Geography Reference
In-Depth Information
Table 3 Relationship between map complexity, average fixation duration and fixation count for
the six maps of the case study
Complexity
hierarchy
(1
Fixation
count
legend
Average fixation
duration map
Average fixation
duration legend
Fixation
count map
highest)
ΒΌ
Map
6
1
273
246
338
109
Map
1
2
286
236
103
75
Map
3
3
286
263
108
34
Map
4
4
280
260
68
28
Map
5
5
235
246
217
55
Map
2
6
279
220
48
27
legend of this map. The choropleth map showing the costs of public pupils
'
transport (which can be seen in Fig.
1
on the bottom, left side) shows a different
eye movement pattern. Respondents were using the legend, and they were looking
especially at the areas of the map which had values higher than they expected. This
is especially true for the northern part of the city, where they have several schools,
but pupils prefer to leave their district and go to school in the city centre or in the
neighbour cities instead.
The gaze parameters show that the maps with the most complex information
content get the most fixations, but the average fixation duration is not higher than at
the maps containing less complex information content (Table
3
). It appears that the
respondents interest in the presented content influences the average fixation dura-
tion instead. The differences between map types are less important than the
differences between maps showing interesting content and maps showing less
interesting content seen from the decision makers perspective.
Conclusion
The study, especially the online survey in the first part, could prove the
relevance of the spatial dimension for the three actor groups within the
process of establishing a local budget. All three actor groups see the advan-
tages of using maps as decision support tool. The respondents gave many
hints about map content and map design in order to create maps which could
support their decisions. Their hints were very different according to the
peoples
background and working tasks. Also, they answer that a combination
of maps and tables would suit their needs best. To sum it up, the participants
favourite local budget plan decision support system would be one where
'
(continued)
