collective spatial actions: policy and planning as emergent properties of human interactions...
TRANSCRIPT
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Collective Spatial Actions: Policy and Planning as Emergent Properties of Human Interactions
Gilberto CâmaraEarth System Science Center, INPE
Licence: Creative Commons ���� By Attribution ���� Non Commercial ���� Share Alikehttp://creativecommons.org/licenses/by-nc-sa/2.5/
Las Navas 2010: Cognitive and Linguistic Aspects of Geographic Space
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What cooperation can achieve...
http://www.youtube.com/watch?v=0HrjevD2vhk&feature=related
Those were the days…
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Collective spatial action: volunteered GI
Are Brazilians less cooperative? Less tech-savvy? Does google solve their problems? Are they happy with their public data?
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Collective spatial action: pedestrian modelling
Batty, “Agent-Based Pedestrian Modelling”, in: Advanced Spatial Analysis, ESRI Press, 2003.
Notting Hill Carnival (London)
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Collective spatial action: deforestation
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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
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The fundamental question of our time
How is the Earth’s environment changing, and what are the consequences for human civilization?
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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.
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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).
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source: Global Land Project Science Plan (IGBP)
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Impacts of global land change
More vulnerable communities are those most at risk
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Nature: Physical equations Describe processes
Society: Decisions on how to Use Earth´s resources
We need spatially explicit models to understand human-environment interactions
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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?
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Clocks, clouds or ants?
Clocks: deterministic methods
Clouds: statistical distributions
Ants: emerging behaviour
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Modelling collective spatial actions: the complex systems approach
1. Situated individuals (persons, groups, agents)2. Interaction rules - communication3. Decision rules - actions4. Properties of space
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Conections and flows are universal
Yeast proteins(Barabasi and Boneabau,
SciAm, 2003)
Scientists in Silicon Valley(Fleming and Marx, Calif Mngt
Rew, 2006)
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Information flows generate cooperation
White cells attact a cancer cell (cooperative activity)
National Cancer Institute, EUA http://visualsonline.cancer.gov
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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.
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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/
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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
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Agent-Based Modelling: Computing approaches to complex systems
Goal
Environment
Representations
Communication
ActionPerception
Communication
Gilbert, 2003
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Four types of spatial agents
Natural agents, artificial environment
Artificial agents, artificial environment Artificial agents, natural environment
Natural Agents, natural environment
source: Couclelis (2001)
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“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
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“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)
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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
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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).
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Social Simulation: SegregationSegregation is an outcome of individual choices
But high levels of segregation indicate mean that people are prejudiced?
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Schelling’s Model of Segregation
...ghettos are formed!
If people require more than 1/3 of neighbours to be of the same kind...
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Game Theory
Provides a standard taxonomy for analyzing strategic interactions.
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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.
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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.
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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.
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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…”
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Tragedy of the Commons?
Everybody’s property is nobody’s property
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Is the tragedy of the commons inevitable?
Experiments show that cooperation emerges if virtuous interactions exist
source: Novak, May and Sigmund (Scientific American, 1995)
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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)
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Common pool resources(Elinor Ostrom)
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The ultimate common pool resource
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Governing the commons
[Ostrom, Science, 2005]
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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.
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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
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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
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Scientists and Engineers Photo 51(Franklin, 1952)
Scientists build in order to study
Engineers study in order to build
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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.
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TerraME: Computational environment for developing nature-society models
Cell Spaces
Support for cellular automata and agents
TerraME: Modular modelling tool[Carneiro, 2006]
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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]
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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?
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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
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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
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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
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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
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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
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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
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Modeling results 97 to 2006
Observed 97 to 2006
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Conclusion
GlScience can make a significant contribution to global change research, supporting spatially explicit models of human-environment interactions with reasoned scientific basis