collective spatial actions: policy and planning as emergent properties of human interactions...

Collective Spatial Actions: Policy and Planning as Emergent Properties of Human Interactions

Gilberto CâmaraEarth System Science Center, INPE

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Las Navas 2010: Cognitive and Linguistic Aspects of Geographic Space

What cooperation can achieve...

http://www.youtube.com/watch?v=0HrjevD2vhk&feature=related

Those were the days…

Collective spatial action: volunteered GI

Are Brazilians less cooperative? Less tech-savvy? Does google solve their problems? Are they happy with their public data?

Collective spatial action: pedestrian modelling

Batty, “Agent-Based Pedestrian Modelling”, in: Advanced Spatial Analysis, ESRI Press, 2003.

Notting Hill Carnival (London)

Collective spatial action: deforestation

Fossil fuel

Land use change

10

8

6

4

2

1960 20101970 1990 20001980

CO2 e

mis

sion

s (P

gC y

-1) 8.7

1.2

9.9 PgC

12% of total

Le Quéré et al. 2009, Nature-geoscience, 2009

Collective spatial action: global change

The fundamental question of our time

How is the Earth’s environment changing, and what are the consequences for human civilization?

We need cooperation at a global level…

By the year 2050...9 billion people: 6 billion tons

of GHG and 60 million tons of urban pollutants.

Resource-hungry: We will withdraw 30% of available fresh water.

Risky living: 80% urban areas, 25% near earthquake faults, 2% in coast lines less than 1 m above sea level.

An explicit spatial problem in global change: land change

“Land-change science has emerged as a foundational element of global environment change and sustainability science” (Rindfuss et al, “Developing a science of land change”, PNAS, 2004).

source: Global Land Project Science Plan (IGBP)

Impacts of global land change

More vulnerable communities are those most at risk

Nature: Physical equations Describe processes

Society: Decisions on how to Use Earth´s resources

We need spatially explicit models to understand human-environment interactions

Slides from LANDSAT

1973 1987 2000

images: USGS

Modelling Human-Environment Interactions

How do we decide on the use of natural resources?

What are the conditions favoring success in resource mgnt?

Can we predict changes resulting from human decisions?

What GIScience techniques and tools are needed to model human-environment decision making?

Clocks, clouds or ants?

Clocks: deterministic methods

Clouds: statistical distributions

Ants: emerging behaviour

Modelling collective spatial actions: the complex systems approach

1. Situated individuals (persons, groups, agents)2. Interaction rules - communication3. Decision rules - actions4. Properties of space

Conections and flows are universal

Yeast proteins(Barabasi and Boneabau,

SciAm, 2003)

Scientists in Silicon Valley(Fleming and Marx, Calif Mngt

Rew, 2006)

Information flows generate cooperation

White cells attact a cancer cell (cooperative activity)

National Cancer Institute, EUA http://visualsonline.cancer.gov

Complex adaptive systems

Systems composed of many interacting parts that evolve and adapt over time.

Organized behavior emerges from the simultaneous interactions of parts without any global plan.

Is computing also a natural science?

“Information processes and computation continue to be found abundantly in the deep structures of many fields. Computing is not—in fact, never was—a science only of the artificial.” (Peter Denning, CACM, 2007).

http://www.red3d.com/cwr/boids/

Computing is also a natural science

Computing studies information flows in natural systems...

...and how to represent and work with information flows in artificial systems

Agent-Based Modelling: Computing approaches to complex systems

Goal

Environment

Representations

Communication

ActionPerception

Communication

Gilbert, 2003

Four types of spatial agents

Natural agents, artificial environment

Artificial agents, artificial environment Artificial agents, natural environment

Natural Agents, natural environment

source: Couclelis (2001)

“Agent-based modeling meets an intuitive desire to explicitly represent human decision making. (…)

However, by doing so, the well-known problems of modeling a highly complex, dynamic spatial environment are compounded by the problems of modeling highly complex, dynamic decision-making. (…)

The question is whether the benefits of that approach to spatial modeling exceed the considerable costs of the added dimensions of complexity introduced into the modeling effort. The answer is far from clear and in, my mind, it is in the negative. But then I am open to being persuaded otherwise ”.

(from “Why I no longer work with agents”, 2001 LUCC ABM Workshop)

Some caution necessary...

Helen Couclelis

“Complexity is more and more acknowledged to be a key characteristic of the world welive in and of the systems that cohabit our world. It is not new for science to attempt tounderstand complex systems: astronomers have been at it for millennia, and biologists,economists, psychologists, and others joined them some generations ago. (…)

If, as appears to be the case, complexity (like systems science) is too general a subjectto have much content, then particular classes of complex systems possessing strongproperties that provide a fulcrum for theorizing and generalizing can serve as the fociof attention.” (from “The Sciences of the Artificial”, 1996)

Some caution necessary...

Herbert Simon (1958)

Nature: Physical equations Describe processes

Society: Decisions on how to Use Earth´s resources

Our spatially explicit models need good social theories to guide them

We need social theories to understand human-environment interactions Survey

Moran, “Environmental Social Science: Human-Environment Interactions and Sustainability” (2010)

Social simulationSchelling, “Micromotives and macrobehavior” (1978).Batty, “Cities and complexity” (2005).

Game theoryvon Neumann and Morgenstern, “Theory of games and economic behavior” (1944)Nash, "Equilibrium points in n-person games“ (1950).

Evolutionary dynamicsMaynard Smith, ”Evolution and the theory of games” (1982)Axelrod, “Evolution of cooperation” (1988).Novak, “Evolutionary dynamics: exploring the equations of life” (2005).

Institutional analysisOstrom, “Governing the commons” (1990).

Social Simulation: SegregationSegregation is an outcome of individual choices

But high levels of segregation indicate mean that people are prejudiced?

Schelling’s Model of Segregation

...ghettos are formed!

If people require more than 1/3 of neighbours to be of the same kind...

Game Theory

Provides a standard taxonomy for analyzing strategic interactions.

Prisoners’ DilemmaTwo suspects are caught and put in different rooms (no

communication). They are offered the following deal:1. If both of you confess, you will both get 3 years in prison2. If you confesses whereas the other does not, you will get 1

year and the other gets 5 years in prison .3. If neither of you confess, you both will get 2 years in prison.

The stag-hunt game: conflict between safety and social cooperation

Two hunters want to kill a stag. Success is uncertain and, if it comes, require the efforts of both. On the other hand, either hunter can forsake his partner and catch a hare with a good chance of success.

Tragedy of the Commons

Assume a common-property resource (exclusion is difficult and joint use involves subtractability) with no property rights. (Pasture open to all)

Each herdsman tries to keep as many sheep as possible on the commons. Each tries to maximize gain.

Add those sheep!

The rational herdsman concludes that he should add another sheep. And another…And another…And so does each herdsman

“Ruin is the destination toward which all men rush, each pursuing his own best interest…”

Tragedy of the Commons?

Everybody’s property is nobody’s property

Is the tragedy of the commons inevitable?

Experiments show that cooperation emerges if virtuous interactions exist

source: Novak, May and Sigmund (Scientific American, 1995)

How can cooperation happen?Nowak MA (2006). “Five rules for the evolution of cooperation” Science 314:1560-1563(most highly cited multidisciplinary paper – ISI, 1st quarter 2010)

"I would lay down my life for two brothers or eight cousins“ (J.B.S. Haldane)

Common pool resources(Elinor Ostrom)

The ultimate common pool resource

Governing the commons

[Ostrom, Science, 2005]

Governing the commons: Ostrom´s conditions

1. Clearly defined boundaries

2. Congruence between appropriation and provision rules and local conditions

3. Collective-choice arrangements:

4. Monitoring and graduated Sanctions.

5. Conflict-resolution mechanisms

6. Minimal recognition of rights to organize.

7. Organized governance activities.

Agen

t

Spa

ce

Space Agent

Benenson and Torrens, “Geographic Automata Systems”, IJGIS, 2005(but many questions remain...)

Modelling collective spatial actions: potential GIScience contributions

Modelling collective spatial actions: some potential GIScience contributions

1. Situated individuals (persons, groups, agents): spatial cognition, spatial analysis, scale in GIS

2. Interaction rules: semantics of communication, mobile computing

3. Decision rules: ontology [of actions, events and processes], spatial analysis

4. Properties of space: spatial analysis, spatial databases, scale, uncertainty, vagueness

Scientists and Engineers Photo 51(Franklin, 1952)

Scientists build in order to study

Engineers study in order to build

Spatially-explicit land change models

Explain past changes, through the identification of determining factors of land use change;

Envision which changes will happen, and their intensity, location and time;

Assess how choices in public policy can influence change, by building different scenarios considering different policy options.

TerraME: Computational environment for developing nature-society models

Cell Spaces

Support for cellular automata and agents

TerraME: Modular modelling tool[Carneiro, 2006]

TerraME´s components

Describe spatial structure

1:32:00 Mens. 11.

1:32:10 Mens. 32.

1:38:07 Mens. 23.

1:42:00 Mens.44.. . .return value

true

1. Get first pair 2. Execute the ACTION

3. Timer =EVENT

4. timeToHappen += period

Describe temporal structure

Newly implanted

Deforesting

Slowing down

latency > 6 years

Iddle

Year of creation

Deforestation = 100%

Describe rules of behaviour Describe spatial relations

[Carneiro, 2006]

Governing the commons?

~230 scenes Landsat/year

Deforestation in Amazonia

How could Brazil reduce deforestation from 27.000 km2 to 7.000 km2 in 5 years?

Institutional analysis in Amazonia

Old Settlements(more than

20 years)

Recent Settlements(less than 4

years)

Farms

Settlements 10 to 20 anos

Source: Escada, 2003

Identify different agents and try to model their actions

Amazonia: multiscale analysis of land change and beef and milk market chains with TerraME

Deforestation

Forest

Non-forest

Clouds/no data

INPE/PRODES 2003/2004:

São Felix do Xingu

Create pasture/Deforest

Speculator/large/small

bad land management

money surplus

Subsistenceagriculture

Diversify use

Manage cattle

Move towardsthe frontier

Abandon/Sellthe property

Buy newland

Settlement/invaded land

Sustainability path(alternative uses, technology)

Sustainability path (technology)

Agents example: small farmers in Amazonia

Create pasture/plantation/

deforest

Speculator/large/small

money surplus/bank loan

Diversify use

Buy newland

Manage cattle/plantation

Buy calvesfrom small

Buy landfrom small

farmers

Agents example: large farmers in Amazonia

Land use Change model

Beef and milk market chain model

Small farmers

Medium and largefarmers

Land use Change model

Small farmers

Medium and largefarmers

Landscapemetrics model

Pasture degradation

model

Several workshops in 2007 to define model rules and variables

Landscape model: different rules for two main types of agents

Landscape model: different rules of behavior at different partitions which also change in time

FRENTE

MEIO

RETAGUARDA

Forest

Not ForestDeforest

River

FRONT

MIDDLE

BACK

SÃO FÉLIX DO XINGU - 2006

Modeling results 97 to 2006

Observed 97 to 2006

Conclusion

GlScience can make a significant contribution to global change research, supporting spatially explicit models of human-environment interactions with reasoned scientific basis