Urban Spatial Expansion Prediction Based on CA Model: A Case Study of Jinhu Coastal Area
SU Lei1,2,3, ZHU Jing-hai1,4, HU Ke-mei5, LIU Miao1
1. Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, China; 2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China; 3. Huludao Urban-Rural Construction Committee, Huludao 125000, China; 4. Department of Environmental Protection of Liaoning Province, Shenyang 110033, China; 5. Ministry of Environmental Protection of the People’s Republic of China, Beijing 100035, China
Abstract：Jinhu coastal area urban land distribution maps in 1990, 2000 and 2010 were compiled with the help of Erdas and ArcGIS, and they served as the basis for urban spatial expansion simulation. The authors used urban CA model which had time and space dynamic constraints to simulate Jinhu coastal area urban spatial form of 2020. The advanced nature of this model lies in the multi-time interval phase transition rule. It uses transition probability matrix to predict urban land total quantity as constraints of CA model, and utilizes logistic regression to adjust the transition rule of CA model. The authors calculated landscape pattern indexes of various stages and drew the following conclusions: the urban land shape complicated unceasingly, and the degree of fragmentation increased from 1990 to 2010; nevertheless, the urban land shape was becoming regularized and the degree of fragmentation tends to decline from 2010 to 2020. During the period of 1990-2020, the average patch size is on the rise, the influence of the largest patch is enlarging year by year, and the accumulation of urban land is accelerated. The geographical space of cities in Jinhu coastal area is gradually narrowed and, with the improvement of regional transportation conditions, the spatial integrated development of Jinhu will become an inevitable trend.
苏雷, 朱京海, 胡克梅, 刘淼. 基于CA模型的城市空间扩展模拟预测——以锦葫沿海地区为例[J]. 国土资源遥感, 2012, 24(3): 129-134.
SU Lei, ZHU Jing-hai, HU Ke-mei, LIU Miao. Urban Spatial Expansion Prediction Based on CA Model: A Case Study of Jinhu Coastal Area. REMOTE SENSING FOR LAND & RESOURCES, 2012, 24(3): 129-134.
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2012, Vol. 24 
