To characterize the urbanization patte quantitatively,a study on the mechanisms of the landscape patte formation could facilitate the understanding on urban landscape pattes and processes,the ecological and socioeconomic consequences of urbanization,as well as the establishment of more effective strategies for landscape management.In this study,we integrated a Geographic Information System (GIS)-based analysis on landscape patte with an artificial neural network (ANN) to quantitatively characterize the urbanization patte of the metropolitan area of Shanghai,China,and to establish an ANN model that could preferably simulate the responses of urban landscape patte to the natural and socioeconomic factors such as residence area,road density,population density,urban development history and the Huangpu River as an element of economic change.Our results showed that the ANN model seems appropriate for studying the nonlinear relationship among the forcing factors of urbanization and the urban landscape pattes,which provided an effective and practical approach for further understanding the mechanisms of the landscape formation patte and the reciprocal relationship between landscape spatial patte and ecological process.