Structural Holes for Structuring Hierarchical Road Network The 24th International Cartographic Conference Santiago, Chile ∙ November 15-21, 2009 Structural Holes for Structuring Hierarchical Road Network Hong Zhang The Hong Kong Polytechnic University oceanzhhd@gmail.com and Zhilin Li lszlli@inet.polyu.edu.hk

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

Street in the urban system (a): a Planning city (http://www.spacesyntax.com/) (b): Nottingham (http://www.spacesyntax.com/) (c): Kevin Lynch “The Image of City” Urban system vs Human body Network & Flows vs Blood vessel & blood

Street and human life Urban street network  Human behaviors (a) Navigation (Rosvall et al. 2005) (b) Traffic flow (Hillier and Iida 2005) (c) Crime (Nubani and Wineman 2005) Urban street network  Human behaviors

Outline Review of road network research Why study road network? Representation and modeling Properties Road structure VS human behaviors Structural holes Concepts and methodology Theoretical analysis Experimental testing Conclusions

Representation and Modelling (cont’ed) Graph Object Primal graph Dual graph Characteristic points Axial line Stroke (70 degree) Named street Fig. 3: a sample street network of London

Representation and Modelling Graph Object Primal graph Dual graph ICN Segment Alternative chain Fig. 3: a sample street network of London

Stroke a b c Natural movement Deflection angle β α

Properties Fractal Small-world Scale-free Self-organized Hierarchical Fig. 5: Hierarchies emerged from traffic flow distribution (Jiang 2009)

Limitations (c) (a) (b) 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 Develop new techniques for Structuring Hierarchical road network

Outline Structural holes 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

Network Science (b) WWW (c) Internet (a) A simple food chain network nd.edu 300,000 web-pages (b) WWW (c) Internet (d) Protein (a) A simple food chain network

Structural hole and ego network third alter ego third alter ego third alter (a) complete ego-network (b) ego-control network (c) ego-passive network Fig. 8: Three kinds of ego networks

Structural hole and ego network alter1 alter2 ego alter1 alter2 ego 1 alter1 alter2 ego (a) complete ego-network (b) ego-control network (c) ego-passive network Fig. 9: Three kinds of ego networks

Centrality Rank Proportional Strength Indirect Link Strength (j∈ine), (j, q∈ine and q ≠j) Proportional Strength Indirect Link Strength Constraint Aggregate Constraint Centrality Rank alter1 alter2 ego

Theoretical illustration (b) S2 S10 S35 S33 S78 (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

Experimental testing Fig. 10: Connectivity graph and traffic flow accommodation of selected roads

Conclusions 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 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/)

Thank you！ Questions?