG – 13-16/10/2014
Palacký University – Olomouc

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Study Design
31 participants
15 experts
- 7 females
- 8 males
16 novices
- 7 females
- 9 males
InDOG – 13-16/10/2014
Palacký University – Olomouc

42. 42
Results
Users’ responses (s) between black and colored labels
Map
Number
(M= Mean, SD= Standard Deviation).
Black Color
F P
M SD M SD
1 15.932 10.603 20.955 15.622 2.077 0.155
2 20.252 21.420 13.672 10.090 2.217 0.142
3 18.075 13.104 17.174 13.829 0.069 0.793
4 14.972 22.713 17.785 14.344 0.319 0.574
5 13.814 14.905 18.299 21.648 0.089 0.766
6 23.342 198.80 32.562 38.221 1.328 0.254
7 20.653 14.476 14.876 13.489 2.476 0.122
8 14.511 12.934 14.822 13.136 0.009 0.927
9 13.501 11.750 18.277 13.847 2.144 0.148
10 16.589 12.404 20.589 12.404 1.300 0.259
11 26.218 25.308 16.940 12.609 0.179 0.674
12 14.560 10.138 35.918 38.613 8.314 0.006
InDOG – 13-16/10/2014
Palacký University – Olomouc
MANOVA tests
 Only map number (labels’ colour) significant
Source df
Reaction Time(s)
Fixation Duration
(s)
Fixation count
(Fix/s)
F P F P F P
Corrected Model 117 2.079 0.000 2.240 0.000 1.518 0.001
Intercept 1 354.591 0.000 535.231 0.000
3343.52
0
0.000
Map number 23 4.519 0.000 2.756 0.000 1.930 0.000
Expertise 1 1.361 0.244 0.055 0.814 0.185 0.667
Gender 1 0.996 0.370 0.037 0.964 0.290 0.748
Map number * Expertise 23 1.000 0.463 0.105 1.000 0.878 0.629
Expertise * Gender 1 0.009 0.925 1.024 0.312 0.082 0.775
Map number * Gender 44 1.037 0.410 0.244 1.000 0.679 0.944
Map number * Expertise *
23 0.605 0.927 1.033 0.420 0.706 0.842
Gender

43. 43
Results
▪ Colour difference
ΔE*ab= {(ΔL*)2+(Δa*)2+(Δb*)2}1/2 where: ΔL*= L foreground* - L background*;
Δa*= a foreground* -a background*;
Δb*= b foreground* -b background*.
InDOG – 13-16/10/2014
Palacký University – Olomouc
Colour difference vs. average fixation count per second

44. 44
Results
▪ Luminance difference
ΔY= Y foreground –Y background
calculated from the measured Y-value in the XYZ-system
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luminance difference vs. the target fixation duration

45. MAPS,
HOW DO USERS SEE THEM?
PHD & POSTDOC RESEARCH
KRISTIEN OOMS
InDOG – 13-16/10/2014
Palacký University – Olomouc

46. 46
Maps are … a medium to communicate
Research Aims:
How do map users
Read
Interpet
Store
Retrieve
information on
digital cartographic
products?
Advice for design
(syntax, semiotics)
of digital
cartographic
products:
Guidelines
Implement in online
tools
...
InDOG – 13-16/10/2014
Palacký University – Olomouc

47. 47
Maps are … visual
Eye Tracking
• Evaluate maps: UCD
- Log users’ Point of Regard
∙ Location
∙ Duration
∙ …in screen-coordinates (px)
- Combination with other methods
∙ Reaction time measurements
∙ Thinking alound
∙ Sketch maps
∙ Questionnaires
∙ …
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48. 48
User studies
▪ PhD Research
Basic map design
Expert vs. novices
Label placement
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original
view
total-design
border-design

49. 49
User studies
▪ PhD Research
Complex map design
Expert vs novices
Adaptations in symbology
Mirroring of map objects
....
InDOG – 13-16/10/2014
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50. 50
Maps are … interactive
• ‘Maps on the Internet/Web’
• Typical user interactions
- Panning
 changing extent
- Zooming
 changing scale & extent
• Influence on users’ cognitive processes?
Read
Interpet
Store
Retrieve
Benifical for user?
e.g. memory, change blindness, …
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51. 51
Eye Tracking & Interactivity?
▪ Georeferencing eye movement data
Changing point of
origin
Applying map
projection formula
Spherical Mercator
(inverse)
휆 = 휆0 +
푥
푅
휑 = 2 푡푎푛−1 푒푥푝
푦
푅
−
휋
2
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Palacký University – Olomouc

52. 52
Case Study
▪ Three eye tracking systems
• SMI RED 250
• Tobii T120
• SR Research EyeLink 1000
Panning
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Case Study
▪ Three eye tracking systems
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Panning

54. 54
Evaluation of panning in Google Maps
▪ Alteration map - satellite view
▪ Panning along a route
• Zoom level 13
▪ Find Belgium
• Zoom level 7
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Palacký University – Olomouc

55. 55
Future Work
▪ Zooming?
• In theory: same concept, only change in R value
• Logging change in zoom levels
- Scroll wheel…
▪ Other map projections?
• In theory: same concept, only change in map projection formula
• Example: Google Earth
- Spherical General Perspective Azimuthal projection
InDOG – 13-16/10/2014
Palacký University – Olomouc

56. IN SEARCH OF INDOOR
LANDMARKS
MASTER THESIS & PHD RESEARCH
PEPIJN VIAENE
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Palacký University – Olomouc

57. 57
Introduction
▪ What is a landmark?
= a wayfinding tool
 a location or a direction
 view-action pair
▪ How to identify a landmark?
• Asking observers
picture based object recognition, verbal protocols,
verbal eye-catcher detection, Wizard of Oz Prototyping,
picture based object description ...
• Quantifying
= object + saliency
» Visual – Semantic – Structural
InDOG – 13-16/10/2014
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58. 58
Study Design
thinking aloud
[CTA]
[CRTA]
eye tracking
[fixation locus]
[duration]
InDOG – 13-16/10/2014
Palacký University – Olomouc
eye-mind hypothesis
saliency = “eye catching”

59. 59
Study Design
[CTA (x2)]
[CRTA ]
▪ 13 recordings
▪ 1924 verbalisation
segments
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Study Design
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Results
41 % Referral to a landmark
59 % No referral to a landmark
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Palacký University – Olomouc

62. 62
Results
= [59]
≠ [73]
Ø [89]
eye tracking
DP landmark category object landmark
1 door (route) grey double door
2 other / route indicator exhibition display
3 route indicator sign (“Geography”)
4 door (route) brown double door
5 window window and view
6 door (route) / other pair of sticks / car batteries
7 door (route) brown doors with windows
8 ornament big plant
9 elevator red elevator
10 poster wooden information board
11 door (other) grey double door
12 door (other) glass main entrance
13 route indicator / other sign (“Paleontology”)
14 door (other) brown double door
15 window / route indicator window and view
16 door (route) brown double door
17 door (route) / poster single door
thinking
aloud
InDOG – 13-16/10/2014
Palacký University – Olomouc

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Conclusion
For the identification of (indoor) landmarks
eye tracking can provide qualitative and complete data,
in addition verbal protocols can clarify specific fixations.
InDOG – 13-16/10/2014
Palacký University – Olomouc

64. SOME FUTURE PLANS…
InDOG – 13-16/10/2014
Palacký University – Olomouc

65. 65
Future Plans
▪ Evaluation of the school’s textbooks
▪ Evaluation of the new 25K symbology
• Together with
• 1 : 20 000  1 : 25 000
• Paper maps, over whole Belgium
InDOG – 13-16/10/2014
Palacký University – Olomouc

66. 66
Future Plans
▪ Evaluation of Neogeography maps
▪ Evaluation of maps on different devices
• Touch-interactions
InDOG – 13-16/10/2014
Palacký University – Olomouc

67. THANK YOU FOR YOUR ATTENTION
QUESTIONS?
Fanny.
VandenHaute
@UGent.be
Lien.Dupont
@UGent.be
PieterLaseure
@hotmail.com
Annelies.Incoul
@UGent.be
Rasha.Deeb
@UGent.be
Kristien.Ooms
@UGent.be
Pepijn.Viaene
@UGent.be