Transcript PPT - Space Syntax Symposium 8

SSS8 - Chile 2012
Time use and movement behaviour of young people in cities
The application of GPS tracking in tracing movement
pattern of young people for a week in Aalborg
The Aalborg Case
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Thank you very much for the possibility to participate in the SSS8
• Thank you for the critique to our paper/presentation
• Thank you for placing the presentation in this session
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A special thank you to Akkelies Van Ness, Delft University of Technology,
Who introduced us to the magnifying world of Space Syntax Analyses
• And to Margarita Greene Z. and José Reyes S. from the SSS8
Organizing Committee for answering our e-mails
Diverse Urban Spaces
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Our research profile
• Research group located at Aalborg University’s Department of
Architecture, Design and Media Technology in Denmark 6 members
• Employees with various academic backgrounds, ph.d.’s, post doc.,
architects, surveyors, sociologists, student assistants etc.
Our research work
• Studies of mobility among different population groups across varying
scales in both indoor and outdoor environments
Examples of our research
• Analyses of how citizens/humans in an urban environment make use
of over parks / plazas / central city areas e.g. – GIS/GPS mapping of
the everyday movement and time consumption patterns of 300 high
school students (2007), 200 Bicyclists (2011), and 400 individual
respondents in around 100 families (2011)
Motivation for applying Space Syntax on GPS data
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All our projects – especially our flagship project ”Diverse Urban Spaces” –
result in very rich GPS data sources describing actual movement and
behaviour, compare to others types of datasamples
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Akkelies Van Ness, Delft University of Technology, provided a series of
Space Syntax analyses of Aalborg City’s road and path network
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Two data sources depicting the infrastructure (the space syntax data and
the GPS data)
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Comparison in order to evaluate theory versus practice and as such the
quality of the Space Syntax method
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Ratti, C. 2004b, "Space syntax: some inconsistencies", Environment and
Planning B: Planning and Design, vol. 31, pp. 487-499.
Diverse Urban Spaces in a nutshell
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A grand research project involving over 300 young people attending high
school or equevalent level of education in Aalborg Denmark who were
tracked in 7 days
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Research objective: To study how the city og Aalborg is used by this
particular segment of respondents
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Technical setup was twofold:
• Each respondent had to carry a hand-held
GPS-receiver throughout a week
• After each survey day, the respondent was
tasked with filling out a trip diary
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Motivation for continuous participation was
daily and weekly lotteries with cash prizes
Technical setup
Case
Data gathering
Server / database Data cleansing
And preparation
GIS analyses
Example of output analysis - Accumulated time consumption
Central city area in Aalborg, Denmark
Urban life ??
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In the Aalborg Case we used a subsample of data from 169 statistical verified
respondents tracked 24 hours in 7 days from the 300 respondents
Overall - Space syntax analyses
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Conducted by Akkelies Van Ness, Delft University of Technology
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Different analyses using varying settings
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High metrical radius highlights main transportation corridors
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Low metrical radius highlights local city centres
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Output stems with reality (with exceptions) for Aalborg, cf. next slide
• Main transportation corridors Vesterbro, Hobrovej, Sønderbro,
Østre Allé get highlighted
• Pedestrian areas in Aalborg and Nørresundby get highlighted
• Some noise in both analyses
Overall - Space syntax analyses
Global integration – high metrical radius
Map uses in the analyses
Local integration – low metrical radius
Time consumption
of men.
Time consumption
of woman.
Put the two together
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The analyses depicting the global integration was chosen for the
comparison
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The reason for using this analysis is that the dataset containing
mobility and time consumption involves the entire urban area
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Time accumulation Maps - The largest time was spent in the various
shopping areas in Aalborg in the central city area. Secondly, some high
amount of time was spent on the various main routes leading through and
between urban areas.
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Woman spent more time in central shopping areas
Overall - Comparison method
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Founded on an assumption of positive linear correlation between a road
segment’s rank as classified by the space syntax analysis and the
accumulated time consumption on streets created by the respondents in
the Diverse Urban Spaces project
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”Home-spun” procedure involving 3 steps
Comparison method, step 1
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10 categories of time consumption levels are calculated, corresponding to
the 10 space syntax classification levels.
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Time consumption categories are yielded as quantile values based on the
time consumption data
Overall - Comparison method, step 2
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Each observation of accumulated time which spatially intersects a given
road segment is selected
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A mean value of accumulated time consumption for the road segment is
calculated based on the values of the selected observations
Comparison method, step 3
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The mean value (µ) is evaluated against the quantile values corresponding
to the the space syntax classification
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If µ matches the quantile values, coherence is attained
Space syntax class
10
9
8
7
6
5
4
3
2
1
Coherence at
(strict rule)
µ < q1
q1 < µ < q2
q2 < µ < q3
q3 < µ < q4
q4 < µ < q5
q5 < µ < q6
q6 < µ < q7
q7 < µ < q8
q8 < µ < q9
q9 < µ
Coherence at
(loose rule)
µ < q2
µ < q3
q1 < µ < q4
q2 < µ < q5
q3 < µ < q6
q4 < µ < q7
q5 < µ < q8
q6 < µ < q9
q7 < µ
q8 < µ
Overall Men/Women - Results, strict coherence rule
Men
Women
Results, strict coherence rule
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Generally only coherence along the main transportation corridors
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There is coherence between time spent and space syntax
classification, when the mean value of the selected squares is
compared with the expected time consumption for the polyline
based on the classification. The expected value is derived by
yielding 9 quantile values (q) which divide the time consumption
registration dataset into 10 approximately evenly distributed
groups.
Results, loose coherence rule
Men
Women
Results, loose coherence rule
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A greater degree of coherence in suburban areas as well as some parts of
the city centres in addition to the main transportation corridors
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A close-up view of the main pedestrian areas shows lack of coherence
between space syntax classification and time consumption
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The coherence rule is loosened slightly in the sense that
coherence is achieved if the mean value resides within a buffer of
± 1 quantile of the expected time consumption value. I.e.,
coherence is reached for the space syntax class 5 at q4 < µ < q7
instead of q5 < µ < q6.
Still lack of coherence in the main pedestrian in the central
City areas for men and woman
Results, overall statistics
Number of road segments
Non-visited road
segments
Number of squares
Accumulated time
consumption
5865
Women
799
Men
779
14,891
15,125,711 seconds
15,625
18,838,688 seconds
Occurrences of
coherence
Occurrences of
lack of coherence
Coherence-ratio
Women, strict
rule
637
4,429
10.86 %
Men, strict rule
625
4,461
10.65 %
Women, loose
rule
1,972
3,094
33.62 %
Men, loose rule
1,916
3,170
32.67 %
Evaluation and conclusions
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High school students in Aalborg also travel frequently along main transportation corridors
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There is no coherence between space syntax classification and actual time
spendure in the main pedestrian areas in the central City area.Most likely
because the used Space Syntax analysis in this cases uses a high metrical
radius which doesn’t highlight road segments with a high local integration
but this will change when using a more loose coherence rule and maybe
low metrical radius in the Space Syntax analysis.
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The lack of coherence is a natural consequence when the space syntax
analysis is executed with a high metrical radius. As such, the northernmost
shopping districts have a classification which is too low to attain
coherence with the massive time consumption registered in these areas. If
the space syntax classification is mapped on top of the time consumption
dataset, this assumption becomes more reliable.
What can be done to adjust Space Syntax to GPS data
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One of the points of criticism of the space syntax method was a lack of
the metrical properties in their analyses (Ratti 2004). Now it is
incorporated in the calculations. As research results show, the geometrical
and topological distances correspond with the pedestrian and vehicle flow
rates and the location pattern of shops more than the metrical distances.
However, when applying metrical radiuses in the angular and axial
analyses, some striking results can be seen.
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Streets with high integration values with a high metrical radius tend to be
the potential routes for through movement. Conversely, streets with high
integration values with a low metrical radius tend to be potential meeting
places for the neighbourhood. When comparing these two analyses with
one another, the most vital urban areas tend to be where streets have
high integration values with both high and low metrical radiuses. (van Nes,
Berghauser-Pont, Maschoodi, 2011).
Further work
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Conduct the comparison using a
better scientific founded method
such as Linear Regression instead of
the “homespun” method
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Conduct the comparison for centre
areas using the Space Syntax analysis
with a low metrical radius – will
most likely lead to a higher
comparison rate
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Conduct the comparison based on
amount of trips and not
accumulated time
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Define what urban life is ..
Thank you for your attention
Any questions?