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The 24th International Cartographic Conference
Santiago, Chile ∙ November 15-21, 2009
HK PolyU
Structural Holes for Structuring
Hierarchical Road Network
Hong Zhang
The Hong Kong Polytechnic University
[email protected]
and
Zhilin Li
The Hong Kong Polytechnic University
[email protected]
Outline

Why study road network?

Review of road network research



Representation and modeling

Properties

Road structure VS human behaviors
Structural holes

Concepts and methodology

Theoretical analysis

Experimental testing
Conclusions
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Street in the urban system
(a): a Planning city
(http://www.spacesyntax.com/)
(b): Nottingham
(http://www.spacesyntax.com/)
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(c): Kevin Lynch
“The Image of City”
Urban system vs Human body
Network & Flows vs Blood vessel & blood
Street and human life
(a) Navigation
(Rosvall et al. 2005)
(b) Traffic flow
(Hillier and Iida 2005)
Urban street network

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(c) Crime
(Nubani and Wineman 2005)
Human behaviors
Outline

Why study road network?

Review of road network research



Representation and modeling

Properties

Road structure VS human behaviors
Structural holes

Concepts and methodology

Theoretical analysis

Experimental testing
Conclusions
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Representation and Modelling (cont’ed)
Graph
Object
Characteristic
points
Axial line
Fig. 3: a sample street
network of London
Stroke
(70 degree)
Named street
Primal graph
Dual graph
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Representation and Modelling
Graph
Object
ICN
Segment
Fig. 3: a sample street
network of London
Alternative
chain
Primal graph
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Dual graph
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Stroke

Natural movement

Deflection angle
b
β
c
α
Properties

Fractal

Small-world

Scale-free

Self-organized

Hierarchical
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Fig. 5: Hierarchies emerged
from traffic flow distribution
(Jiang 2009)
Limitations
(a)
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(b)
(c)
Fig. 6: (a) the observation windows (Hillier and Iida 2005), (b) Hong Kong (Jiang and
Liu 2007) (c) flow dimension and flow capacity (Jiang 2008)
Objective
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Develop new techniques for
Structuring
Hierarchical road network
Outline

Why study road network?

Review of road network research



Representation and modeling

Properties

Road structure VS human behaviors
Structural holes

Concepts and methodology

Theoretical analysis

Experimental testing
Conclusions
HK PolyU
Structure hole and Social science

Social sciences focus on structure and
conceptualize social structure as a network
of social ties (Nooy, et al., 2005).

Sociologists either examine the structure of
the entire social group, or turn to the
position of each individual in the local
network.
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Structural hole and ego network (Cont’d)

An ego network is defined as a road network consisting of a single actor
(ego) together with the actors they are directly connected to (or alters)
and all the links among them

Structural hole is an approach developed by Burt (1995) to define the
positional status of each node in its ego network

The structural hole theory believes that in a social network, the
individual’s advantage or power is based on his or her control over
the spread of information, goods or services between his or her
immediate neighbors, and the absence of a tie between either ego or
alter and other alters would induce a structural hole
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Structural hole and ego network
alter
ego
alter
third ego
(a) complete ego-network
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alter
third ego
(b) ego-control network
Fig. 8: Three kinds of ego networks
third
(c) ego-passive network
Structural hole and ego network
alter2
(a) complete ego-network
ego
1
0.5
0.5
1
1
1
0.5
0.5
alter1
0.5
0.5
ego
alter1
0.5
0.5
0.5
alter1
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0.5
alter2
(b) ego-control network
Fig. 9: Three kinds of ego networks
ego
alter2
(c) ego-passive network
Centrality Rank
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1
(j∈ine),
ki

Proportional Strength pij 

Indirect Link Strength pij'  piq pqj


Constraint
Cij   pij   pij' 
(j, q∈ine and q ≠j)


  pij   piq pqj 
q


2
Aggregate Constraint ACi   Cis
2
 j i
ne
,q  ine,q  i,q  j 
alter1
 s  ine ,s  i 
1

ACi
1
 Cis
 s  ine ,s  i 
s
ego
0.5
Centrality Rank CRi 
0.5

0.5
0.5
s
0.5
0.5
alter2
Theoretical illustration
S2
1
S1
0
S1
S4
S3
4
S1
5
S1
2
S1
S1
3
S1
6
S1
S9
7
S1
S8
S5
8
S1
S7 S19
0
S2
S6
(a)
(b)
S2
S78
S35
S35
S2
S33
S10
S2
S2
(c)
(d)
Fig. 11: The sampled Road networks and their connectivity graphs
Experimental testing (Cont’d)
Fig. 12: The location of Sydost and its road network
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Experimental testing
Fig. 10: Connectivity graph and traffic flow accommodation of selected roads
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Conclusions
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
Structural holes can be used for ranking street networks

There is a positive relationship between centrality rank
and traffic flow

Weighted link strength and k-step aggregate constraints
Acknowledgements
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
This research is supported by the Hong Kong
Polytechnic University and RGC of HK (PolyU5221/07E)

The data about Sydost highway network is provided by
Bin Jiang

The San Francisco sampled road network is obtained
from TIGER data of U.S.Census Bureau
(http://www.census.gov/geo/www/tiger/)
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Thank you！
Questions?