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1 st Brazilian Symposium on Global Enviromental Change, Rio de Janeiro, March 2007 Modelling Land Change: The Scientific Challenges Gilberto Câmara Director National Institute for Space Research Brazil Model = a simplified description of a complex entity or process E 0 E 4

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modelling land change the scientific challenges

1st Brazilian Symposium on Global Enviromental Change, Rio de Janeiro, March 2007

Modelling Land Change: The Scientific Challenges

Gilberto Câmara


National Institute for Space Research


what is a model
Model = a simplified description of a complex entity or process



What is a Model?






  • income
  • land use
  • soil type

Model = entities+ relations + attributes + rules

source: Carneiro (2006)

what is computational modelling
What is Computational Modelling?
  • Design and implementation of computational enviroments for modelling
    • Requires a formal and stable description
    • Implementation allow experimentation
  • Rôle of computer representation
    • Bring together expertise in different field
    • Make the different conceptions explicit
    • Make sure these conceptions are represented in the information system
scientific challenges
Scientific Challenges
  • “Third culture”
    • Modelling of physical phenomena
    • Understanding of human dimensions
  • How to model human actions?
    • What makes people do certain things?
    • Why do people compete or cooperate?
    • What are the causative factors of human actions?
limits for models
Limits for Models

Uncertainty on basic equations

Social and Economic















Solar System Dynamics

Complexity of the phenomenon

source: John Barrow

(after David Ruelle)

public policy issues
Public Policy Issues
  • What are the acceptable limits to land cover change activities in the tropical regions in the Americas?
  • What are the future scenarios of land use?
  • How can food production be made more efficient and productive?
  • How can our biodiversity be known and the benefits arising from its use be shared fairly?
  • How can we manage our water resources to sustain our expected growth in urban population?
modelling land change in amazonia
Modelling Land Change in Amazonia









dynamic spatial models


tp + 10



Dynamic Spatial Models

tp - 20

tp - 10


source: Cláudia Almeida

challenge how do people use space



Small-scale Farming

Challenge: How do people use space?


Competition for Space

Source: Dan Nepstad (Woods Hole)

dynamic areas current and future
Dynamic areas (current and future)

Escada et al. (2005)

New Frontiers

INPE 2003/2004:

Intense Pressure



Future expansion


Clouds/no data


Altamira (Pará) – MODIS Image – 21 May 2004

Imagem Modis de 2004-05-21, com excesso de nuvens


Altamira (Pará) – MODIS Image – 22 June 2004

6.000 hectares deforested in one month!

amazonian new frontier hypothesis becker
Amazonian new frontier hypothesis (Becker)
  • “The actual frontiers are different from the 60’s and the 70’s
  • In the past it was induced by Brazilian government to expand regional economy and population, aiming to integrate Amazônia with the whole country.
  • Today, induced mostly by private economic interests and concentrated on focus areas in different regions.
modelling human actions two approaches
Modelling Human Actions: Two Approaches
  • Models based on global factors
    • Explanation based on causal models
    • “For everything, there is a cause”
    • Human_actions = f (factors,....)
  • Emergent models
    • Local actions lead to global patterns
    • Simple interactions between individuals lead to complex behaviour
    • “More is different”
    • “The organism is intelligent, its parts are simple-minded”
emergence clocks clouds or ants
Emergence: Clocks, Clouds or Ants?
  • Clocks
    • Paradigms: Newton’s laws (mechanistic, cause-effect phenomena describe the world)
  • Clouds
    • Stochastic models
    • Theory of chaotic systems
  • Ants
    • The colony behaves intelligently
    • Intelligence is an emergent property
statistics humans as clouds
Statistics: Humans as clouds
  • Establishes statistical relationship with variables that are related to the phenomena under study
  • Basic hypothesis: stationary processes
  • Exemples: CLUE Model (University of Wageningen)

y=a0 + a1x1 + a2x2 + ... +aixi +E

statistics humans as clouds22
Statistics: Humans as clouds

source: Aguiar (2006)

Statistical analysis of deforestation


Área de estudo – ALAP BR 319 e entorno (Aguiar, 2006b)


Estradas pavimentadas em 2010

Estradas não pavimentadas

Rios principais



BASELINE SCENARIO – Hot spots of change (1997 a 2020)

% mudança 1997 a 2020:

0.0 – 0.1

0.1 – 0.2

0.2 – 0.3

0.3 – 0.4

0.4 – 0.5

0.5 – 0.6

0.6 – 0.7

0.7 – 0.8

0.8 – 0.9

0.9 – 1.0


Estradas pavimentadas em 2010

Estradas não pavimentadas

source: Aguiar (2006b)

Rios principais


GOVERNANCE SCENARIO – Differences from baseline scenario (Aguiar, 2006b)


Protection areas


Estradas pavimentadas em 2010




Sustainable areas

Estradas não pavimentadas




Rios principais

the trouble with statistics
The trouble with statistics
  • Extrapolation of current measured trends
  • How do we know if tommorow will be like today?
  • How do we incorporate feedbacks?
complex adaptative systems
Complex adaptative systems
  • How come that a city with many inhabitants functions and exhibits patterns of regularity?
  • How come that an ecosystem with all its diverse species functions and exhibits patterns of regularity?
  • How can we explain how similar exploration patterns appear on the Amazon rain forest?
results of human society such as economies
Results of human society such as economies

Source: John Finnigan (CSIRO)

agents and ca humans as ants



10 to 20 anos

Recent Settlements

(less than 4 years)

Old Settlements

(more than 20 years)

Escada, 2003

Agents and CA: Humans as ants

Identify different actors and try to model their actions

different agents different motivations
Different agents, different motivations
  • Intensive agriculture (soybeans)
    • export-based
    • responsive to commodity prices, productivity and transportation logistics
  • Extensive cattle-ranching
    • local + export
    • responsive to land prices, sanitary controls and commodity prices

photo source: Edson Sano (EMBRAPA)

Large-Scale Agriculture

different agents different motivations33
Different agents, different motivations
  • Small-scale settlers
    • Associated to social movements (MST, Church)
    • Responsive to capital availability, land ownership, and land productivity
    • Can small-scale economy be sustainable?
  • Wood loggers
    • Primarily local market
    • Responsive to prime wood availability, official permits, transportation logistics
  • Land speculators
    • Appropriation of public lands
    • Responsive to land registry controls, law enforcement
agent model using cellular automata
Agent model using Cellular Automata


  • Small farms environments:
  • 500 m resolution
  • Categorical variable: deforested or forest
  • One neighborhood relation:
  • connection through roads
  • Large farm environments:
  • 2500 m resolution
  • Continuous variable:
  • % deforested
  • Two alternative neighborhood
  • relations:
  • connection through roads
  • farm limits proximity



the trouble with agents
The trouble with agents
  • Many agent models focus on proximate causes
    • directly linked to land use changes
    • (in the case of deforestation, soil type, distance to roads, for instance)
  • What about the underlying driving forces?
    • Remote in space and time
    • Operate at higher hierarchical levels
    • Macro-economic changes and policy changes
game theory and mobility
Game theory and mobility
  • Two players get in a strive can choose shoot or not shoot their firearms.
  • If none of them shoots, nothing happens.
  • If only one shoots, the other player runs away, and then the winner receives $1.
  • If both decide to shoot, each group pays $10 due to medical cares.
game theory and mobility37
Game theory and mobility

Three strategies

A - ((10%;; $200; 0)

B - ((50%;; $200; 0)

C - ((100%;; $200;; 0))

game theory and mobility38
Game theory and mobility
  • What happens when players can move?

If a player loses too much, he might move to an adjacent cell

flexible neighbourhoods
Flexible neighbourhoods

Consolidated area

Emergent area

Scale is a generic concept that includes the spatial, temporal, or analytical dimensions used to measure any phenomenon.

Extent refers to the magnitude of measurement.

Resolution refers to the granularity used in the measures.


(Gibson et al. 2000)

the trouble with current theories of scale
The trouble with current theories of scale
  • Conservation of “energy”: national demand is allocated at local level
  • No feedbacks are possible: people are guided from the above
the search for a new theory of scale
The search for a new theory of scale
  • Non-conservative: feedbacks are possible
  • Linking climate change and land change
  • Future of cities and landscape integrate to the earth system
nested cellular automata




Nested Cellular Automata

Environments can be nested

Multiscale modelling

Space can be modelled in different resolutions

computational modelling with cell spaces

Cell Spaces

  • Components
    • Cell Spaces
    • Generalizes Proximity Matriz – GPM
    • Hybrid Automata model
    • Nested enviroment
Computational Modelling with Cell Spaces

fonte: Carneiro (2006)

terrame functionality
TerraME functionality

fonte: Carneiro (2006)

global land project
Global Land Project
  • What are the drivers and dynamics of variability and change in terrestrial human-environment systems?
  • How is the provision of environmental goods and services affected by changes in terrestrial human-environment systems?
  • What are the characteristics and dynamics of vulnerability in terrestrial human-environment systems?
  • Carneiro, T., 2006. Nested-CA: a foundation for multiscale modeling of land use and land change., in PhD Thesis in Computer Science. INPE: São José dos Campos, Brazil.
  • Aguiar, A., 2006a. Modeling Land Use Change in the Brazilian Amazon: Exploring Intra-Regional Heterogeneity, in PhD Thesis, Remote Sensing Program, INPE: Sao Jose dos Campos
  • Escada, M.I.S., 2003. Evolução de Padrões da Terra na Região Centro-Norte de Rondônia. 2003, INPE: São José dos Campos. p. 164.
  • Escada, M.I.S., et al.,2005. Padrões e Processos de Ocupação nas Novas Fronteiras da Amazônia: O Interflúvio do Xingu/Iriri Estudos Avançados, 19(54): p. 9-23.