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Because of its strong ability in capture the nature of complex systems, cellular automata (CA) have been widely used to simulate suburban land use changes and urban pattern evolution. Driving forces impacting suburban land use changes could be derived from the multi-temporal remotely sensed imageries to retrieve the transition rules of geographic CA (geo-CA). With the images of two stages ranging...
Principal component analysis (PCA) is a powerful technique for extracting structure from high-dimensional datasets. In this paper, a PCA based cellular automata (CA) model for modelling urban development is presented. Compared to the conventional method of retrieving CA transition rules, the PCA model needs a small number of principal components to account for most of the structure in the datasets...
A novel prototype, SimUrban, is developed to simulate urban development through the integrated GIS and cellular automata (CA) with hybrid transition rules. This new framework consists of three tiers: data, operation and display for different purposes. Based on Object-Oriented Technology (OOP), we built the SimUrban framework using ArcGIS Engine and VS.Net. The open framework has favorable extensibility...
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