在我国快速城市化进程中，缺乏动态化的评价依据，特别是缺乏以动态模拟技术为指导的城市绿地空间扩展的调控方法，是造成我国城市绿地布局与城市发展脱节的重要原因。. 为此，本项目以“3S”技术为平台，利用空间动态模拟技术探讨城市绿地扩展的科学调控。研究的主要内容包括：1）利用3S技术对不同时期城市高分辨率遥感影像解译的基础上提取城市绿地空间扩展的驱动因素，并基于Fragstats3.3定量评价各典型驱动因素下城市绿地空间扩展的分异趋势；2）基于空间马尔柯夫的元胞自动机模型技术，建立城市绿地空间扩展驱动因素机制模型，分析综合驱动因素下城市绿地空间扩展的规律；3）利用人工神经网络元胞自动机模型中城市绿地微观土地元胞的转换规则，建立城市绿地空间扩展的动态模拟模型，模拟预测未来城市化过程中绿地空间扩展的一般规律，并以此探索城市绿地布局的科学途径，为城市绿地的规划建设探索新的理论与方法。

In the process of China’s rapid urbanization, lack of dynamic evaluation basis, especially the regulative methods of urban green space expansion guided by the dynamic simulation technology has been the important reason of disjunction between China’s urban green space expansion with the urban development.. To solve these problems,based on 3S technology, explores the scientific regulation of urban green space expansion using dynamic simulation techniques. The main content of the study includes: 1) Extract the driving factors of urban green space expansion based on the interpretation of high resolution urban remote sensing image during different periods using 3S technology. Under Fragstats3.3 quantitative evaluation, predict the fractionation trends of urban green space expansion over typical driving factors. 2) Establish the driving factors model of urban green space expansion and analyze the urban green space expansion law under synthesized driving factors based on Markov cellular automata (CA) model techniques. 3) Using the transformational rules of urban green space micro land cellular under artificial neural network (ANN) and cellular automaton (CA) model, establish dynamic simulation model for the urban green space expansion to simulate the general process of green space expansion in the future urbanization process, which is as a way to regulate urban green space expansion and explore new theories and methods for the planning and construction of urban green space.