中文摘要：

传统的城市土地扩张模型多为静态模型，无法呈现空间上每一时间点的土地利用状况，以元胞自动机（Cellular Automata）模型为代表的新型城市土地扩张模型虽然具有动态特性，但其无法描述影响城市土地扩张的智能体（Agent）之间所产生的多元变化结果。以多智能体系统（Multi—Agent System）理论为基础，建立城市土地资源时间和空间配置规则，构建了动态且能描述影响城市土地扩张的智能体（Agent）间互动关系的城市土地扩张模型，并以长沙市区为例，应用所构建之模型进行了城市土地扩张的实证分析。结果表明：该模型可以反映城市土地扩张的基本特征和规律．对于解释城市土地扩张的成因、理解智能体行为对城市土地扩张过程的影响是合适的。并且将模拟结果与遥感土地利用解译结果对比．1998年、2001年、2005年城市土地扩张模拟的点对点精度均达到68％以上，从而能够为政府和城市规划者制定用地政策提供辅助决策支持。

英文摘要：

The traditional urban land expansion model has paid much attention on a static state, and few scholars have focused research on land use change situations through time. Although the urban land expansion model based on cellular automata performs dynamic feature, the model fails to display the multivariate change results produced from different agents＇ behaviors. On account of the above reasons, this research has built up a set of spatial-temporal land resource allocation rule and developed a dynamic urban land expansion model based on multi-agent system, which can simulate the interactions among agents. What＇s more, this model is applied to analyze and simulate urban land expansion process taking downtown of Changsha city as a study area. The results show that this model can not only reflect basic characteristics of urban land expansion, but also help to explain the reasons for urban land expansion process and understand the effect of agents＇ behavior on urban land expansion, what＇s more, in contrast to simulation results with land use classification map from remote sensing images, the accuracies of the simulation reached over 68% according to the cell-by-cell comparison, which makes it possible to provide land use decision-make support to government and urban planners.