文章基本信息

标题：Modeling of urban growth using cellular automata (CA) optimized by Particle Swarm Optimization (PSO)
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作者：M. H. Khalilnia ; T. Ghaemirad ; R. A. Abbaspour 等
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2013
卷号：XL-1/W3
页码：231-234
DOI：10.5194/isprsarchives-XL-1-W3-231-2013
出版社：Copernicus Publications
摘要：In this paper, two satellite images of Tehran, the capital city of Iran, which were taken by TM and ETM⁺ for years 1988 and 2010 are used as the base information layers to study the changes in urban patterns of this metropolis. The patterns of urban growth for the city of Tehran are extracted in a period of twelve years using cellular automata setting the logistic regression functions as transition functions. Furthermore, the weighting coefficients of parameters affecting the urban growth, i.e. distance from urban centers, distance from rural centers, distance from agricultural centers, and neighborhood effects were selected using PSO. In order to evaluate the results of the prediction, the percent correct match index is calculated. According to the results, by combining optimization techniques with cellular automata model, the urban growth patterns can be predicted with accuracy up to 75 %.
关键词：Urban Growth; Cellular Automata; Particle Swarm Optimization; Logistic Regression