Robustness and Resilience of Cities Around the World
Transcript of Robustness and Resilience of Cities Around the World
Robustness and Resilience of Cities Around the World
Tahar ZanoudaSofiane Abbar Javier Borge-holthoefer
@UrbComp. San Francisco, California. Aug'2016
Heather Leson*
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Urban Resilience
25+ definitions from different domains (Meerow et al.)– Engineering sci, Environment sci, Social sci, etc.
• Capacity of a urban area to confront uncertainty and/or risk
• Capacity of a system to recover its initial state after a shock
S. Meerow, J. P. Newell, and M. Stults. Defining urban resilience: A review. Landscape and Urban Planning, 147:38-49, 2016
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Helping cities around the world become more
resilient to the physical, social, and economic challenges
that are a growing part of the 21st century.
Rockefeller 100RC 1/2
City Resilience Index
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Rockefeller 100RC 2/2
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Random failure
Reachability of services
Targeted attacks
Road Networks!
Rockefeller 100RC 2/2
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Large Scale Study of Road Networks Resilience
50+ cities from 6 continents
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Graph GenerationFrom Open Street Map to Road Networks
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Generated Road NetworksDoha
Riyadh
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Robustness
• Network Robustness has long tradition in complex systems/applied physics
• Approached by percolation processes
• Two types of percolation• Site percolation: nodes removal• Bond percolation: edges removal
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Road Network Robustness Through Bond Percolation
• Failures– Random removal of edges / probabilistic
• Attacks– Targeted removal of edges (e.g., based on their
centrality scores) / deterministic
Cities may react differently to these two types of percolation
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Approach 1/2
• While size(GCC) != size(SLCC) do: – Remove an edge from the graph– Report the size of the new GCC (Giant Connected
Component)– Report the size of the new SLCC (Second Largest
Connected Component)
• Percolation threshold (pc) is observed at the fraction of removed edges in which SLCC maximizes
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Approach 2/2
Size of components (fraction of
#nodes)
Percentage of removed edges
GCC
SLCC
Pc = 27% percolation threshold
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Robustness Results
RandomFailure
Targeted Attack
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Robustness vs. Resilience
Robustness– How much can you
take before you fall down
Resilience– How long does it take
you to stand up again #R
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Resilience
• Group Foursquare locations by categories– Medical centers, transportation & travel, food, etc.
• Assign each foursquare location (f_l) to the nearest node n (intersection) in the graph iff dist(f_l, n) <= d
• Compute service availability in the giant connected component before and after failures
Can the city keep servicing its population?
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Resilience results 1/2
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Resilience results 2/2
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Future work
• Dynamical robustness– Assess the impact of percolation on the
traffic status (congestion levels)
• Multi-model robustness– Consider multiple transportation layers– Run percolation on the multiplex
Thank you!Sofiane Abbar · [email protected]
We are hiring!- Post-Docs (urban computing)- Research Associate (urban computing)