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Simulations of Land Use ChangesSimulations of Land Use Changes
-- AGENTAGENT--LUC Model LUC Model
K S RajanInternational Institute of Information Technology, HyderabadInternational Institute of Information Technology, Hyderabad
[email protected]@iiit.ac.in
March 29March 29thth, 2007, 2007
International Workshop on
URBANIZATION, DEVELOPMENT PATHWAYS AND CARBON IMPLICATIONS
28-30 March 2007, Tsukuba, Japan
Source: Fukui, 1993
Land Use Change and Related FactorsLand Use Change and Related Factors
For 3 villages in Central Thailand
Villages that were Surveyed Per capita acreage of Paddy Land
Proportion of Population
commuting to WorkProportion of Upland Area
in Total Area
Land Use Change and Spatial FactorsLand Use Change and Spatial Factors
Earth (Environment )
Resource System(Land/ Water, Ecosystem)
Agricultural Land Use(Crop Choice)
Urban Land Use
Pastures/Grassland
Other Land uses
Farmer
Land Owner
Micro-sphere of Decision Making
Market Dynamics Cumulative Changes
in Environment
Changes in
Life Style
Macro-sphere of Decision Making
Policy Directions Migrations
Short termLong Term
Water Supply
Multiple Levels of Decision Making
Environment / Resource
System
MICRO
Sub-Models
SPATIAL URBAN
EXPANSION
MODEL
BIO-PHYSICAL
CROP MODEL
AGRO-ECONOMIC
Sub-Model
Behavioral
Models
Land UserLand Use Conversion - within Agriculture
MigrationAgent Decision Sub-Model
PopulationPrice Supply
Regulations
National Scenario Crop Demand Estimation MACRO
Sub-Model
International Market
Model Structure of AGENTModel Structure of AGENT--LUCLUC
Major Components are Major Components are --
�� Agent Decision ModelAgent Decision Model
�� Agricultural Income ModelAgricultural Income Model
�� BioBio--Physical Crop ModelPhysical Crop Model
�� Agricultural Cost Estimation ModelAgricultural Cost Estimation Model
�� Spatial Urban Expansion ModelSpatial Urban Expansion Model
�� Limited focus: Limited focus:
�� agricultural land useagricultural land use
�� simplified urban expansion.simplified urban expansion.
�� no forestry or industrial development.no forestry or industrial development.
�� Shifting Cultivation (in Laos version)Shifting Cultivation (in Laos version)
shorter
longer
Time
horizon
Decision Table
(Age, Education Level, Food Reserves)
Land Use Decision
Migration Decision
- No change
- Crop change
- Forest to Agriculture
- Agriculture to Urban
- Forest to Urban
- New lands
- To Nearest Urban Area
- Major Urban Center
Expected Increase
of Income (Grid-based)
Expected Risk
Age, Educational level
Expected Increase of Income
← Age
← Educational Level
Agent Decision ModelAgent Decision Model
Spatial Urbanization Model (SUM)Spatial Urbanization Model (SUM)
Industrial /Service Sector
GDP per capita
Urban GDP Share
Land Needs
Expansion of Urban Area
Current Urban Area
Transport
Infrastructure
Land Use Conversion
Potential
Rural to Urban
Migration
Population Growth
and Readjustments
Pull factorsTopography
Model Results Model Results –– An Example of Nan Province in ThailandAn Example of Nan Province in Thailand
Elevation Maps (L: Thailand; R: Nan Province)
Income Map of Nan Province
Legend
Examples of the MicroExamples of the Micro--Simulation Model Results [1]Simulation Model Results [1]
Urban Centre
No. of Households in Each Grid : 600
LU: Paddy(4); Maize(1,6,7,8); Paddy+Maize(rest)
Examples of the MicroExamples of the Micro--Simulation Model Results [Simulation Model Results [22]]
Income Graph (Around Urban Center)
-400000
-200000
0
200000
400000
600000
800000
1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11
in Bahts
Revenue Gen_Cost On_Farm_Inc Off_Farm_Inc Gross_Inc
Income Graph (Around the Urban Center)Income Graph (Around the Urban Center)
No. of Households in Each Grid : 83(1,2); 117(rest)
LU: Paddy(all grid points)
Examples of the MicroExamples of the Micro--Simulation Model Results [Simulation Model Results [3]3]
Income Graph (Far from Urban Center)
-400000
-200000
0
200000
400000
600000
800000
1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11in Bahts
Revenue Gen_Cost On_Farm_Inc Off_Farm_Inc Gross_Inc
Fixed Cost
Variable Cost
- Land Based
- Yield Based
Income Graph (Mainly Rural Area)Income Graph (Mainly Rural Area)
Model Simulated Total Migration in the Period 1980Model Simulated Total Migration in the Period 1980--9090
Model Simulation Model Simulation
of Land Use for of Land Use for
Thailand Thailand
19801980--19901990
Validation: 60-85% depending on
the Provinces
Model Simulation Model Simulation
of Land Use for of Land Use for
Thailand Thailand
19801980--19901990
Further Applications of Further Applications of the Modelthe Model
�� Application to BangladeshApplication to Bangladesh
��New multiNew multi--season approach to crop modellingseason approach to crop modelling
�� Involving such seasonal changes in decision makingInvolving such seasonal changes in decision making
�� Application to LaosApplication to Laos
��Shifting Cultivation Shifting Cultivation –– spatial and temporal changesspatial and temporal changes
��Forest land use changesForest land use changes
�� Application to IndiaApplication to India
�� Nature Conservation Nature Conservation vsvs Human Needs Human Needs
�� Water resourcesWater resources
�� Forest reserveForest reserve
Some ObservationsSome Observations
•• Rural areas are no more predominantly Rural areas are no more predominantly
Agriculture orientedAgriculture oriented
•• Spatial Location of the Rural landscape is Spatial Location of the Rural landscape is
important to understand the different Economic important to understand the different Economic
structuresstructures
•• Highly data intensive on SocioHighly data intensive on Socio--Economic Economic
characteristicscharacteristics
�������� Urbanization Modelling Urbanization Modelling --
SUMSUM
Vulnerability AssessmentVulnerability Assessment
-- Flood Impacts and SocioFlood Impacts and Socio--
Economic ConsequencesEconomic Consequences
Urbanization Model Urbanization Model
Simulations of Urban Land use & PopulationSimulations of Urban Land use & Population
19901990--21002100•• ObjectivesObjectives
–– To Develop Tools that forecast the To Develop Tools that forecast the Spatial extentSpatial extent of the of the Urban AreasUrban Areas
–– Incorporating the Economic growth, Migration and sprawl Incorporating the Economic growth, Migration and sprawl effecteffect
•• Simulation Tools Help understand the Impact Simulation Tools Help understand the Impact –– Shift of Population and Changing Dimensions of Shift of Population and Changing Dimensions of
•• NEEDNEED
–– Water and other resourcesWater and other resources
–– Economic sphere of influenceEconomic sphere of influence
•• DISASTERS/VulnerabilityDISASTERS/Vulnerability
–– Increased Populations at RiskIncreased Populations at Risk
•• Approach Approach –– Urban Agglomeration BasedUrban Agglomeration Based
3232
4848
3434
9999
60**60**
3737
7979
3737
5454
5353
4747
100100
4242
4141
BangladeshBangladesh
ChinaChina
FijiFiji
Hong KongHong Kong
India**India**
IndonesiaIndonesia
Korea, RepublicKorea, Republic
MalaysiaMalaysia
MyanmarMyanmar
PhilippinesPhilippines
PakistanPakistan
SingaporeSingapore
Sri LankaSri Lanka
ThailandThailand
Estimated Urban GDPEstimated Urban GDP
(%)(%)Country/TerritoryCountry/Territory
An Estimate of GDP of Urban Areas as An Estimate of GDP of Urban Areas as
Percentage of National GDPPercentage of National GDP
Source: "State of the Environment in Asia and the Pacific - 1990" Bangkok: The UN Economic and
Social Commission for the Asia Pacific. **FICCI estimates of 2005
Spatial Urbanization ModelSpatial Urbanization Model
Industrial /Service Sector
GDP per capita
Urban GDP Share
Land Needs
Expansion of Urban Area
Current Urban Area
Transport
Infrastructure
Land Use Conversion
Potential
Rural to Urban
Migration
Population Growth
and Readjustments
Pull factorsTopography
Relationships in the ModelRelationships in the Model
In-Migration to the Cities
Mt = β – ( γ . ln GDP pc,t )
where, β= 5.0846479; γ=0.4905977,
and GDPpc,t is the Per-capita GDP at time t
Population Growth
Pt = Po e(µ/ω).e(ωt - 1)
where, µ is the national population growth rate at initial time reference
t0 and ω is the exponential decreasing rate of national population growth
InIn--Migration FormulationMigration Formulation
•• Based on data of Japan since 1955Based on data of Japan since 1955
•• Considers Tokyo and the surrounding ProvincesConsiders Tokyo and the surrounding Provinces
•• Separates Natural Growth Rate with the Total Separates Natural Growth Rate with the Total Population changesPopulation changes
•• InIn--Migration is a proxy for all the regional and Migration is a proxy for all the regional and national population movementsnational population movements
•• Assumes that the Other Countries in Asia have Assumes that the Other Countries in Asia have similar Urbanization Patterns similar Urbanization Patterns –– Developmental Developmental PathwaysPathways
PPoopulation Changes 1980, 1990pulation Changes 1980, 1990--21002100Population in Bangkok and Surrounding Population in Bangkok and Surrounding
Provinces and its Ratio to ThailandProvinces and its Ratio to Thailand’’s total s total
PopulationPopulation
0
2
4
6
8
10
12
14
16
18
20
1980 1990 2000 2025 2050 2075 2100
Year
Population (in M
illions)
0
5
10
15
20
25
30
Percentages
Sim Total Popln (BKK+5 provinces) Ratio of (BKK+5 provinces) to Thailand
Urban PUrban Poopulation Changespulation Changes
1980, 19901980, 1990--21002100Share of Urban Population in Bangkok Share of Urban Population in Bangkok vsvs Total Total
Population in the RegionPopulation in the Region
0
2
4
6
8
10
12
14
16
18
20
1980 1990 2000 2025 2050 2075 2100
Year
Population (in M
illion)
0
10
20
30
40
50
60
70
80
90
Percentages
Sim Total Popln (BKK+5 provinces) Only Urban Popln % Urban Popln
Urbanization ModellingUrbanization Modelling
�������� Vulnerability AssessmentVulnerability Assessment
-- Flood Impacts and SocioFlood Impacts and Socio--
Economic ConsequencesEconomic Consequences
Where are We ?Where are We ?•• Most of the Major Cities are in the CoastsMost of the Major Cities are in the Coasts
•• Floods cause Human and Economic LossesFloods cause Human and Economic Losses
–– 5 fold in 30 years in Asia5 fold in 30 years in Asia
•• High rate of High rate of UUrbanization and population growth rbanization and population growth in coastal areas are likely to aggravate the situationin coastal areas are likely to aggravate the situation
What do we plan in this Research?What do we plan in this Research?•• Impact of floods in the Coastal CitiesImpact of floods in the Coastal Cities
•• Estimate Vulnerable Population and Risk COSTSEstimate Vulnerable Population and Risk COSTS
–– Spatial DistributionSpatial Distribution needed for Developing Responsesneeded for Developing Responses
Characteristics of Hue CityCharacteristics of Hue City
•• Hue City of Hue City of ThuaThua ThienThien Hue province is Hue province is
located in the central part of Vietnam.located in the central part of Vietnam.
•• Old Capital of Vietnam Old Capital of Vietnam –– Now a Tourist Now a Tourist
AttractionAttraction
•• Total area of the province is 5,009 kmTotal area of the province is 5,009 km2.2.
•• Total population is 1,050,000 in 1999.Total population is 1,050,000 in 1999.
•• 70% of the total natural land is mountainous.70% of the total natural land is mountainous.
•• Flood and storms are the main disastersFlood and storms are the main disasters
–– Almost AnnuallyAlmost Annually
Flood Depth Map Flood Depth Map –– Base SimulationBase Simulation
Figure: Flood Depth Map at Peak Discharge in Kim Long (03.11.1999) for Base Condition
Acknowledge: APN Project 2004-05
Flood Depth Map Flood Depth Map –– 30cm Sea Level Rise30cm Sea Level Rise
Figure: Flood Depth Map at Peak Discharge in Kim Long (03.11.1999) for 30 cm Sea Level Rise
Flood Depth Map Flood Depth Map –– 88cm Sea Level Rise88cm Sea Level Rise
Figure: Flood Depth Map at Peak Discharge in Kim Long (03.11.1999) for 88cm Sea Level Rise
Difference in Flood DepthDifference in Flood Depth
with 100cm and 30cm Sea Level Risewith 100cm and 30cm Sea Level Rise
SocioSocio--Economic SimulationsEconomic Simulations
•• Urban Area and Population ChangesUrban Area and Population Changes
–– Economic developmentEconomic development
–– Population GrowthPopulation Growth
–– MigrationMigration
–– Increase of Floor area per capitaIncrease of Floor area per capita
Spatial Simulation is carried out based on IPCC Spatial Simulation is carried out based on IPCC
SRES B1 Scenario of Economic growth and SRES B1 Scenario of Economic growth and
Population changesPopulation changes
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
2000 2025 2050 2075 2100
Year
Population (in M
illion)
0
1
2
3
4
5
6
7
8
Percentages
Sim Popln (Hue+4 districts) Share Ratio
Population in Hue and Neighboring Population in Hue and Neighboring
DistrictsDistricts
SocioSocio--Economic Impacts Economic Impacts –– Area Change in 2000, 2050 and 2100Area Change in 2000, 2050 and 2100
due to different levels of due to different levels of SeaLevelSeaLevel Rise Rise
0
50
100
150
200
250
300
350
Area-2000 Area-2050 Area-2100
Num
ber
of G
rids
Base in 1999 30cm Sea Level Rise 100cm Sea Level Rise
SocioSocio--Economic Impacts Economic Impacts –– Population affected in 2000, 2050 and 2100Population affected in 2000, 2050 and 2100
due to different levels of due to different levels of SeaLevelSeaLevel Rise Rise
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
Popln-2000 Popln-2050 Popln-2100
Popu
lation
(in
Mill
ions)
Base in 1999 30cm Sea Level Rise 100cm Sea Level Rise
Summary of the Vulnerability Summary of the Vulnerability
Assessment of Floods in Coastal CitiesAssessment of Floods in Coastal Cities
•• Flood modelling indicates the Impacts are Flood modelling indicates the Impacts are nearly nearly
samesame irrespective of Sea Level Rise here.irrespective of Sea Level Rise here.
•• Urban Area Urban Area –– almost 7 times in 2050 and 13 times in almost 7 times in 2050 and 13 times in
21002100
•• Urban Population is going up by 300%Urban Population is going up by 300%
•• Impacted Population goes up by 350%Impacted Population goes up by 350%
•• Though the Physical Impact is similar to the present Though the Physical Impact is similar to the present
times, the Sociotimes, the Socio--Economic Impact is many fold.Economic Impact is many fold.
Ongoing and Future WorksOngoing and Future Works
•• SUM SUM –– Application to Indian Cities just started Application to Indian Cities just started –– Hyderabad City, Hyderabad City, PunePune
(National Urban Renewal Mission)(National Urban Renewal Mission)
•• Green Building Policy and Urbanization Green Building Policy and Urbanization ––Mainly Energy use scenariosMainly Energy use scenarios
•• ChallengesChallenges
–– Moving from a Single City to Multiple City Moving from a Single City to Multiple City Urbanization Urbanization –– interactions within the countryinteractions within the country
•• CautionCaution
–– National Projections are being used as Parameters National Projections are being used as Parameters