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dc.contributorFaculty of Construction and Environmenten_US
dc.contributor.advisorShi, Wenzhong (LSGI)-
dc.creatorDeng, Fanyu-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/8342-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic University-
dc.rightsAll rights reserveden_US
dc.titleMonitoring and modeling of urban growth process using cellular automata : a case study of Dongguan city, Chinaen_US
dcterms.abstractUrbanization along with profoundly transformation of land use cover has become a universal and significant issue. China is at a high speed of developing, many mainland cities are witnessing amounts and rates of land conversion unprecedented in history. Rapid urban growth with no signal to slow down has caused problems of not only environment surroundings but also human social conflicts. Therefore, sustainable development plan is critical, however the first step it to learn an in-depth and comprehensive understanding of urban growth progress. This study aims to obtain a comprehensive understanding of urban growth progress with the case of a typical frantic expansion city. A multi-face knowledge is contributed by monitoring the expansion with quantified measurements and spatial temporal detection, correlation analysis with available driving forces with logistical regression model, and modeling the historical growth to modify the model for landscape prediction. Starting with the land use conversion matrices for general information, five spatial metrics ( CA, NP, LPI, LSI and MNN) and two local scales (township boundaries and regular blocks) are further adopted to quantify spatial temporal changes during each study period. It is concluded that besides the conjunct areas around city center, western border towns experienced a relatively surprising expansion. However, eastern towns represented a total high level of developing. In the next section of correlation analysis, two main parts of factors are explored: year round rivers and reservoirs are selected as physic factors, meanwhile transport accessibility and population density as socioeconomic. Different combinations of these factors are individually estimated and evaluated by a binary logistic regression model. Discovery of urban area allocation change is revealed by explanation of the coefficients. Largest contribution owes to the closure to urban areas,alteration of physical factors indicate the change of allocation intension. For the respective of third section, cellular automata model has the excellent capability of characterizing stochastic systems. In addition, it is compatible with GIS, and the outcome can be easily visualized. In this study, transition rules are explicitly expressed by a logistic function. Calibration is to modify the model parameters thus obtain the best performance. After exploration of historical periods, prediction of future urban pattern is experimented under designed conditions. Operation of spatial measurements on different design scenarios, impact of macro is packed into micro geographic extents. And the result is that incremental development will attach more conversion amount in the southern especially coastal areas.en_US
dcterms.extentxi, 73 pages : color illustrationsen_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2015en_US
dcterms.educationalLevelAll Masteren_US
dcterms.educationalLevelM.Sc.en_US
dcterms.LCSHUrbanization -- China -- Dongguan Shi.en_US
dcterms.LCSHCities and towns -- Growth -- China -- Dongguan Shi.en_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.accessRightsrestricted accessen_US

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Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/8342