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Urban Growth Simulation and Geospatial Web for Planning Support. PhD Researcher, Dong Han Kim Centre for Advanced Spatial Analysis. Outlines. Research Goal Study Area and Problem Context Modelling Urban Growth Visualizing Model Output Future Works. Research Goal. Research Goal and Method. - PowerPoint PPT Presentation
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Urban Growth Simulation and Geospatial Web for Planning Support
PhD Researcher, Dong Han Kim
Centre for Advanced Spatial Analysis
Outlines
• Research Goal
• Study Area and Problem Context
• Modelling Urban Growth
• Visualizing Model Output
• Future Works
Research Goal
Research Goal and Method
• Developing a urban growth simulation model and disseminating it by geospatial Web technologies to support planning policy making
• Explorative and descriptive
• Literature review, modelling, and experimental case study
Study Area and Problem Context
Study Area
Seoul
Seoul MetropolitanArea
Hwaseoung: Study area
South Korea
Study Area Characteristics
• Undeveloped rural area in Seoul Metropolitan Area until 2000
• Industrial and residential development began to occur afterward
• One of the fastest urbanizing area in Korea
• One of the most concerned area for sprawl
Land Cover 1985
Legend
Study area
Barren
Argriculture
Forest
Water
Wet land
Built up
Grass land
Land Cover 1990
Legend
Study area
Barren
Argriculture
Forest
Water
Wet land
Built up
Grass land
Land Cover 1995
Legend
Study area
Barren
Argriculture
Forest
Water
Wet land
Built up
Grass land
Land Cover 2000
Legend
Study area
Barren
Argriculture
Forest
Water
Wet land
Built up
Grass land
Land Cover 2003
Legend
Study area
Barren
Argriculture
Forest
Water
Wet land
Built up
Grass land
Land Cover 2006
Legend
Study area
Barren
Argriculture
Forest
Water
Wet land
Built up
Grass land
Conurbanisationdown to south
Suitability Analysis
• Developable lands in SMA– Excluding physically and
legally undevelopable land, significant amount of developable land are located in Hwaseoung
• What is happening and what can happen in future ?
Greenbelt
Leapfrog Development
• Individual manufacturing firms• Small scale or individual housing development
Population Trend
Urbanized Area
Total Area: 727 km2; Urbanized Area: 255 km2 (35.14%), As of 2008
Major Planning Problem/Agenda
• Sprawl of small scale(but lots of) industrial and residential developments
• Rapid loss of forest and agricultural land
• Development oriented policy without long term vision and citizen consensus
• Need for “centres” or “compact cores” for sustainable development
Modelling Urban Growth
Why Agent Based Modelling(ABM) ?
• Dynamic• Driving force of urban growth : Spatial behaviour
of individual agents• Bottom up approach can be joined with top down
intervention• Possible “hot spots” during growth simulation
(Emergence, Knowledge discovery)
Overall Model Building Process
Understanding ProblemContext
Data Analysis(Explanatory/Descriptive)
Simulation
Time matching, Parameter setting
Output Analysis
Calibration, Verification, Validation
Implementation
Toolkit: NetLogo, Repast
Conceptual model
EnvironmentDecision
ruleAgent
Policy Evaluation
Feedback
I am here now!
Model Outline (1)
• Simulating urban growth– Non-urban to residential use– Non-urban to service use– Non-urban to industrial use
• To support planning policy by simulating future urban growth under different policy scenarios
Model Outline (2)
• Hybrid approach (Combination of ABM and CA : Cells state affected by not only neighbourhood characteristics but also agent behaviour)
• Cell: 30m * 30m grid
• Agent: Household, manufacturing industry, retail
Model Outline (3)
Agent Location Decision
Logistic Regression
PhysicalVariable
(elevation, slope)
PhysicalVariable
(elevation, slope)
InstitutionalVariable
(regulation)
InstitutionalVariable
(regulation)
SocialVariable
(ownership, accessibility,
price)
SocialVariable
(ownership, accessibility,
price)
Development Probability Surface
Development Toolkit (1)
Functionality
Programming difficulty
NetLogo
Mason
Repast J/Phyton/.Net
Swarm
Development Toolkit (2)
• NetLogo • Repast
Visualizing Model Output and Reasoning Together
Disseminating Model Outcomes
• Knowledge, especially one about future, is of importance in making planning policy
• However, contemporary planning not only relies on knowledge but also requires a broader consensus among stakeholders
• Thus, sharing model outcome is a necessary step to support planning decision making and action
Java Applet
• Simple development
• User interactions on model parameter
• Inflexibility of data overlay
WebGIS Server
• Web 2.0, mesh up
• Spatial analysis on Web
• Requires heavy duty hardware
Google Earth
• Ease of use, wide availability
• Mesh up (Spatially explicit communication)
• OGC standard
• Dynamic KML
Dynamic KML
http://puff.images.alaska.edu/dynamic_kml.shtml
• Display a series of KML data in time sequence
• Applicable to cell changes and agent movement
Future Works
Next Step
• Conceptual model building– Agents behavior– Environment – Decision rules
• Bridging model and planning policy– Storytelling ?
Thank you !