Modelagem Dinâmica com TerraME: A Gentle Introduction Dezembro/09 Pedro Ribeiro de Andrade DSA/CCST/INPE

Modelagem Dinâmicacom TerraME:

A Gentle Introduction

Dezembro/09

Pedro Ribeiro de AndradeDSA/CCST/INPEhttp://www.terrame.org

MotivaçãoÉ crescente a demanda por modelos dinâmicos que permitam a

avaliação e o prognóstico dos impactos causados por mudanças ambientais e que considerem de forma integrada fatores sociais, econômicos, hidrológicos, climáticos e ecológicos.– Projeto Land Use and Cover Change - LUCC– Projeto GEOMA

?Fonte: (Carneiro,

2006)

Processo cognitivo no qual os princípios de uma ou mais teorias são aplicados para se produzir um modelo de um determinado fenômeno, sistema ou processo real.

Desmatamento ?

Teoria de Modelagem

If (... ? ) then ...

Fonte: (Carneiro, 2006)

Causa e Efeito

rainrain rain

N

Itacolomi do ItambéPeak Lobo’s Range


Área de estudo – ALAP BR 319 e entorno

ALAP BR 319Estradas pavimentadas em 2010Estradas não pavimentadasRios principais

Portos

new road

Data models but not process models

Geographic Information Systems (GIS)

Simulação Computacional

Caixa Preta

Variação de Temperatura

-40

-30

-20

-10

0

10

20

30

40

50

60

0 20 40 60 80 100

tempo (s)

gra

us

ce

ntí

gra

do

s

Entrada

Modelo1

Modelo2

Objetivo

Modelo3: 0,1

Modelo3: |f-o|/(|f|+|o|)

Source: (Carneiro, 2006)

TerraME:Terra Modelling Environment

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 LUALUA is the language of choice for computer games

[Ierusalimschy et al, 1996]source: the LUA team

Methodology: TerraME architecture & applications


Basic concepts

The Earth’s environment …

can be represented as a synthetic environment…

… where analytical entities (rules) change the space properties in time.

Several interacting entities share the same spatiotemporal structure.Fonte: (Carneiro, 2006)

TerraME’s way: Modular components

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

Temporal structure

Newly implanted

Deforesting

Slowing down

latency > 6 years

Iddle

Year of creation

Deforestation = 100%

Rules of behaviour Spatial relations

Source: [Carneiro, 2006]

Source: (Aguiar, 2003;; Carneiro, 2006)

CellCellularSpaceTrajectoryNeighbourhoo

d

( , )

Space

Cellular Space

AnariCells = CellularSpace {dbType = "ADO",host = "localhost",database ="c:\\terralibDB\\mas_lucc.mdb",user = "",password = "",layer = "celulas_500_Anari_1985_pasto",theme = "celulas_500_Anari_1985_pasto",select = {"object_id", "cover", "owner“}

}

r = Trajectory{cellularspace, function(cell) return cell.height > 50 end, function(c1, c2) return c1.height > c2.height end}

( , )

Trajectory

Source: (Aguiar, 2003)

Which objects are closer?


Which objects are closer?

Euclidean Spaces

Open Network Closed Network

GPM – strategies for building relations

GPM as a graphTo

Ag

en

t

Cell

a

b

a

b

c

c

Cell Agent

From

Vizinhança

createMooreNeighborhood(cs)cs:loadTerraLibGPM("name")cs:loadGALNeighborhood("file.gal")


Behaviour

AgentAutomata



Desmatamento > 70%

recémImplantada

desflorestando

saturada

Latência > 6 anos

Evolução Desflorestamento - Fazenda

recessão

crescimento

normal

time = 1997

time = 1988

time = 1994

Sistema EconômicoHybridSituated

Behaviour – State Machines

State{id = "MoveDown", Jump{ function(event, agent) return input == "raise" end, target = "MoveUp" }, Jump{ function(event, agent) return gate.y == 0 end, target = "Closed" }, Flow{ function(event, agent) gate.y = gate.y - 9 if gate.y <= 0 then gate.y = 0 end end}}

State Machine

Temporal model

1:32:00 Mens. 11.

1:32:10 Mens. 32.

1:38:07 Mens. 23.

1:42:00 Mens.44.

Execute an agent over the cellular space regions

Save the spatial data

Draw cellular spaces and agents states

Carrie out the comunication between agents

. . .return value

true

1. Get first pair 2. Execute the ACTION

3. Timer =EVENT

4. timeToHappen += period


time = Timer { Pair { Event{time = 1985, period = 1}, Message{ function(event) AgentRancher:execute(event) return 1 end} }, Pair { Event {time = 1988, period = 1}, Message { function(event) AgentSmall:execute(event) return 1 end} }}

Timer

myScale = Environment{ id = "MyScale", cs1 = CellularSpace{ ... }, -- ... csN = CellularSpace{ ... },

aut1 = Automata{ ... }, -- ... autN = Automata{ ... },

t1 = Timer{ ... }, -- ... tN = Timer{ ... },

sc1 = Environment{ ... }, -- ... scN = Environment{ ... },}

Environment

CellAgent

ForEachAgent ForEachCell

ForEachCellForEachNeighbor ForEachNeighbor

ForEachAgent

CellularSpaceSociety

Group Trajectory

DBMS

chuvachuva chuva

N

Pico do Itacolomido Itambé Serra do Lobo


Autômatos Celulares

DRY WET

(soilWater > infCap) ?

(soilWater <= infCap) ?


Simulationoutcome

fonte: Carneiro (2006)

STUDY AREA

Parque Nacional Serra das Emas

Fonte: (Almeida et al, 2008)

STUDY AREA

Dados de Entrada do Modelo


STUDY AREA

Propagação do Incêndio


Estimativa de Emissões por Desmatamento

Emissões de CO2 por Desmatamento de Floresta Primária na Amazônia e nos Estados (Modelo C1)

0

200

400

600

800

1000

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Ano

Mto

nCO

2

Acre

Amapa

Amazonas

Maranha

Mato Grosso

Pará

Rondonia

Roraima

Tocantins

Amazonia

Fonte: (Aguiar et al, 2009)

Deforestation

Forest

Non-forest

Deforestation Map – 2000 (INPE/PRODES Project)

km

Projetos de Colonização

10

8

15

1614

13

Projetos antigosNovos projetosProjetos planejados

km

Projetos de Colonização

10

8

15

1614

13



Federal Government induced colonization area (since the 70’s):

Small, medium and large farms. Mosaic of land use patterns. Definition of land units and typology of actors

based on multi-temporal images (85-00) and colonization projects information (Escada, 2003).

Deforestation in Rondônia


1985 to 1997

Source: adapted from (Carneiro, 2006)

Deforestation in Rondônia

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


0.0 – 0.10.1 – 0.20.2 – 0.30.3 – 0.40.4 – 0.50.5 – 0.60.6 – 0.70.7 – 0.80.8 – 0.90.9 – 1.0

% mudança 1997 a 2020:

Fonte: (Aguiar, 2006)

GOVERNANCE SCENARIO – Differences from baseline scenario


0.0 -0.50Less:0.0 0.10More:

Differences:Protection areas

Sustainable areasFonte: (Aguiar, 2006)

STUDY AREA

São Félix do Xingu

Fonte: (Costa, 2009)

Landscape model: different rules of behavior at different partitions

Forest

Not ForestDeforest

River

FRONT

MIDDLE

BACK

SÃO FÉLIX DO XINGU - 1997

Observed deforestation in 1997


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

Observed deforestation in 2006


Modeling results 97 to 2006

Observed 97 to 2006

Real Data

Simulation


Modelagem Multi-Escala

Athmosphere, ocean, chemistry climate model (resolution 200 x 200

km)

Atmosphere only global climate model

(resolution 50 x 50 km)

Regional climate model(resolution 10 x 10 km)

Hydrology, VegetationSoil Topography (e.g, 1 x 1 km)

Regional land use changeSocio-economic changes

Adaptation (e.g., 100 x 100 m)

Fonte: (Camara, 2009)

Acoplamento de Modelos

Fonte: (Piribauer, 2009)

TerraME Hoje

• Versão 1.0 Beta prevista para fevereiro/2010• www.terrame.org • Extensão para acessar outros tipos de dados

(pontos, linhas, etc.) como células• TerraME-GIMS (Graphical Interface for Modeling

and Simulation)• TerraME-HPA (High Performance Architecture)• Dificuldade para visualizar dinamicamente os

resultados dos modelos

http://www.terrame.org/

Documents

Modelagem Dinâmica com TerraME: A Gentle Introduction Dezembro/09 Pedro Ribeiro de Andrade DSA/CCST/INPE