Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.428142
Title: A dynamic settlement simulation model : applications to urban growth in Thailand
Author: Piyathamrongchai, Kampanart
ISNI:       0000 0001 3492 3215
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2006
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Abstract:
Evolution at the urban-regional scale reflects complex characteristics in connection with both space and time. An effective way to study urban- regional growth and expansion is to build a hybrid simulation model to represent spatial phenomena at different scales, capable of generating different scenarios in an observable simulated time period. This work reports an implementation of such a simulation model - the Dynamic Settlement Simulation Model (DSSM) - which has been developed based on integrating two different cell-based modelling techniques: cellular automata (CA) and raster GIS. The CA model is used to dynamically simulate the growth of urban cells consistent with a set of probabilistic rules which reflect the system's complexity. The raster GIS module plays the role of controlling mutually static and dynamic constrained spatial variables that significantly affect urban-regional growth. Conceptually, DSSM has been developed using a theory of spatial organisation based on the nodal region from which we need to infer the growth process of urban and regional development over space and time. DSSM has been developed using an object-oriented programming approach the model is composed of all the modules necessary to input the data, visualise the temporal simulation, and yield practical outcomes. For experiments, fabricated data at two different scales has been used to construct the model and explore different growth hypotheses. Furthermore, the model has been applied to two other sets of real data from two major cities in Thailand, Chiang Mai and Phitsanulok city, in order to evaluate its usability and efficiency. The simulation has produced acceptably accurate results when compared quantitatively to the actual land use/cover imagery of both cities. Finally, this work demonstrates how the model can be used as a part of a spatial decision support system (SDSS). It is able to provide other outcomes that represent the possibility of implementing predictive and scenario-based applications, which are applicable to urban and regional planning and related fields.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.428142  DOI: Not available
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