An artificial neural network model of the landscape pattern in Shanghai metropolitan region
上海市景观格局的人工神经网络(ANN)模型

To characterize the urbanization pattern quantitatively and study the mechanisms on the formation of landscape pattern could facilitate the understanding on urban landscape patterns 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 GIS-based analysis of landscape pattern with an Artificial Neural Network (ANN) to quantitatively characterize the urbanization pattern of the metropolitan area of Shanghai, and to establish an ANN model which could preferably simulate the responses of urban landscape pattern to the natural and socioeconomic factors such as residence area, road density, population density, urban development history and Huangpu River. Our results showed that the ANN model seems appropriate for studying the nonlinear relationship among the forcing factors of urbanization and the urban landscape patterns, which provides an effective and practical approach for further understanding the mechanisms on the formation of landscape pattern and the reciprocal relationship between landscape spatial pattern and ecological process.