Bikeability can significantly contribute to liveable cities. This presentation presents 3 spatial analysis tools that support planners and decision makers in their effort for more bicycle-friendly cities. The presentation was given at a miniconference on "Quality of Life" at the Department of Geoinformatics, University of Salzburg

1. Safety and accessibility
as major keys for
bicycle-friendly cities
Martin Loidl
Department of Geoinformatics, Z_GIS
University of Salzburg
martin.loidl@sbg.ac.at | http://gicycle.wordpress.com

2. Bicycle Friendliness - QoL
2
http://www.copcap.com/Newslist/2013/Copenhagen-ranked-no-1-as-
the-most-livable-city
http://www.streets.mn/
Positive effects for individuals
and urban societies

3. Which factors make cities
bicycle friendly?
3
http://upload.wikimedia.org/wikipedia/commons/c/c3/Bicycle_parking_lot.jpg

4. 4
Existence ≠
Accessibility!
http://static.panoramio.com/photos/large/57999280.jpg

5. 5
http://www.johns-cycling-diary.co.uk/?p=725 http://www.johns-cycling-diary.co.uk/?p=725
http://newcastlecycleways.org.au
Physical Obstacles &
Dangerous Sections

6. 6
Connectivity
https://static.panoramio.com.storage.googleapis.com/photos/large/80494278.jpg

7. Positive Example
7
http://hovenring.com/design/
Hovenring, Eindhoven (Netherlands)

8. Problem Statement
 Many highly frequented institutions (main station,
university etc.) provide adequate bicycle
infrastructure.
8
https://www.stadt-salzburg.atML

9. Problem Statement
 Many cities and regions invest in bicycle infrastructure
in order to increase the modal split.
9
https://www.stadt-salzburg.at

10. Problem Statement
 Despite these efforts, the potential of the bicycle can
not be used in the most effective way
 Lack of connectivity
 Poor accessibility
 Obstacles
 Thus accessibility and safety needs to be taken into
acount in planning for bicycle traffic!
10

11. Research Work GI Mobility Lab
 Safety evaluation of
 Immediate environment and
 Accessibility of popular destinations
 Provision of a web-based planning tool
 Status-quo analysis
 Assessment for different criteria
 Simulation of the effect of several measures
11

12. Basis
 Indicator-based assessment tool [1]
12
[1] LOIDL, M. & ZAGEL, B. Assessing bicycle safety in multiple networks with different data models. In: VOGLER, R., CAR, A., STROBL, J. & GRIESEBNER,
G., eds. GI-Forum, 2014 Salzburg. Wichmann, 144-154.

13. 13
≤ 0.1 ... optimal
≤ 0.2
≤ 0.3
≤ 0.4
≤ 0.5
≤ 0.6
≤ 0.7
≤ 0.8
≤ 0.9
> 0.9 ... worst
Bikeability around
TechnoZ

14. 14
≤ 0.1 ... optimal
≤ 0.2
≤ 0.3
≤ 0.4
≤ 0.5
≤ 0.6
≤ 0.7
≤ 0.8
≤ 0.9
> 0.9 ... worst
Bikeability around
VHS

15. 15
≤ 0.1 ... optimal
≤ 0.2
≤ 0.3
≤ 0.4
≤ 0.5
≤ 0.6
≤ 0.7
≤ 0.8
≤ 0.9
> 0.9 ... worst
Bikeability around
Eichetstr. 2

16. 16
≤ 0.1 ... optimal
≤ 0.2
≤ 0.3
≤ 0.4
≤ 0.5
≤ 0.6
≤ 0.7
≤ 0.8
≤ 0.9
> 0.9 ... worst
Bikeability around
NaWi

17. 17
Accessibility NaWi

18. 18
Accessibility NaWi

19. 19
Planning Tool
 Interactive, web-based planning tool:
http://gimobility.sbg.ac.at/network-assessment/index.html
@gicycle_
gicycle.wordpress.com
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