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Modelling Human-Environment Interactions with TerraME Gilberto Câmara (INPE) Tiago Carneiro (UFOP) Pedro Andrade Neto (INPE) Licence: Creative Commons.

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Presentation on theme: "Modelling Human-Environment Interactions with TerraME Gilberto Câmara (INPE) Tiago Carneiro (UFOP) Pedro Andrade Neto (INPE) Licence: Creative Commons."— Presentation transcript:

1 Modelling Human-Environment Interactions with TerraME Gilberto Câmara (INPE) Tiago Carneiro (UFOP) Pedro Andrade Neto (INPE) Licence: Creative Commons ̶̶̶̶ By Attribution ̶̶̶̶ Non Commercial ̶̶̶̶ Share Alike Symposium in Modelling of Terrestrial Systems and Evolution, Ouro Preto, 2011

2 The fundamental question of our time fonte: IGBP How is the Earth’s environment changing, and what are the consequences for human civilization? By ,5 billion people: 6 billion tons of GHG and 60 million tons of urban pollutants. Resource-hungry: We will withdraw 30% of available fresh water.

3 Planetary Boundaries

4 Global Change Where are changes taking place? How much change is happening? Who is being impacted by the change? What is causing change? Human actions and global change photo: A. Reenberg photo: C. Nobre

5 Is Computing a natural science? “Computer science is not actually a science. It does not study natural objects. It’s about getting to do something, rather than dealing with abstractions.” (Richard Feynman)

6 Is Computing a natural science? “Computing is the study of natural and artificial information processes.” (Peter Denning)

7 What’s in an image?

8 Web map (Barabasi) (could be brain connections or between scientists)

9 Information flows in nature Ant colonies live in a chemical world

10 Conections and flows are universal Yeast proteins (Barabasi and Boneabau, SciAm, 2003) Scientists in Silicon Valley (Fleming and Marx, Calif Mngt Rew, 2006)

11 Information flows generate cooperation White cells attact a cancer cell (cooperative activity) National Cancer Institute, EUA

12 Tragedy of the Commons? Everybody ’ s property is nobody ’ s property (Hardin)

13 Is the tragedy of the commons inevitable? Experiments show that cooperation emerges if virtuous interactions exist source: Novak, May and Sigmund (Scientific American, 1995)

14 Common pool resources (Elinor Ostrom)

15 The ultimate common pool resource

16 Governing the commons: institutional arrangments [Ostrom, Science, 2005]

17 Elinor Ostrom on governing the commons “Neither the state nor the market is uniformly successful in enabling individuals to sustain long-term, productive use of natural resource systems.”

18 Building information models Territory (Geography) Money (Economy) Culture (Antropology) Modelling (Computing) Connect expertise from different fields Make the different conceptions explicit

19 Slides from LANDSAT 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 anticipate changes resulting from human decisions? What techniques and tools are needed to model human- environment decision making?

20 Nature: Physical equations Describe processes Society: Decisions on how to Use Earth´s resources We need spatially explicit models to understand human-environment interactions

21 f ( I t+n ). FF f (I t )f (I t+1 )f (I t+2 ) Dynamic Spatial Models “A dynamical spatial model is a computational representation of a real-world process where a location on the earth’s surface changes in response to variations on external and internal dynamics on the landscape” (Peter Burrough)

22 Cells (objects) Question #1 for human-environment models Fields What social theories and concepts are required for human- environment models? Can they be translated into information systems?

23 Resilience Concepts for spatial dynamical models Events and processes

24 degradation Concepts for spatial dynamical models vulnerability

25 Human-environmental models need to describe complex concepts (and store their attributes in a database) and much more… biodiversity Concepts for spatial dynamical models sustainability

26 We need social theories to understand human- environment interactions  Social simulation Schelling, “Micromotives and macrobehavior” (1978). Batty, “Cities and complexity” (2005).  Game theory von Neumann and Morgenstern, “Theory of games and economic behavior” (1944) Nash, "Equilibrium points in n-person games“ (1950).  Evolutionary dynamics Maynard Smith, ”Evolution and the theory of games” (1982) Axelrod, “Evolution of cooperation” (1988). Novak, “Evolutionary dynamics: exploring the equations of life” (2005).  Institutional analysis Ostrom, “Governing the commons” (1990).

27 Game Theory GT is an analytical tool for social sciences that is used to model strategic interactions or conflict situations. Strategic interaction: When actions of a player influence payoffs to other players

28 Where can we use Game Theory? Any situation that requires us to anticipate our rival’s response to our action is a potential context for GT. Economics, Political science, Biology

29 What models are needed to describe human actions? Question #2 for human-environment models

30 Clocks, clouds or ants? Clocks: deterministic equations Clouds: statistical distributions Ants: emerging behaviour

31 Statistics: Humans as clouds Establishes statistical relationship with variables that are related to the phenomena under study Basic hypothesis: stationary processes y=a 0 + a 1 x 1 + a 2 x a i x i +E Fonte: Verburg et al, Env. Man., Vol. 30, No. 3, pp. 391–405

32 Amazônia in 2007 x All Variables Variables Transportation (11) Distance Markets(7) Demography (3) Tecnology (2) Environmental (20) Public Policy(8) Market (8) Agrarian Structure(6)

33 Agents as basis for complex systems Agent: flexible, interacting and autonomous An agent is any actor within an environment, any entity that can affect itself, the environment and other agents.

34 Agent Space Space Agent Benenson and Torrens, “Geographic Automata Systems”, IJGIS, 2005 (but many questions remain...) Modelling collective spatial actions

35 Question #3 for human-environment models What types of spatial relations exist in nature-society models?

36 Rondonia Natural space is (usually) isotropic Societal space is mostly anisotropic

37 Which spatial objects are closer? Societal spaces are connected Which cells are closer? [Aguiar et al., 2003]

38 Euclidean spaceOpen network Closed network D2 D1 Requirement #3 for human-environment models: express connections explicitly [Aguiar et al., 2003]

39 Question #4 for human-environment models How do we combine independent multi-scale models with feedback?

40 Models: From Global to Local Athmosphere, ocean, chemistry climate model (200 x 200 km) Atmosphere only global climate model (50 x 50 km) Regional climate model (10 x 10 km) Hydrology, Vegetation Soil Topography (1 x 1 km) Regional land use change Socio-economic adaptation (e.g., 100 x 100 m)

41 Question #5 for human-environment models Small Farmers Medium-Sized Farmers photos: Isabel Escada How can we express behavioural changes in human societies? When a small farmer becomes a medium-sized one, his behaviour changes

42 Societal systems undergo phase transitions Newly implanted Deforesting Slowing down latency > 6 years Deforestation > 80% Small Farmers Iddle Year of creation Deforestation = 100% Deforesting Slowing down Iddle Year of creation Deforestation = 100% Deforestation > 60% Medium-Sized Farmers photos: Isabel Escada

43 TerraLib: spatio-temporal database as a basis for innovation Visualization (TerraView) Spatio-temporal Database (TerraLib) Modelling (TerraME) Data Mining(GeoDMA) Statistics (aRT) G. Câmara et al.“TerraLib: An open-source GIS library for large-scale environmental and socio-economic applications”. In: B. Hall, M. Leahy (eds.), “Open Source Approaches to Spatial Data Handling”. Berlin, Springer, 2008.

44 TerraME: Computational environment for developing human-environment models Cell Spaces Support for cellular automata and agents [Carneiro, 2006]

45 Spatial structure in TerraME: Cell Spaces integrated with databases

46 TerraME´s approach: Modular components Describe spatial structure 1:32:00Mens :32:10Mens :38:07Mens :42:00Mens 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 behaviourDescribe spatial relations [Carneiro, 2006]

47 TerraME: multi-scale modelling using explicit relationships Generalized proximity matrices express explicit spatial relationships between individual objects in different scales up-scaling Scale 1 Scale 2 father children [Moreira et al., 2008] [Carneiro et al., 2008]

48 To Agent Cell a b a b c c Cell Agent From GPM: Relations between cells and agents [Andrade-Neto et al., 2008]

49 TerraME uses hybrid automata to represent phase transitions State A Flow Condition State B Flow Condition Jump condition A hybrid automaton is a formal model for a mixed discrete continuous system (Henzinger, 1996) Hybrid Automata = state machine + dynamical systems

50 Hybrid automata: simple land tenure model STATEFlow ConditionJump ConditionTransition SUBSISTENCEDeforest 10% of land/yearDeforest > 60%CATTLE Extensive cattle raisingLand exhaustionABANDONMENT Forest regrowthLand revisionRECLAIM Public repossessionLand registrationLAND REFORM Land distributionFarmer gets parcels SUBSISTENCE Deforest 20%/year Farmer gets parcel deforest>=60% Land exhaustion CATTLE Extensive cattle raising ABANDONMENT Regrowth RECLAIM Public repossession Land revision LAND REFORM redistribution Land registration

51 Lua and the Web Where is Lua? Inside Brazil  Petrobras, the Brazilian Oil Company  Embratel (the main telecommunication company in Brazil)  many other companies Outside Brazil  Lua is used in hundreds of projects, both commercial and academic  CGILua still in restricted use until recently all documentation was in Portuguese TerraME Programming Language: Extension of LUA LUA is the language of choice for computer games [Ierusalimschy et al, 1996] source: the LUA team

52 TerraME programming environment [Carneiro, 2006]

53 Source: Carlos Nobre (INPE) Can we avoid that this….

54 Fire... Source: Carlos Nobre (INPE) ….becomes this?

55 Deforestation in Amazonia ~230 scenes Landsat/year

56 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

57 Land use Change model Beef and milk market chain model Small farmers Medium and large farmers Land use Change model Small farmers Medium and large farmers Landscape metrics model Pasture degradation model Several workshops to define model rules and variables Landscape model: different rules for two main types of actors

58 Create pasture/ Deforest Speculator/ large/small bad land management money surplus Subsistence agriculture Diversify use Manage cattle Move towards the frontier Abandon/Sell the property Buy new land Settlement/ invaded land Sustainability path (alternative uses, technology) Sustainability path (technology) Small farmers in Amazonia

59 Create pasture/ plantation/ deforest Speculator/ large/small money surplus/bank loan Diversify use Buy new land Manage cattle/ plantation Buy calves from small Buy land from small farmers Large farmers in Amazonia

60 Local scale Regional scale CATTLE CHAIN MODEL Flows: goods, information, etc.. Connections: Agents LANDSCAPE DYNAMICS MODEL - Front - Medium - Rear INDIVIDUAL AGENTS Large and small farmers Local farmers Frontier Region SCENARIOS

61 Landscape model: different rules of behavior at different partitions which also change in time FRENTE MEIO RETAGUARDA Forest Not Forest Deforest River FRONT MIDDLE BACK SÃO FÉLIX DO XINGU

62 Modeling results 97 to 2006 Observed 97 to 2006

63 “Complexity is more and more acknowledged to be a key characteristic of the world we live in and of the systems that cohabit our world. It is not new for science to attempt to understand 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 subject to have much content, then particular classes of complex systems possessing strong properties that provide a fulcrum for theorizing and generalizing can serve as the foci of attention.” (from “The Sciences of the Artificial”, 1996) Some caution necessary... Herbert Simon (1958)

64 Modelling human-environment interactions 1. Situated individuals 2. Interaction rules: semantics of communication 3. Decision rules 4. Properties of space

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


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