Complexity Settlement Simulation using CA model and GIS (proposal) Kampanart Piyathamrongchai...

Complexity Settlement Simulation using CA model and GIS (proposal)

Kampanart PiyathamrongchaiUniversity College London

Centre for Advanced Spatial Analysis

26 February 2003

Complexity Settlement Simulation using CA model and GIS CASA : 26 Feb 2003 : 2

Introduction

• Let’s introduce the work with this question ‘How growth of a city and its surrounding hinterlands?’

• Human geographers have attempted to answer this question by exploring many theories and models.

• Those are utilized as norm to explain the real urban phenomena in several parts of the world.

• Evolutions of computer graphic and geographic information sciences have resulted several new higher potential ways to model the urban growth phenomena.

• It’s still not delimitated of imagination, how complex of model can be applied by these technologies.


Introduction

Cellular automata model

Dynamic spatial model

t1 t2

Urban – Regional system


Introduction• Integrating DSM to CA model makes possibility to define complex spatio-temporal transition rules.

• Integrating DSM to the model makes possibility to use powerful GIS functions in order to reveal spatio-temporal behavior of urban and regional system.

• Integrating CA to DSM makes possibility to increasing the temporal process of phenomena into spatial analysis.

• Focus more in urban-regional system to implement the model is conceivable to set up cross-scale simulation framework.

• Focus more in urban-regional system into the complex model might be useful to improve some famous urban and regional theories.


Objective

To use of CA technique and GIS to model spatio-temporal complexity behavior of urban and regional system


Scope of this study

• To integrate the CA simulation technique and dynamic spatial model to reveal interaction of urban and regional system.

• To explore variables or indicators in order to measure the centrality and hierarchy of nodes (cities and towns in a region) and find out the interaction and diffusion pattern between entire nodes.

• To implement the complex settlement simulation model.

• To recommend the model in order to use as decision-base urban and regional management.


Study Area

• The study area is Bangkok municipality and surrounding towns

and communities.


Study Area


Study Area (Other choices)

• This might be reasonably to set up the simulation model to other regions of Thailand because Bangkok city is the apex metropolis. There are some difficulties to utilize outcomes of the model to this city.

• It might be easier and efficiency to perform the model and put it to use with the others that are taking after Bangkok city.

• Other regions, can be potentially investigated, for instance; ChiangMai and Phitsanulok in northern part, KhonKaen and NakornRatchasima in northeastern part etc.


Work Plans

1-5 6 - 12 13 - 24 25 - 28 29 - 36

• Background theories review• Literatures review

• CA Model and DSM implementation review• Data Collection• Data manipulation• Conceptual model • Model implementation• Data analysis and programming• Model Evaluation and Finalize the user product• Final writing up

• Quantify centrality, hierarchy and interaction of nodes

0%

100%

Month


In progress

• Background Review : To catch the concepts, several papers, notes, books and internet documents, concern to cellular automata, dynamic spatial model, urban and regional system theories, have being reviewed.

• Literatures Review : More precisely, the concerned papers and other documents have being explored critically.

• This should be finished at the tenth month and the end of first year of study respectively.

1-5 6 - 12 13 - 24 25 - 28 29 - 36

• Background theories review• Literatures review


Conceptual framework (temporary)

Dynamic Dynamic Spatial ModelSpatial Model CA and CA and

Diffusion Diffusion modelmodel

Decision rule of transition for generating or not generating a new cell

The CA model returns a new situation at time t such as size of urban suburban

Spatial Interaction Model

Population Model

Nodal Model

Hierarchy Modification Model

Spatial information in time t + 1 return to the dynamic spatial model

Spatial information from

time t will be used as base to generate a new situation in the next time step


Conceptual framework (temporary)

CA and Diffusion modelt1 -> t2

Urban form State at t2

• CA algorithm

• Mean information Field : MIF

• Size of urban objects

• Compactness index

• Predicted population

• Modified hierarchy of nodes

• Gravity model

• Sphere of influence

• Potential surface

• Centrifugal&Centripetal

• Core-Periphery model

Spatial interaction model

DSM

Decision rule of transition

• Accessibility

• Transportation

• Land use

• Urban-regional growth policy

• etc.

Sprawl index

Urban-region Growth Map

Dynamic maps

retu

rncr

iteria

byby


Next Steps to explore

• CA and Diffusion algorithms on GIS-based programming

• How to quantify sprawl index and making map

• How to implement spatial interaction model

• Which spatial interaction models are suitable for this simulation model

• The criteria and weight definition in DSM

• How to visualize the model as dynamic maps and urban –region growth maps


Expected Results

• The complex spatial model that can illustrate simulated results both in urban and regional scale.

• Dynamic maps represent the growth of cities and their neighbors.

• The framework of integration of CA model and dynamic spatial model.

• A flexible simulation model that can be improved as decision support system for urban and regional management.


Next Steps

• Defining specific study area and collecting preliminary data.

• Criticizing more concerned documents in order to fine-adjust the conceptual framework.

• Quantifying the centrality, hierarchy and interaction of nodes (cities and towns) in urban and regional scale.

• Preliminary model implementation for testing the model.

Complexity Settlement Simulation using CA model and GIS (proposal) Kampanart Piyathamrongchai...

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