Resilience in Spatial and Urban Systems

Aura Reggiani (University of Bologna, Italy)

INTERNATIONAL ABC WORKSHOP ON “SMART PEOPLE IN SMART CITIES”

Banská Bystrica (Slovakia), 28-30 August 2016

Overview and Reflections on:

Resilience & Vulnerability in (Smart)UrbanSystems

Two Perspectives: Spatial Economics and Transport

Smart Cities and Resilience

Reflections on:

Complex evolution of smart cities (multidimensional network perspective)

Positive and negative network externalities

Role of resilience/vulnerability vs accessibility

Two main perspectives: Spatial and TransportEconomics

Background (1)

Smart city: no universally accepted definition(Albino et al., 2015 in JUT): “The concept of smartcity is far from being limited to the application oftechnologies to cities”

“We believe a city to be smart when investments in human and social capital and traditional(transport) and modern(ICT)communication infrastructure fuelsustainable economic growth and a high quality of life, with a wise management of naturalresources, through a participated governance” (Caragliu, Del Bo and Nijkamp, 2011)

Background (2)

The conceptualization of smart cities varies from city to city and from country to country, depending on the level ofdevelopment, willingness to change and resources and aspirations of the city residents:

e.g: Different connotations in India than in Europe, but alsodifferent connotations in Europe! (Nijkamp, 2016)

Different concepts -> different measures-> different no ofindicators (60, 18, 9, 6, etc).

The spatial level of smart city: medium-size (m-s) (pop. between 100,000-500,000 inhabitants) -> after megacities

“These m-s cities which have to cope with the largermetropolitan areas, appear to be less equipped in terms ofcritical mass, resources and organizational capacity” (TU-Wien)

Smart Cities: Research Questions

Can smart cities be the core of the economy (aftermegacities)?

Evolution of smart cities? Strong urbanizationtrends? Unexpected – even chaotic – shocks?

Sustainability? (three main perspectives: economics/environment/social equity)

Are smart cities complex networks?

Complex (non-linear) evolution: are smart citiesalso resilient?

Role of Connectivity and Accessibility?

Smart Cities: RoadMap

Where are we?State of the art: how to measure a smart city? multidimensional analyses/interdisciplinary approaches and links with players/actors

Volume: ‘Measuring the Unmeasurable’ (Nijkamp et al., 1987)

Where are the main problems? - The understanding of the complex evolution of smart cities: ‘ability to transform’ -> the role of resilience and accessibility

What are the most promising perspectives? Methodological/empirical/policy reflections: novel directions

Smart City: Unifying Multidimensional Perspectives

http://www.smart-cities.eu/

TU-Wien: six main dimensions

The dynamics of these dimensions: some can be chaotic or vulnerable in their evolution-> (un)stable impact on the whole smartcity?

How to elaborate and test this?

Synthesis Analysis: two fundamental pillars:

resilience vs accessibility

TU-Vienna: The Emerging Smart Cities

Question: are the emerging smart cities alsoresilient (able to absorb shocks)?

Sweden:

UMEAA, JOENKOEPING, ESKILSTUNA (res &acc)

Germany: ERFURT, GOETTINGEN

KIEL, MAGDEBURG, REGENSBURG, TRIER (res)

Slovakia: BANSKA BYSTRICA, KOSICE, NITRA (res)

Why Resilience and Vulnerability?

Growing popularity in research

Uncertainty due the interconnections betweeneconomic and ecological crises

Batabyal (1998): “the concept of resilience itselfappears to have been rather resilient”

Other fields:

David Whythe (philosopher) (2014): “Robustvulnerability” (A’dam, 26 Sept., 2014)

Andrew Zolli (2010) (entrepreneur) “Resilience: Whythings bounce back”

Resilience and Vulnerability: Research Questions

1. Definitions of the two terms?

2. Several indicators of resilience and vulnerability co-exist; are these differences related to specific fields of research in urban systems? And also: are resilience and vulnerability complementary or conflicting concepts? (Miller et al, 2010)

3. Is a complex urban network, such the smart city, a necessary condition for the emergence or presence of resilience and vulnerability?-> Are smart cities resilient?

4. Can connectivity/accessibility be considered as a useful complementary framework for better understanding and interpreting the evolution of the smart cities – and thus their resilience and/or vulnerability?

1. Definitions

Resilience concept is stemming from ecology: clear definition(s)

↓

Several applications in urban economics; rare applications in transport/communication systems

Vulnerability concept is more ambiguous from the theoretical viewpoint

↓

Rare applications in urban economics; several applications in transport/communication systems

↓

Myriad of interpretations!

2. Resilience and VulnerabilityIndicators

Many different approaches and indicators exist:

Multidisciplinary nature of these two concepts (economic, environmental, energy, digital systems connected to transport)

Context-specific characteristics, aims, etc. (Carlson et al.,

2012)

Even though urban resilience and vulnerability are two states of complex networks – it is difficult to observe and measure them in unambiguous operational terms

3. Complex Networks, Resilience & Vulnerability

Complex networks – and thus connectivity – a sine qua non for the development of resilience and vulnerability in smart cities

Relevance of topological structures of urban/inter-urban networks (proximity to large hubs; hubs not only as attractors, but also as most critical nodes: Barabási,2013; O’Kelly, 2014)

Large amount of unknown interconnectivity in and between networks (connected smart city)

Outcome of these connectivity patterns can be heavily negative, whether a disruption occurs

↓

1step: Identification of the type of topological configuration- As this may suggest a tendency towards a resilient or a

vulnerable urban network (network analysis)

4. Connectivity and Accessibility

Connectivity might be a core element

in the recognition of the evolution of resilience/vulnerability states, as well as in the consequent policy actions towards either the assessment and enhancement of resilience, or

the reduction of vulnerability:

Accessibility more complete indicator (weightingconnectivity by means of socio-economic indicators)

Accessibility as complementary framework

(Non) linear relationship between accessibility and resilience

↓

Basic definitions of resilience and vulnerability

Resilience: Basic Definitions

Engineering Resilience: it refers to the properties of the system near some stable equilibrium. This definition, due toPimm (1984), takes the resilience of a system to be a measure of the speed of its return to equilibrium

Ecological Resilience: it refers to the perturbation/shock that can be absorbed before the system is displaced from one state to another. This definition, due to Holling (1973, 1986, 1992), does not depend on whether a system is at or near some equilibrium (e.g. chaos systems can be resilient)

(see, among others, Gibson, Ostrom, Ahn, 2000; Reggiani et al., 2002)

↓

Connectivity not so explicit in the definition of resilience

Engineering Resilience vs. Ecological Resilience (1)

The 2 Faces of Resilience(Holling 1996)

Attributes (Holling1973)

Focus (Holling1996)

MethodologicalNature (Reggiani et al. 2002)

Measures

Engineering Resilience

Efficiency, constancy, predictability, single equilibrium

Efficiency of function

Strength of the perturbation

Resistance to disturbance and speed of return to equilibrium (O'Neill et al. 1986; Pimm1984)

Ecological Resilience

Persistence, change, unpredictability, multiple locally stable equilibria

Maintenance of function

Size of the attractor orstability domain

Magnitude of disturbance that can be absorbed before the system changes its structure to new equilibria (Walker et al. 1969)

Engineering Resilience vs. Ecological Resilience (2)

Engineering resilience: more feasible under a physical and mathematical point of view compared to ecological resilience

The assessment of a single equilibrium – when dealing with simple dynamic systems – can be achieved by means of differential/difference equations

Ecological resilience refers to extent of shock that a local stable domain is able to absorb before it is induced into some other equilibrium (adaptivity) (for the adaptivityconcept: Levins et al., 1998; Martin, 2012)

Some elements in: Arthur (1990): multiple states among competing technologies; in prey-predator models, etc.

Ecological Resilience

Ecological resilience: More revolutionary concept!

(Holling, 1973)

Computational difficulties may emerge in the presence of multiple equilibria (more than two steady states), or in the presence of a complex network (prey-predator systems; chaos systems (May, 1976); accelerator/multiplier by Samuelson’s business cycle, 1939)

Ecological resilience (and not engineering resilience) can be a property even of a chaotic regime (Reggiani et al., 2002)

↓

The equilibrium/stability notions reinforce the concept of engineering resilience

The uncertainty and unpredictability of the current network phenomena call for the investigation of ecological resilience (more theory is necessary here!)

Dynamic Complexity and Models

Multiple-chains of dynamic logistic-models (e.g. competition /symbiosis/prey-predator models):

x(t+1) = x(t) (K1 - b x(t) –(+)c y(t)) (income)(1)

y(t+1) = y(t) (K2 –(+)e x(t) – f y(t)) (inflows)

If system (2) is expressed in discrete time: unstable, vulnerable and chaotic/unpredictable trajectories may emerge, depending on the parameters’ values and initial conditions, according to the Poincaré-Bendixson Theorem!

System (1) has frequently been utilized in spatial economic analysis as an ‘epidemic’ model for describing technological innovation diffusion, urban growth (e.g., Batty, 2005, Haag, 2005)

↓

Connectivity is ‘hidden’ in the interaction parameters c and e!

Dynamic Models: First Remarks

Chaos models worth to be ‘revisited’

Chaos models can embed both vulnerability and ‘ecological’ resilience elements:

Strange attractors (limited domain) can absorb extreme waves of fluctuations

In chaos models small uncertainties grow exponentially, but these ‘erratic’ and often ‘disruptive’ patterns can leadto new equilibria (ecological resilience): relevance ofparameters’ values!

↓

Chaos models can be revisited by means of ‘ecologicalresilience’

Resilience in Urban/Spatial Systems

Resilience linked to the evolution of spatial economicentities, such as smart cities

Spatial economic is concerned with “the spatial pattern and

interaction of systems of production, distribution or consumption (or more generally, human activities) in a spatial context, including the management, planning and forecasting

of spatial development” (Nijkamp and Ratajczak, 2013)

Relevance of space as action container, as well as the result of human action (social interactions)

Review of about 40 studies (Modica and Reggiani, 2015):

Different resilience interpretations

Different resilience indicators!

Table 3. Different interpretations for spatial economic resilience

Author(s) Year Main Field Definition Kind of

Resilience

Adger 2000 Community

‘the ability of groups or communities to cope with external stresses

and disturbances as a result of social, political and environmental

change’ (p. 347)

Ecological

resilience

Ashby et al. 2008 Local places

‘the extent to which local places and local government are capable

of riding the global economic punches, working within

environmental limits, dealing with external changes, bouncing back

quickly, and having high levels of social inclusion’

Both kinds of

resilience

Bristow 2010 Places

‘Resilience emphasises the importance of healthy, dynamic local

businesses—businesses which are ‘competitive’ and successful—

and yet it does so in a manner which sees virtuous

interrelationships between competition, environment and

distribution’ (p.156)

Ecological

resilience

Bruneau et

al. 2003 Community

‘the ability of social units […]to mitigate hazards, contain the

effects of disasters when they occur, and carry out recovery

activities in ways that minimize social disruption and mitigate the

effects of future earthquakes’ (p. 735)

Engineering

resilience

Coles and

Buckle 2004 Community

‘the total of the individual elements that thorough capacities, skills,

and knowledge are able to participate fully in recovery from

disasters and to cope with wider social, economic and political

communities’ (p. 6)

Engineering

resilience

Davies 2011 Region ‘the capacity of a regional economy to withstand change or to

retain its core functions despite external upheaval’, (p.370)

Both kinds of

resilience

Foster 2007 Region ‘the ability of a region to anticipate, prepare for, respond to and

recover from a disturbance’ (p.14)

Both kinds of

resilience

Hill et al. 2011 Region

‘[regional resilience] is the ability of a regional economy to

maintain or return to a pre-existing state (typically assumed to be

an equilibrium state) in the presence of some type of exogenous

(i.e., externally generated) shock’ (p. 1)

Engineering

resilience

Martin 2012 Region

‘the capacity of a regional economy to reconfigure, that is adapt, its

structure (firms, industries, technologies and institutions) so as to

maintain an acceptable growth path in output, employment and

wealth over time’ (p.10)

Ecological

(adaptive)

resilience

Paton and

Johnston 2001 Community

‘the capability to “bounce back” and to use physical and economic

resources effectively to aid recovery following exposure to hazard

activity’ (p. 158)

Engineering

resilience

Pendall et

al. 2010 City

‘Resilient city would be one that resumed its previous

[economic/population/built form] growth trajectory after a lag’ (p.

73)

Engineering

resilience

Pendall et

al. 2012 Region

‘A resilient region, is one whose governance decisions identify and

anticipate stresses, avoid those that can be avoided, and mitigate

those that cannot, thereby protecting individuals and households

from many harms and helping them recover from others’ (p. 272)

Both kinds of

resilience

Pfefferbaum

et al. 2005 Community

‘the ability of community members to take meaningful, deliberate,

collective action to remedy the effect of a problem, including the

ability to interpret the environment, intervene, and move on’ (p.

349)

Ecological

resilience

Rose and

Liao 2005

Firm and

region

‘inherent ability and adaptive response that enables firms and

regions to avoid maximum potential losses’ (p.76)

Engineering

resilience

Swanstrom 2008 Region

‘a resilient region would be one in which markets and local

political structures continually adapt to changing environmental

conditions and only when these processes fail, often due to

misguided intervention by higher level authorities which stifle their

ability to innovate, is the system forced to alter the big structures’

(p. 10)

Ecological

resilience

Wolfe 2010 Region

‘how a particular economy gets locked into a specific pattern of

growth through a cumulative series of decisions over time. This

perspective is also concerned with how new paths are launched and

regions alter their trajectory of development’ (p.140)

Ecological

resilience

Authors, year Sub-division No. of

vars. Variables Weighting

Graziano,

2013

Infrastructure

Innovation and technology

Socio-economic

19

Broadband services

Electrical network

Energy networks

Rail infrastructure

Application of designs

Application of models

European application of designs

European application of models

Patents

Bank deposits

Business density

Housing

Liquidity ratio

Loans to firms

Non food consumption/total

consumption

Pensions per capita

Population growth rate

Return on equity

Value added per capita

Factor

analysis

Martin,

2012 Socio-economic 1 Employment -

Resilience

Alliance,

2009

Infrastructure

Natural environment

Socio-economic

10

Water table depth

Water table equilibrium

Biodiversity measure

River condition

Riverine ecosystem condition

Soil acidity

Water infrastructure

Balance among values held

Farm income

Presence of high multiplier economic

sectors

Equal

weight

University at

Buffalo

Regional

Institute,

2011

Community

Socio-economic 12

Civic infrastructure

Home ownership

Without disability

Business environment

Economic diversification

Educational attainment

Health insured

Income equality

Metropolitan stability

Regional affordability

Out of poverty

Voter participation

Equal

weight

Spatial Economic Resilience: Summary(Review Paper by Modica and Reggiani, 2015)

Recessionary, industry and disaster shocks

Both engineering and ecological/adaptivity resilience of a region/community/urban area

Multeplicity of applications in USA, UK and EU: mostlyat regional level, despite a few exceptions…;-)

Role of the scale of analysis: local/urban vs region

Different socio-economic indicators (mobilityfactors ara rarely present)

Different methods and measures (econometric models, regression analyses, performance indices)

Rare connectivity considerations ->

Spatial Economic Vulnerability?

Spatial Economic Vulnerability (1)

No clear definition (origins from political ecology)

Vulnerability: more negative connotation, as the overall reduction of a system’s performance as a consequence of dynamic factors stressing the system

↓

“It is an oversimplification to treat resilience as the converse of vulnerability” (Seeliger and Turok, 2013)

↓

Vulnerability is more about the susceptibility of the urban system or any of its constituents to harmful external pressures;

Resilience concerns more the response of the urban system: “its elasticity or capacity to rebound after a shock,

indicated by the degree of flexibility, persistence of key functions,

or ability to transform (Seeliger and Turok, 2013)

Spatial Economic Vulnerability (2)

Vulnerability – analogously to resilience – depends on factors such as nature of the system, and type of shock, which vary for different spatial and socio-economic contexts

Developmental factors including poverty, health status, economic inequality, and types of governance may constitute vulnerability (Brooks et al., 2005)

These factors are also included in various resilience indicators…

↓

Links and differences between resilience and vulnerability in urban economics appear to be

ambiguous

Resilience in Spatial Economics: Follow-up

As anticipated, the majority of the applications in spatialeconomics do not take into account dynamics and connectivity

But (smart) cities are connected (virtually, physically, intra-, inter-)!

↓

Zipf’s Law Coeff., Rank-size Rule and Gibrat’s law (based on population) are linked to connectivity structures (Reggiani

and Nijkamp, EPB, 2015)

↓

New theoretical steps: More Efforts on the Role of the Parameters’ Values, also by means of dynamic models

What about Transport (Communication) Resilience/Vulnerability in urban systems?

Transport Resilience & Vulnerability

Transport & communication’s evolution has strong feedback effects on spatial economicdevelopments (positive and negative externalities)

Our modern society strongly depends on large scale infrastructure networks: “Recent disasters have vividly demonstrated the importance and vulnerability of our transportation and critical infrastructure systems -

local disturbance has led to the global failure or

interruption of systems” (Nagurney, 2011)

Relevance of the identification of the potential ‘risk

areas’ in a early stage

Relevance not only of shock entities, but also of propagation of shocks -> Vulnerability!

Transport Resilience:Interpretations

SURVEY OF 33 ARTICLES (Reggiani et al., TRA, 2015):

↓

Adoption of similar concepts :

Robustness (Engineering resilience):

“The system will retain its systems structure (function) intact (remain unchanged or nearly unchanged) when exposed to perturbations” (Holmgren, 2007)

A network is “robust if the network performance stays close to the original level” (Nagurney and Qiang, 2012)

Reliability (Ecological resilience):

Operability of the network under strenuous conditions

Ability to continue to function after shocks (Husdal, 2005)

Demand side: user’s behavioural response (Van Exel and

Rietveld, 2001)

Transport Resilience: Applications/Simulations

Rare empirical applications of resilience in transport:

Change in modal split after terrorist attack on the London subway and bus bombing in 2005 (Cox et al., 2011)

Use of network equilibrium /traffic assignment models

Several simulations of network robustness/reliability:

Hub reliability of telecommunication networks in the USA (Kim and O’Kelly, 2009)

Robustness of the Dutch road network (Knoop et al., 2012) and Snelder et al., 2012 )

Reliability of the Dutch railway system (Vromans et al., 2006)

Network robustness and performance models, in the context of financial (merger and acquisitions) and logistic networks (Nagurney and Qiang, 2012)

Transport Vulnerability:Interpretations

From network reliability to the impact of variability in the factors that affect the urban system (Clark and Watling, 2005)

Vulnerability of reliability: vulnerability of connectivity/capacityreliability (Watling and Balijepalli, 2012)

Reliability focuses on transport network performance, in terms of probability; vulnerability focuses on network weaknesses or failure, irrespective of the probability of failure (Taylor, 2008)

“Vulnerability is primarily a pre-disaster condition; resilience is the outcome of a post-disaster response” (Rose, 2009)

Vulnerability as attention to potential weak points (susceptibility toshocks)

Transport Vulnerability: Applications/Simulations (1)

More empirical works in transport vulnerability than in transport resilience

Vulnerability studies concern mainly road infrastructure networks, given the extensive road coverage (Berdica, 20012;

Jenelius et al., 2006 – Swedish School by Lars-Goran Mattsson)

Network vulnerability measured as: reduction in road network serviceability, function of recovery time (Cats &

Jenelius, 2014; Jenelius et al., 2006; Jenelius & Mattsson, 2012)

Network vulnerability as ‘reduced accessibility’ (Berdica

2002; Kondo et al., 2012; Taylor et al., 2006)

Transport Vulnerability: Applications/Simulations (2)

Applications/Simulations on real case studies:

Montpellier’s road network (Appert and Chapelon,2013)

Stockholm public transport sytems (Cats and Jenelius, 2014)

Road network of Northern Sweden (Jenelius et al., 2006)

Swedish Road network (Jenelius and Mattsson, 2012

Delft and Rotterdam road network (Knoop et al., 2012)

Ohio interstate highway (Maticziw and Murray, 2007)

Kobe urban area road network (Nagae et al., 2012)

Supply chain (Qiang and Nagurney, 2012)

Rural locations in south East Australia (Taylor and Susilawati, 2012

Chinese railyway network (Ip and Wang, 2011)

Swedish commuting network (Osth and Reggiani, 2014)

Emilia Romagna-network (Rupi et al., 2014)

Transport Vulnerability: First Remarks

Transport vulnerability: richer analysis than transport resilience

Different interpretations (decrease of network performance, etc.)

Different approaches (generalized travel costs, optimizationmodels, risk analysis, weighted multi-criteria decision approach,network weakeness indicators, etc.)

Analogously to resilience in economics, applications are ratherrecent

Relevance of ‘Propagation of shocks’ in a network

First Concluding Remarks

Vulnerability: richer analysis in transport than in spatial economics!

Resilience: richer analysis in spatial economics than in transport!

↓

More studies on the links between these two concepts and fields are necessary

Again: Measuring the Unmeasurable...

Multi-disciplinary approaches, for example..:

Chaos models linked to network analysis and contagion models

Theoretical and Empirical Perspectives:

Theoretically: Chaos models/properties might berevisited in a positive perspective, by means of ecologicalresilience

- Small changes -> higher effects which are notnecessarily negative (as we considered in the past)

- The new equilibria - eventhough arising on the distruction of the previous ones – can create newopportunities (‘Old concept’ from Socrates: Chaos as the Divinity…)

- New theoretical efforts

Empirically: (Dynamics of) Resilience vs Accessibility in smart cities

Accessibility

Accessibility more complete than connectivity (economic weight)!

Accessibility: Σj Dj f(cij) (1)

f(cij) = impedance/deterrence (cost) function, which embeds theaggregate behaviour (by means of the cost-sensitivity parameters) andthe connectivity structure ; Dj is the economic weight (e.g. workplaces)

Accessibility can identify the potential “risk areas” (least accessible) (Berdica, 2002; Jenelius and Mattsson, 2012; Taylor et al, 2006)

Accessibility might be an instrument for enhancing resilience

↓

Application to Municipalities in Sweden(Osth, Reggiani and Galiazzo, 2015, CEUS)

Measuring Resilience vs Accessibility in Urban Areas in Sweden(Osth, Reggiani, Galiazzo, 2015)

RCI (Resilience Capacity Index) (Kathryn A.

Foster; Cowell, 2013): http://brr.berkeley.edu/rci/

12 Socio-economic (not mobility) indicators

Three components (at municipality level in Sweden)• Economic Capacity (4 indicators)

• income equality (income distr. Gini), economic diversity (deviation from national industrial mix), affordability (housing market – related to income in SE), and business environment (ranking of local business climate)

• Socio-demographic capacity (4 indicators)

• Educational attainment (% 25+ with bachelor’s degree), ’Without disability’ (share of pop without need of care), ’out of poverty’ (% pop above the poverty-line) and health insured (sick leave in Sweden)

• Community connectivity capacity (4 indicators)

• Civic infrastructure (share of ‘NGO’ workers), metropolitan stability (Stability of pop), Homeownership (residing in owned home), and Voter participation (share voting)

Measuring Accessibility in Sweden

Accessibility as potential of opportunity for interaction:

Ai = Σj Dj f (γ, dij) (Hansen, 1959)

Accessibility at location i = the sum of surroundingopportunities/workplaces j, under influence ofcost/time/distance for reaching j

Use of a power-decay in a doubly-constrained spatial interaction model, which has proven to be good for the analysis of accessibility in the 290 Swedishmunicipalities (Osth, Reggiani and Galiazzo, 2015)

All statistics are computed at a municipality level

Resilience vs Accessibility: The Relationships

Clustering of Resilience and Accessibility in Sweden (2)

Concluding Remarks (1)

Experiments in Sweden show that socio-economic resilience and accessibility are linked:

Resilient smart centres are the most accessible

Suburb and commuting municipalities often have poor resilience ranks – but high accessibility (!)

Probably accessibility will enhance resilience of these locations in the future

Dynamics: analyses in the coming years/different countries such as Slovakia (how is accessibility)?

Regional GDP per capita in the EU-2011

SLOVAKIA 12 800

Bratislavský kraj 31 500

Západné Slovensko 12 200

Stredné Slovensko 10 000

Východné Slovensko 8 700

SWEDEN 40 800

Stockholm 56 200

……

Norra Mellansverige 34 400

(Italy: Lombardia -> 33 900)

Concluding Remarks (2)

Socio-economic resilience – in conjunction with

accessibility analyses – might provide ‘stability results’ on (smart) cities evolution

Policy implications

Some locations are worse of than others:

• Low socio-economic resilience is less of a problem in locations with high accessibility

• Low socio-economic resilience and low accessibility can be a lethal combination

• High resilience and low accessibility might be problematic in the future

Preventive action should be targeting urban areas with low socio-economic resilience and low accessibility

Conclusions: From Resilience to Vulnerability to Reality....

(Smart) Cities as Evolutionary Accessible Networks

Two joint (Synthetic) pillars in the smart cities evolution:

resilience and accessibility

Different indicators at different spatial levels -> need for more reflections on the measurement of resilience/vulnerability: multidimensional analysis

For more operability, more theoretical efforts on the formalizationof these concepts are also necessary:

- e.g. Entropy vs Zipf/Gibrat’s law vs. Dynamic/Chaos models, in the light of resilience

- Role of parameters’ values/behavioural patterns

Multi-disciplinary approaches: Spatial/Urban Economics vs Transport Economics vs Network & Social Sciences...

Special Issues

Different perspectives on Resilience & Vulnerability:

Caschili, Reggiani, Medda (2015), Special Issue on “Resilience and Vulnerability in Spatial Economic Networks”, Networks and Spatial Economics.

Caschili, Medda, Reggiani (2015), Special Issue on “Resilience and Vulnerability in Transport Networks”, Transport Research A.↓

Unifying framework necessary, also jointly withaccessibility:

Reggiani, Thill, Martin (2016) Special issue on “Resilience, Vulnerability and Accessibility”, Transportation

Thank you,

for your ‘resilient’ attention!

Questions and commentsare welcome

Complexity

“Complexity has turned out to be very difficult to define” (‘From Complexity to Perplexity’: Heylighen, 1996)

31 Definitions of complexity and associated concepts

From Latin: Complexus means ‘entwined’, ‘twisted together’

Oxford Dictionary: ‘Complex’ if it is ‘made of (usually several) closely connected parts’

The term ‘complexity’ embeds both the assemblage of different units in a system and their intertwined dynamics

↓In other words, the term ‘complexity’ is strictly related

to the concept of networks

Spatial Economic Networks

Net-works: ‘operations via nets’: NECTAR (1990)

Spatial (economic) networks: ordered connectivity structure

for spatial communication and transportation which is characterized

by the existence of main nodes which act as receivers or senders

(push and pull centres), and which are connected by means of

corridors and edges (Nijkamp and Reggiani, 1998)

↓

The relevance of the dynamic function of the (spatial) networks via organized linkage patterns is embedded in this

definition

Spatial networks are networks for which the nodes are located in a

space equipped with a metric (Barthélemy, 2010)

Complexity and Spatial Networks

Complexity of Space-Time Phenomena

“Large number of parts that interact in a nonsimple way” (Simon,1962)

“The primary idea of complexity concerns the mapping of a system’s non-intuitive behaviour, particularly the evolutionary patterns of connections among interacting components of a system whose long-run behaviour is hard to predict” (Casti, 1979)

Static vs. Dynamic Complexity

Static Complexity: network configuration, where the components are put

together in an interrelated and intricate way (high dimension of the network,

high no. of hierarchical subsystems, type of the connectivity patterns etc.)

Dynamic Complexity: dynamic (random) network behaviour governed by non-linearities in the interacting components (computational complexity and the evolutionary complexity; for the latter measure: chaos and evolutionary models)