关键词: 城市空间扩展, 土地转化模型(LTM), GIS, 人工神经网络(ANN)

Abstract: The land transformation model (LTM), which couples geographic systems (GIS) with artificial neural networks (ANN) to simulate and forecast urban spatial growth is presented. Using ANN with its highly intelligent function, LTM can make a quantitative analysis on the relationship between social, political, environmental factors and urban growth, and then give a prediction of urban spatial expanding. The main approach of LTM includes three steps: first, select some appropriate impact factors and pretreat them; second, set up Artificial Neural Network and train; third, input all factors data and gain the prediction result. A map of urban growth probability was calculated and used to predict future urban patterns. Then, Beijing which underwent a rapid urbanization in the past years is selected as the research area, and it shows that this LTM has a good efficiency and it is a useful tool for simulating urban growth.

Key words: urban spatial expanding, land transformation model (LTM), GIS, artificial neural network(ANN)